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Questions related to Satellite
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Gustavo Diniz
Gustavo Diniz
  • asked a question related to Satellite
Is there a known origin for the satellite peaks of the 3d Ag XPS spectra?
Question
5 answers
  • 3 Jan 2025
The XPS spectra of 3d Ag exhibit two characteristic peaks at binding energies around 367 eV and 373 eV. However, it also reveals two small satellite peaks near these characteristic peaks. Is the origin of these peaks known?
Relevant answer
  • 9 Jan 2025
Answer
Jürgen Weippert thanks for the references! Yes, I am familiar with shake-up effect, but still these references were very helpful. Thanks again!
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Samodh Ammini Nivas
Samodh Ammini Nivas
  • asked a question related to Satellite
Tourism Satellite account
Question
2 answers
  • 19 Dec 2024
Does anyone knows the working of tourism satellite account especially estimation of indirect contributions and i/o analysis , kindly send me message as in need to understand it , this framework is what i am researching at present
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  • 1 Jan 2025
Answer
sir I do not know about input out analysis and how it is been conducted , can you send me some sources or suggest areas where i can get basic information as it is needed for my phd thesis
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Md. Shawkat Islam Sohel
Md. Shawkat Islam Sohel
  • asked a question related to Satellite
Creating AI driven automatic dashboard to process satellite images?
Question
3 answers
  • 21 Nov 2024
Is there anyone on ResearchGate with expertise in creating dashboards that can process satellite images and data, and visualize the findings in real time, similar to the Sentinel Hub dashboard (https://apps.sentinel-hub.com/dashboard/#/)? Any guidance or information on this would be greatly appreciated!
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Relevant answer
  • 16 Dec 2024
Answer
Md. Shawkat Islam Sohel .... Md, I'm confused, sentinel-hub captures the images and (via subscription) offers 4 levels of monthly processing plans. What added image processing / analysis do you want ???
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Ibrahim Bathis K
Ibrahim Bathis K
  • asked a question related to Satellite
How can we estimate the Biodiversity richness using remote sensing and GIS Application?
Question
9 answers
  • 11 Dec 2024
I am sure about the NDVI products deprived from the satellites images will provide the vegetation richness. However, I wanted to know how can estimate the Biodiversity (only Flora) richness using NDVI or any others means of method available.
Instead of a generalized explanation, I expect a detailed explanation. Any similar studies has carried out by any researchers, then please tag the research paper for references and further clarity.
Thank you
Relevant answer
  • 11 Dec 2024
Answer
Ibrahim Bathis K
Assessing plant biodiversity using NDVI or other similar remote sensing methods requires a careful approach, as NDVI (Normalized Difference Vegetation Index) and similar indices primarily measure the density and health of vegetation but do not directly provide information about species diversity. However, there are various approaches that can help assess plant biodiversity using NDVI and other methods. Here are some ways you can approach this task:
1. NDVI as an Indicator of Vegetation Density
NDVI is useful for assessing the density and health of vegetation, which can indirectly indicate biodiversity:
  • NDVI time series: By observing changes in NDVI over time, you can analyze how vegetation density and health change with different seasons or climatic conditions. Higher plant species diversity usually implies greater variation in vegetation density, which can be useful for assessing biodiversity.
  • Spatial variability of NDVI: In some ecosystems, greater variability in NDVI values can indicate a higher number of different plant species. Spatial maps showing NDVI variability can reveal habitat heterogeneity and different vegetation types.
2. Using Other Indices for Biodiversity Assessment
  • Maps of different vegetation covers: In addition to NDVI, satellite data can be used to create maps that show different types of vegetation (e.g., forests, grasslands, aquatic ecosystems). Vegetation cover, together with NDVI, can give a better picture of plant biodiversity.
  • Plant diversity index: In some cases, indices such as the Shannon-Weaver index or Simpson index can be used based on satellite data that indicates different vegetation types in an area. These indices assess species diversity based on vegetation distribution.
3. Satellite Imagery Classification Algorithms
  • Land cover classification: Using satellite image classification techniques (e.g., maximum likelihood, machine learning), you can identify different plant communities or species. Classifying different vegetation types based on spectral characteristics can give you an idea of the plant diversity in that area.
  • Spectral difference analysis: Different plant species have distinct spectral signatures, which can be used to differentiate them. By utilizing these spectral differences (e.g., across visible and infrared bands), various plant species can be identified and biodiversity assessed.
4. Combining Methods
  • Integrating NDVI with species data: If you have actual data on plant species (e.g., from field surveys or databases), you can combine this data with NDVI indices to assess plant biodiversity. For example, if the species present in a given region are known, you can analyze how NDVI corresponds to the diversity of those species.
  • Biodiversity modeling: Using models like MaxEnt (Maximum Entropy) or other species distribution modeling tools, you can combine NDVI data with local climatic conditions to predict the likelihood of different plant species’ presence in an area.
5. Ecosystem Dynamics and Habitat Heterogeneity
Vegetation diversity usually implies a higher degree of habitat heterogeneity. Disturbed or monotonous habitats, such as monoculture plantations, generally exhibit lower plant diversity, while more heterogeneous habitats (e.g., natural forests, tropical rainforests) have a greater number of different plant species.
While NDVI and other satellite-based indices do not provide direct data on the number or types of plant species, they are useful for assessing vegetation density and the health of ecosystems. By combining NDVI with other tools such as land cover classification, spectral indices, and methods like species modeling, a relatively accurate estimate of plant biodiversity can be achieved.
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WonMoo Kim
WonMoo Kim
  • asked a question related to Satellite
Time delay of a satellite (general relativity): How much time delay for a satellite?
Question
1 answer
  • 30 Oct 2024
I have a question on general/special relativity for a realistic situation. I looked for the answer to find the answer on the internet which is summarized here, but found it hard to accept for the reason given here.
Suppose
1) There is Earth whose radius is /R/ and mass /M/, for simplicity the Earth is sphere, and no rotation and no revolution around the sun. (for simplicity, lets say the earth is a point mass and R=0)
2) There is a significantly tall mountain on the Earth whose height is /r/. There stands the observer A.
3) A satellite of mass /m/ (M >> m) is orbiting the earth at altitude /r/, i.e., it passes right through the observer A every time it orbits. On the satellite is the observer B.
4) Also suppose there is an observer at the surface of the earth, the observer C.
5) (optional) Suppose there is an alien observer D, far away from the gravity, staying still relative to the Earth, not accelerating.
What is a time delay between A and B?
The internet only has comparison between B and C. it says, with some realistic parameters, there are two effects cancelling each other, namely
a) time delay due to gravity difference (general relativity) - difference between gravitational delay for B (at R+r) and C (at R) ~ B clock gains 45 microseconds/day :: This, I understand. OK, let's call this the general effect.
b) time delay as B is fast moving against C (special relativity) - due to velocity time loss B clock lose 7 microseconds/day :: Hmm...?? Shouldn't the effect be symmetric? You may also say C is fast moving against B. I don't think this affects the time delay. -> let's call this the special effect.
=> Thus the internet concludes the net time gain is :: B clock runs faster by 45-7=38 microseconds/day against C.
I don't understand regarding b) explanation.
Let's say, for simplicity R=0, and compare A (one on the mountain at /r/) and B (satellite at /r/).
From A's point:
- The general effect is valid, but as A and B are of same altitude (same gravitational potential), there is no time difference between A and B in terms of gravitational dilation. (cf. yes, B and C (one at the surface) will have difference => Let's say this delay rate is /delta/.)
- As B is orbiting, it accelerates, and this acceleration produces the effect of minus /delta/, which is the exact opposite.
=> Thus, the clock A lags behind at the rate of /delta/
From B's point
- The satellite B is free-falling, which means B feels no acceleration (may think s/he's still or at constant velocity; locally inertial). (So B's clock ticks same as D,) and there is no time delay for B.
- The one the mountain, A, is under the influence of gravity, so the clock delays at the rate of /delta/.
=> Thus, the clock A lags behind at the rate of /delta/
However, if you follow the internet argument, the difference should be "/delta/ - (cancellation due to fast motion)" rather than "/delta/".
Which is correct? Thank you for your insight.
(further stupid question) If there is nothing else in the space, but the point mass Earth and two observers B (satellite) and D (alien), Can B and D conclude who's actually orbiting (moving)?
Relevant answer
  • 8 Nov 2024
Answer
Your question touches on a variety of subtle concepts in general and special relativity, particularly the way time dilation effects interplay in different gravitational and inertial reference frames. Let's go through your points one by one to clarify the issues, starting with the two key effects you mentioned:
1. Gravitational Time Dilation (General Relativity)
This is the effect where clocks run slower in stronger gravitational fields. The general effect you're referencing between observers A (on the mountain) and B (in orbit) is due to the difference in gravitational potential. Since both A and B are at the same altitude (r), you are right that there is no difference in gravitational time dilation between them. Both A and B are subject to the same gravitational potential (because they're at the same radial distance from the center of Earth), so there is no gravitational time dilation between A and B. This means that the time dilation due to gravity between A and B is zero.
Now, for comparison:
C (at Earth's surface) is in a stronger gravitational field than A or B, so C’s clock runs slower due to gravitational time dilation compared to A and B. This causes a time difference between C and B (or A).
2. Special Relativistic Time Dilation (Due to Velocity)
This effect is because objects moving relative to one another experience time differently. From your description:
B (the satellite) is orbiting and moving at a significant velocity relative to A (on the mountain). This causes special relativistic time dilation, where B’s clock ticks more slowly from A’s perspective. The velocity of the satellite causes this time dilation, but only when considering special relativity.
The internet explanation suggests that B's clock loses time relative to C due to B's orbital velocity. However, as you rightly pointed out, if we apply this reasoning symmetrically, there should also be an effect on A due to the velocity difference between A and B.
3. Symmetry of Special Relativistic Effects
Here’s where confusion arises. The special relativistic time dilation effect is not symmetric between A and B in the same way that gravitational time dilation is not symmetric in the Earth-frame. From B’s perspective, A is moving, and thus A’s clock would appear to tick slower. Similarly, from A’s perspective, B is moving and would experience time dilation as well. However, the difference between A and B's velocities is much smaller than the difference between B’s velocity and C’s velocity, so the net special relativistic effect is much smaller between A and B than it is between B and C.
4. Why is the Special Relativistic Time Dilation Effect Between A and B Negligible?
The key point here is that both A and B are moving in the same gravitational field. The only difference is that B is moving very fast in orbit, while A is stationary on the mountain. In relativity, the key is not just the relative motion but also the acceleration and the reference frame you're considering. B’s orbit involves an inertial frame (at least locally), whereas A, being on Earth, is under the influence of Earth's gravity and is not in an inertial frame. This creates the apparent discrepancy between the effects.
If we are trying to directly compare the clocks of A and B:
Gravitational time dilation: There’s no effect because A and B are at the same radial distance from the center of Earth (the same gravitational potential).
Special relativistic time dilation: A's and B's relative motion is small compared to B’s motion relative to C, so this effect is very small between A and B.
5. Conclusion About Time Difference Between A and B
You’re correct to point out that the net effect between A and B should primarily come from their relative velocities. Since B is moving very fast relative to A, it’s the special relativistic time dilation that would cause a very tiny difference. But the difference between A and B will be very small compared to B and C.
Final Clarification:
To summarize the net time difference:
Gravitational time dilation between A and B: 0 (same gravitational potential).
Special relativistic time dilation: A and B experience a small difference because of their relative velocity, but this is negligible compared to the effect between B and C.
Thus, the net effect on B's clock compared to A’s will be a small time dilation due to velocity (special relativity). There’s no cancellation of effects as suggested by the internet; the effects are additive and non-zero between A and B, but very small.
Further Question: Can B and D Tell Who's Orbiting?
In a simplified scenario where only Earth (a point mass) and two observers, B (in orbit) and D (far away), are involved:
B (the satellite) is in orbit and feels a centripetal force, so it is accelerating in its own frame (from the perspective of an inertial observer, it’s in free fall).
D, far away from any gravitational sources, would be stationary in a uniform inertial frame.
B and D cannot tell who is moving relative to whom without additional information. In general relativity, motion is relative, and there is no absolute frame of rest. However, if B were to emit a signal, D could detect the Doppler shift of the signal, indicating that B is moving relative to D. But this is based on relative motion, not absolute motion.
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Hamaad Raza Ahmad
Hamaad Raza Ahmad
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Can we assess apple 🍎 yield using satellite image please guide me ?
Question
1 answer
  • 11 Oct 2024
want to work on it
Relevant answer
  • 11 Oct 2024
Answer
You can assess apple yield using satellite imagery by employing UAVs with deep learning for fruit detection and analyzing multispectral images with machine learning models. Additionally, monitoring growth patterns through time-series data can enhance yield predictions.
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Lee Edward
Lee Edward
  • asked a question related to Satellite
What is the collection of articles on the Luojia 3-01 satellite?
Question
1 answer
  • 9 Oct 2024
What is the collection of articles on the Luojia 3-01 satellite?
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  • 9 Oct 2024
Answer
We have collected 6 articles on Luojia3-01 Satellite from Geomatics and Information Science of Wuhan University. Hope these articles are useful to you.
A Fast and Accurate Orbit Prediction Method for Satellite On-Orbit Autonomous Mission Planning
Article link: https://jtp.oversea.cnki.net/Bilingual/detail/html/WHCH202406001?view=2
Bayer Interpolation Method by Integrating Color-Difference Gradient and Color Correlation
Article link: https://jtp.oversea.cnki.net/Bilingual/detail/html/WHCH202406002?view=2
Object-Space-Consistency-Based Real-Time Stabilization Approach for Luojia3-01 Video Data
Article link: https://jtp.oversea.cnki.net/Bilingual/detail/html/WHCH202406003?view=2
Application of Intelligent Video Frame Interpolation for Luojia3-01 Satellite
Article link: https://jtp.oversea.cnki.net/Bilingual/detail/html/WHCH202406004?view=2
Color Correction of Luojia3-01 Satellite Images with Partial Snow or Cloud Cover
Article link: https://jtp.oversea.cnki.net/Bilingual/detail/html/WHCH202406005?view=2
Area-Array Satellite Images Denoising Based on Bilateral Weighted Group Sparsity Residual Constraint Model
Article link: https://jtp.oversea.cnki.net/Bilingual/detail/html/WHCH202406006?view=2
More bilingual resources could be found via this link https://jtp.oversea.cnki.net/bilingual/.
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Kim Jee Hoon
Kim Jee Hoon
  • asked a question related to Satellite
Satellite orbit estimation using Recurrent Neural Network - what should I use?
Question
4 answers
  • 24 Feb 2021
Hello, I am a master's student studying in Yonsei Univeristy, Korea.
I am trying to estimate the state of satellite, using Neural Network.
Below is a simple flow of my study.
1. Train (t0 ~ t1)
Train neural network using known observation & true state data
2. Validation (t1 ~ t2)
Using observation data starting from t1, validate the network
3. Test (t3 ~ t4)
With new observation data, estimate the true ECI coordinate at different time.
[For all steps]
Input : observation data ( RADAR SEZ coordinate data or Orbital Element data )
Output : true data ( ECI coordinate data)
I know that the validation is already done while training,
but the validation part is for checking whether the network is well-trained.
I used "narxnet" from the deep learning toolbox, and it worked well until the validation part.
However, in order to use the network made with "narxnet" for the test part,
I had to retrain using data from just before.
(to estimate t3~t4, need tx ~ t3 data trained network)
So all my work have failed, and I am going to restart on doing this.
Here is what I want to ask.
  1. I found that most of codes in MATLAB related to neural network is for image training. Is it better to use other program for this type of work? (e.g. Python, Tensorflow...)
  2. I found that is it better to use recurrent neural network, and time series input. Is MATLAB "train" code available for this?
  3. I cannot find much information on the documentations. I would like to know if there is good example I can refer to.
Thank you very much for reading my questions.
Jee Hoon, Kim.
Relevant answer
  • 1 Oct 2024
Answer
When using Recurrent Neural Networks (RNNs) to estimate satellite orbits, a few important considerations come into play. First, you’ll need to gather and prepare historical data about the satellite, including its position, velocity, and external factors like gravitational influences or atmospheric drag. This data should be normalized for the network to perform effectively.
In terms of architecture, a standard RNN could work, but you’ll likely get better results with Long Short-Term Memory (LSTM) networks or Gated Recurrent Units (GRUs). These are designed to handle time-series data more effectively and are better at remembering long-term dependencies.
When you set up your input features, please be sure to include key orbital elements, such as the satellite's position and velocity, and possibly even external variables that impact the orbit, like solar radiation or Earth's gravitational pull. You should also experiment with the depth of the network, the number of layers, and how many timesteps the network should consider.
In developing your model, it’s crucial to test it against known satellite trajectories to validate the accuracy of its predictions. Metrics like Mean Squared Error (MSE) or Root Mean Squared Error (RMSE) can help gauge how well your model is performing. For satellite orbit estimation, LSTMs or GRUs are often the best choice, as they are well-suited to capturing complex patterns over time. I hope this helps; let me know if you need me to clarify anything in my comment! Cheers
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Ravi Kumar
Ravi Kumar
  • asked a question related to Satellite
Pixel rate calculation for Remote sensing satellites?
Question
4 answers
  • 23 Sept 2024
How to calculate pixel rate for AREA CCD detector and NEDT for IR sensors kindly provide calculation from frame rate by giving examples
Relevant answer
  • 27 Sept 2024
Answer
Ei Ei Khin Thank you
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Forqan Khalid Al-Daraji
Forqan Khalid Al-Daraji
  • asked a question related to Satellite
Question for researchers and specialists?
Question
1 answer
  • 8 Sept 2024
Question for researchers and specialists:
What are the most important remote sensing indicators and algorithms that can be used to estimate the shape of riverbeds and small streams? How can the accuracy of these estimates be improved using data available from satellites like Sentinel-2 and Landsat?
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  • 26 Sept 2024
Answer
Hi Forqan Khalid Al-Daraji,
To estimate the shape of water bodies using remote sensing, several important indicators and algorithms can be employed. Key indices like the Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and the Automated Water Extraction Index (AWEI) are effective for detecting and delineating water bodies in satellite imagery. These indices enhance the contrast between water and land features, making it easier to identify the boundaries of rivers and streams.
For algorithmic approaches, object-based image analysis (OBIA) can be particularly useful, especially when dealing with high-resolution imagery. Additionally, machine learning algorithms such as random forests or support vector machines have been applied successfully to classify water bodies and extract river morphology from satellite data.
However, when analyzing the morphology of rivers and narrow streams, spatial resolution is a critical factor. Landsat imagery provides a 30 m resolution, while Sentinel-2 offers a 10 m resolution. This may still be insufficient for capturing narrow water bodies accurately, especially when land adjacency effects become significant.
For more detailed comparisons of these methods, you might find the following papers helpful:
https://www.mdpi.com/2072-4292/13/1/137
https://www.sciencedirect.com/science/article/abs/pii/S0034425721000158
I hope this information assists you in your research.
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Abderrahmane Noui
Abderrahmane Noui
  • asked a question related to Satellite
Can groundwater be explored and detected by satellites?
Question
1 answer
  • 11 Sept 2024
Can groundwater be explored and detected by satellites?
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  • 12 Sept 2024
Answer
Soil moisture can be shown by multispectral satellite imagery, so shallow groundwater may be detected in some areas such as springs, seeps, or shallow lakes.
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Daniel Patón
Daniel Patón
  • asked a question related to Satellite
How can we compare SENTINEL vs LANDSAT for NDVI?
Question
1 answer
  • 17 Jun 2024
A question to see who can answer it. If the red and infrared bands of the satellites are these:
--------------------------------------------------------------------------------------------
Satellite.................................Landsat 8 / 9.................................Sentinel 2...................................
--------------------------------------------------------------------------------------------
....Red..............................Band 4: 0.64-0.67 μm.....................Band 4: 0.53-0.68 μm
Infrared............................Band 5: 0.85-0.89 μm....................Band 6: 0.70-0.80 μm
...................................................................................................Band 7: 0.81-0.92 μm
...................................................................................................Band 8: 1.20-1.30 μm
--------------------------------------------------------------------------------------------
Why do you use band 5 in Landsat and band 8 in Sentinel to estimate NDVI? Wouldn't it be more appropriate to use band 7 in Sentinel?
Thanks.D
Relevant answer
  • 19 Jun 2024
Answer
Band 5 in Landsat 8 and 9 represent NIR wich is more appropriate to calculate NDVI, for the Sentinel 2 the Band 8 (835.1nm (S2A) / 833nm (S2B)) is also in the NIR range its more appropriate than Band 7 (782.5nm (S2A) / 779.7nm (S2B)) which represent Red Edge 3. you can check the Sentinal 2 Wavelengths Bands in the link bellow :
https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED
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Vishva Deep Singh
Vishva Deep Singh
  • asked a question related to Satellite
How spectral bands and indices like (NDVI, NDBI) together used as input before supervised classification? In ArcGIS pro or any other software?
Question
1 answer
  • 7 Jun 2024
How Satellite Bands (Landsat/Sentinal) and indices (NDVI/NDBI) were composite together (Layer stacked) (In a single layer) before performing supervised classification (MLC/SVM/RF etc)? How it reduces the heterogeneity in data?
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  • 11 Jun 2024
Answer
To the best of my knowledge this is not a common practice in remote sensing to mix thematic rasters and continues rasters to perform supervised classifications,where did you learn this from if I may ask and what is the aim of doing that?
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Ruvimbo Tsomondo
Ruvimbo Tsomondo
  • asked a question related to Satellite
Download of Satellite Rainfall Estimates?
Question
2 answers
  • 3 Jun 2024
What is the easiest way to download daily precipitation data for CMORPH, PERSIAN, TRMM and CHIRPS?
Relevant answer
  • 6 Jun 2024
Answer
Try the Google Earth Engine (GEE), which provides a powerful platform for downloading these datasets.
// Initialize the CHIRPS dataset
var chirps = ee.ImageCollection("UCSB-CHG/CHIRPS/DAILY")
.filterDate('2022-01-01', '2022-12-31');
// Define the region of interest
var region = ee.Geometry.Rectangle([longitude1, latitude1, longitude2, latitude2]);
// Reduce the image collection to daily precipitation
var dailyPrecip = chirps.select('precipitation')
.filterBounds(region);
// Export the data to Google Drive
Export.table.toDrive({collection: dailyPrecip,description:'CHIRPS_Daily_Precipitation',fileFormat: 'CSV'});
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Syeda Hina Zainab
Syeda Hina Zainab
  • asked a question related to Satellite
How to get Turbidity from Turbidity Index?
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1 answer
  • 4 Jun 2024
Hello,
Using the satellite imaginary Ive calculated the Turbidity Index of a waterbody. Is it possible to convert NDTI into Turbidity (NTU)?
Relevant answer
  • 5 Jun 2024
Answer
Yes, if you find a published diagram that, under similar conditions, does the correlation. For example, take a look at the links below:
Definition of NDTI (turbidity index) and relation to NTU
https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2023JG007650
Definition and relationship of TSS and NTU
https://www.tecnoconverting.com/technical-articles/what-is-ntu/
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Minhazul Kibria
Minhazul Kibria
  • asked a question related to Satellite
Why having very high value of LST (Land Surface Temperature) after calculating from the (LANDSAT/LC08/C02) LandSat 8 collection 2 level 2 tier 1 data?
Question
4 answers
  • 28 May 2024
I have used the formula
LST = (BT / (1 + (0.00115 * BT / 1.4388) * Ln(ε))) for finding the JJA (June, July, and August) LST for California.
Where for BT (at satellite brightness temperature) I have used the 'ST_B10' band directly without re-scaling it since there are no brightness temperature bands in LandSat8 level 2 collection 2 Tier 1 data products and for calculating the emissivity (ε) I've used the re-scaled i.e. (ST_B10 = ("ST_B10" * 0.00341802) + 149.0) and cloud corrected ST_B10 band. When I use the formula (("ST_B10" * 0.00341802) + 149.0) following the LandSat8 handbook for LST, it shows a high value ranging from 10 to 70-degree degrees Celsius for California. I don't know what is wrong here and how to correct it. I am new to this field. Thanks in advance for any help you provide.
References: Weng et al., 2004-Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies.
Relevant answer
  • 30 May 2024
Answer
Hello
You can read about this problem in this topic:
https://www.researchgate.net/post/Why_LST_results_comes_higher_in_my_AOI
Good luck
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Dawod Rasooli Keya
Dawod Rasooli Keya
  • asked a question related to Satellite
Which satellite precipitation data are reliable for research study, especially with high resolution (5-10 minutes)?
Question
2 answers
  • 28 May 2024
As the experts know, to calculate rain energy and erosivity factor, rainfall intensity data in short periods of time is needed.
Relevant answer
  • 29 May 2024
Answer
You can't go wrong with WorldClim which has both monthly historical (1960-2020) and future (2020-2100) values for precipitation (and minimum and maximum temperature) at the 2.5-minutes highest spatial resolution for the historical values, and likewise, 30-secs for the future values.
[LINK]: https://www.worldclim.org
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Majid Lashkanpour
Majid Lashkanpour
  • asked a question related to Satellite
Satellite remote sensing by PCMODWIN4???
Question
1 answer
  • 22 May 2024
I am designing a software system for ordering satellite imagery in a way that by entering the specifications of the satellite orbit and its optical sensor, as well as the target ground area, it can determine the required time for the satellite camera to turn on.
To ensure that the weather conditions above the target area are suitable for satellite optical sensor imaging, can I use the PCMODWIN4 software???
In fact, I will perform the following steps:
  1. Obtain weather conditions (including temperature, wind speed, precipitation probability, humidity or water vapor, cloud type and density, pressure, etc.) above the target area in the next few hours from meteorological websites.
  2. Apply the necessary engineering for my problem to the PCMODWIN software and provide the above items as input to this software.
  3. Finally, obtain the pass window and, based on the working wavelength of the camera, determine whether this time is suitable for imaging or not.
Relevant answer
  • 23 May 2024
Answer
Of course it's possible, MODTRAN can simulate the radiance observed by satellites, which can input some atmospheric profiles and aerosol data. It is best to carefully read the relevant help files to set the parameters. In addition, you also need to input the solar zenith angle, satellite observation attitude, and camera spectral response function to obtain the radiance. Based on your own sensor response characteristics, set the gain, level, and exposure time parameters
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Mohammed Jalal Tazi
Mohammed Jalal Tazi
  • asked a question related to Satellite
Hydrothermal alteration mapping
Question
4 answers
  • 13 May 2024
What is the best satellite for mapping hydrothermal alteration, and what factors influence this choice?
Relevant answer
  • 19 May 2024
Answer
Mohammed Jalal Tazi
Salam Alaikum
Here are some of the best satellites for mapping hydrothermal alteration and the factors that influence the choice:
Best Satellites for Hydrothermal Alteration Mapping
  1. Landsat 8 and Landsat 9:Spectral Resolution: Landsat 8 and 9 offer 11 spectral bands, including visible, near-infrared (NIR), shortwave infrared (SWIR), and thermal infrared (TIR) bands. The SWIR bands are particularly useful for identifying minerals associated with hydrothermal alteration. Spatial Resolution: 30 meters for most bands, 15 meters for the panchromatic band, and 100 meters for thermal bands. Temporal Resolution: 16-day revisit cycle.
  2. Sentinel-2:Spectral Resolution: Sentinel-2 has 13 spectral bands, with bands in the visible, NIR, and SWIR regions. The SWIR bands are essential for detecting alteration minerals. Spatial Resolution: 10 meters for visible and NIR bands, 20 meters for red-edge and SWIR bands, and 60 meters for atmospheric correction bands. Temporal Resolution: 5-day revisit cycle when combining Sentinel-2A and 2B.
  3. ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer):Spectral Resolution: ASTER provides 14 bands in visible, NIR, SWIR, and TIR regions. Its high spectral resolution in the SWIR region (6 bands) is particularly advantageous for hydrothermal alteration studies. Spatial Resolution: 15 meters for visible and NIR bands, 30 meters for SWIR bands, and 90 meters for TIR bands. Temporal Resolution: Variable, generally 16 days.
  4. Hyperion (EO-1):Spectral Resolution: Hyperion offers 220 spectral bands covering the visible to shortwave infrared range (0.4 to 2.5 µm). This high spectral resolution allows for detailed identification of alteration minerals. Spatial Resolution: 30 meters. Temporal Resolution: Hyperion is no longer operational, but historical data can be valuable for research.
Factors Influencing the Choice of Satellite
  1. Spectral Resolution:Importance: High spectral resolution, particularly in the SWIR region, is crucial for identifying specific minerals associated with hydrothermal alteration, such as clays, carbonates, and sulfates. Example: ASTER and Hyperion are preferred for their extensive spectral bands in the SWIR region.
  2. Spatial Resolution:Importance: The spatial resolution determines the level of detail that can be resolved in the imagery. For detailed mapping of small-scale alteration features, higher spatial resolution is beneficial. Example: Sentinel-2 and Landsat 8/9 offer relatively high spatial resolution suitable for regional studies.
  3. Temporal Resolution:Importance: Frequent revisit times are essential for monitoring changes over time and capturing data during optimal conditions. Example: Sentinel-2 has a short revisit time, making it ideal for time-sensitive studies.
  4. Availability and Accessibility:Importance: The availability of data and ease of access can significantly impact the choice of satellite. Free and open-access data allow for more extensive and cost-effective research. Example: Landsat and Sentinel-2 data are freely available through platforms like the USGS Earth Explorer and Copernicus Open Access Hub.
  5. Historical Data:Importance: Access to historical data can help in understanding long-term changes and trends in hydrothermal alteration. Example: Landsat has a long historical archive dating back to the 1970s, providing valuable temporal coverage.
Recommendations
  • For Regional Mapping: Sentinel-2 is a strong choice due to its good balance of spectral and spatial resolution, frequent revisit times, and free access.
  • For Detailed Mineral Identification: ASTER is recommended for its superior spectral resolution in the SWIR region, essential for detecting specific alteration minerals.
  • For Historical Analysis: Landsat's extensive historical archive makes it suitable for studies requiring long-term temporal analysis.
  • For High Spectral Resolution Needs: Although no longer operational, Hyperion data can be highly valuable for detailed spectral analysis of historical events.
Please recommend this reply if you find it useful . Thanks
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Nagabhushan Rao
Nagabhushan Rao
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How can we Map availability and quality of Water using satellite images using AI?
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2 answers
  • 17 May 2024
Satellite images are available for various bandwidths. How can we reap benefits of AI to classify and recognise the status of water bodies? How can we predict the availability of quality water for human use and agriculture? How can we help the situation of drought and flood?
Relevant answer
  • 18 May 2024
Answer
We have to be careful not to make AI another Fad for the 21st century, as we did with other fads in the 20th century! Can AI be used to analyze data?
How Much Water is There on Earth? According to a 2019 Geological Survey
Here's a mind-boggling fact: a cubic kilometer of water equals about 264 billion gallons (1 trillion liters). About 3,100 mi 3 (12,900 km 3) of water, mostly in the form of water vapor, is in the atmosphere at any one time. If it all fell as precipitation at once, the Earth would be covered with only about 1 inch of water. Now, let's ponder: what could be the purpose of this measurement? Okay, there is too much chlorophyll or turbidity, but chlorophyll didn't have a large impact on turbidity, according to ArcGIS. According to them, there were some days when the turbidity was really high, and the levels of chlorophyll weren't. This means that the chlorophyll levels don't have a super big impact on turbidity. So, how will AI access water quality? I love to hear your thoughts!
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Omar Hazaymeh
Omar Hazaymeh
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Do satellite channels constitute a constructive or a destructive factor in linguistic development through the new vocabulary they produce?
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2 answers
  • 7 May 2024
Media, language
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  • 9 May 2024
Answer
If we accept the chronological change a language is subject to due to community interference as a natural matter , or phenomenon, it is , then, constructive, but, when we consider that as a harm that may affect the structure of the language, it is destructive.
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Mika Mika
Mika Mika
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Can you integrate multiple air quality map images (from satellite data) into a single image that depicts the average of all the images?
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2 answers
  • 1 May 2024
So I am conducting a research on changes in NO2 and aerosol index during a certain time period of 1 year. I am using sentinel-5 data. Following is the link:
s5phub.copernicus.eu
I used anaconda(spyder) to analyze the data, creating a map for each day. So in total, there are like more than 30 images. A made a collage of these for my manuscript but it doesn't look quite neat. And is a bit difficult to comprehend.
Is there any way I can integrate these images into one i.e. one image per month that reveals the average. Any tool or software that is acceptable for research purpose. I really need help with this.
Relevant answer
  • 4 May 2024
Answer
Hey there Mika Mika,
Absolutely, integrating multiple air quality map images into a single image to depict the average is a great approach for your research. Here's a method using Python and a library called Matplotlib:
1. **Data Preparation**: First, you'll Mika Mika need to download the images from the Sentinel-5 website and organize them properly.
2. **Python Script**: Write a Python script to read all the images, calculate the average, and create a new image.
```python
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
# Function to read an image and convert it to numpy array
def read_image(image_path):
img = Image.open(image_path)
return np.array(img)
# Function to calculate the average of images
def average_images(image_paths):
total_images = len(image_paths)
first_image = read_image(image_paths[0])
sum_image = first_image.astype(np.float64)
# Summing up all images
for path in image_paths[1:]:
img = read_image(path)
sum_image += img.astype(np.float64)
# Calculating the average
average_image = (sum_image / total_images).astype(np.uint8)
return average_image
# List of paths to your daily images
daily_images_paths = ["path_to_your_images/image1.png", "path_to_your_images/image2.png", ...]
# Call the function to get the average image
average_img = average_images(daily_images_paths)
# Save the average image
plt.imsave("average_image.png", average_img)
```
3. **Visualization**: You Mika Mika can also visualize the average image using Matplotlib.
```python
plt.imshow(average_img)
plt.axis('off')
plt.show()
```
This script will generate an average image from all the daily images you Mika Mika have. It's important to ensure that the images are aligned and have the same dimensions. You Mika Mika can adjust the script accordingly if your images have different sizes.
Some interesting articles to read are:
Feel free to reach out if you Mika Mika need further assistance!
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Shri Darshini
Shri Darshini
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Satellite Zenith Angle (SZA) product of Landsat 8 Level 1 product has values ranging from 1 - 2768. is there any scaling factors to be applied ?
Question
1 answer
  • 23 Apr 2024
usgs has not given any scaling factor values to be applied for level 1 products. but it also doesn't make sense for satellite zenith angle to have values from 1-2768.
Relevant answer
  • 24 Apr 2024
Answer
You may find the solution in the document:
https://www.usgs.gov/media/files/lsds-1928-landsat-8-olitirs-solar-view-angle-generation-add
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Gholamreza Nikravesh
Gholamreza Nikravesh
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To extract Normalised Difference Vegetation Index (NDVI), we should consider only reflectance concept on Sentinel images?
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1 answer
  • 8 Apr 2024
To extract Normalised Difference Vegetation Index (NDVI), we mustconvert satellite images from digital number to reflectance form? In other words, it is possible to extract NDVI directly from satellite images which are in Digital Number (DN) mood?
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  • 8 Apr 2024
Answer
Yes, from processing baseline 04.00, Sentinel-2 images are distributed with scale and offset (from https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-2-msi/processing-baseline):
L1C_TOAi = (L1C_DNi + RADIO_ADD_OFFSETi) / QUANTIFICATION_VALUEi
Offset is defined in metadata (check .XML file). In order to compute NDVI, you must convert to TOA first.
This applied to scenes from Jan 25, 2022.
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Abbas Kashani
Abbas Kashani
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Can the actual display of snow be shown as a map? Like snow border - snow depth - scDs snow levels - snow covered days - to find out the water storage
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1 answer
  • 31 Mar 2024
Can the actual display of snow be shown as a map? Like snow border - snow depth - scDs snow levels - snow covered days - to find out the water storage in the seasons?
Snow is a form of precipitation that behaves differently from other forms of precipitation due to the time delay between its occurrence and the time of runoff production and feeding of the underground water table. It is very important to study and measure changes in snow levels as one of the important sources of water supply. Due to the harsh physical conditions of mountainous environments, it is not possible to make permanent measurements on the ground to estimate the sources of snow and create a database. The use of satellite images and remote sensing due to their low cost, up-to-dateness and wide coverage is a way forward in this field and can be a suitable method for identifying snow catchment areas and evaluating its changes to achieve this goal. The area of snow cover is a very important parameter for the hydrological and climatological cycle. Its reflection caused by the whiteness above the snow causes the snow surfaces to return most of the radiant energy of the sun. Due to the high heat capacity of snow, snow surfaces protect the soil surface from the atmosphere and reduce the warming process in spring; Therefore, snow plays a direct role in microclimate and macroclimate scale atmospheric circulation models by affecting energy absorption and basin warming. Snow cover and soil moisture are the most important variables in the heat and moisture exchange process between the earth and the atmosphere. The presence of snow in the basin has a great effect on the moisture on the surface and as a result the runoff flow. Snow-covered surfaces undergo rapid and heterogeneous changes due to climatic and topographical factors. Most of the efficient methods of monitoring the snow extent are with the help of remote monitoring by satellites. The physical characteristics of snow have made it possible to monitor this phenomenon through remote sensing. Satellite is the best tool that can measure the snow cover of vast areas that can be determined by ground methods. It is not possible to show in different times (Simpson and State). The presence of snow in the catch basins is not only effective on the local and regional climate, but also affects the water resources that are stored in the form of frozen water on the surface. Therefore, temporal and spatial monitoring of snow cover has been used for hydrological forecasts for years. The use of satellite image data is effective in determining daily changes in snow cover, snow temperature, snow water depth and flood forecasting.
Relevant answer
  • 5 Apr 2024
Answer
Take a look at:
U.S. National Weather Service
National Operational Hydrologic Remote Sensing Center at:
https://www.nohrsc.noaa.gov/nsa/
also:
U.S. The Natural Resources Conservation Service, National Water and Climate Center
https://www.nrcs.usda.gov/resources/data-and-reports/snow-and-water-interactive-map
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Adebisi Agoro
Adebisi Agoro
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Can you please assist with generating a new DOI? and can we change or edit research profile on file??
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  • 20 Mar 2024
a
Coco G. WTClub Commemorative
https://www.facebook.com/story.php?story_fbid=pfbid0mxGLNTQV3k4s9K
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*President Bill Clinton *President Barrack Obama & *President Joseph Biden & VP Kamala Harris. *Historical Black Colleges* * Wilberforce University Xenia, Ohio. (ALUMNI) * * Black Farmers History Heritage Month * * 30 Years VOTE Democracy Grand Commemorative *
Bill Gates & Melinda Gates Foundation.
www. Azure Arc cloud; www. Azure Internet.com; Ai; Multi cloud Server applications; www.
NCBI.nlm.NIH.GOV/UNICEF/UN; ml; Hybrid Cloud; THINKSPEAK; Smart Lagos Arsenic
Water Quality Research Metals (SLAWQRM APP) Model Applications; (IaaS) (PaaS) (SaaS);
Microsoft Corporation GlobaI Pediatrics Health Care; Abort Medical Services Corporation; Planned Parenthood of Milwaukee, WI.
Https://www.ncbi.nlm.nih.gov/UNICEF.UN/ Mortality and Primary Causes of Death in
Mothers of Children / NIH / National Library of Medicine / (IaaS) (SaaS) Digital Output; (D) (Qin) flow; impacting Model (IaaS) Community. (PaaS) Maternal Healthcare. (PaaS) Satellite.
(SaaS) Clinics. (CMHSC). (Shared Networking);
STEAKHOLDERS
*Microsoft Global Health Specialist Rx; Care*
*Children Infant Pedialyte Supplements*
*Azure Aquatic Intelligence (TV) Awareness*
GET INVOLVE SUMMIT.
Pedialyte Water Dehydration; Outdoor Sports, Swimming and Fisheries (pH.) Toxicity Recreations Technical Proposal.
(IaaS) (PaaS) (SaaS)Digital Output; (D) (Qin) flow; to Smart (PaaS) Lagos State (SaaS) Arsenic Water Quality (Shared Networking) Research Metals (SLAWQRM APP) Model Applications; (IaaS) (PaaS) (SaaS) Online (AQUATIC AZURE WETLANDS Television (TV).
(SaaS)
impacting Metalliferous Contaminants Pollutant Effluent Events Systems; (SaaS) Digital Output; (D) (Qin) flow; to Coastal Federal highway’s flash waves flooding’s; dynamic cyclical riverine fate conveyor, transportation (Qin) flow; to Local Government Council Area roadway’s Storms Water Runoff; Pollutants Monitoring & Management Systems;(SaaS) Digital Output; (D) (Qin) flow; to
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(HRH) King of Lagos – Kabiyesi “Olu of Eko” Oba Rilwan Akiolu
Source: Billionaireproof.com
Impacting Midstream (SaaS) Digital Output; (D) (Qout) flow; to and in to YEWA River (SaaS)
Digital Output; (D) (Qout) flow; to OLOGE River (SaaS) Digital Output; (D) (Qout) flow; to OGUN River (SaaS) Digital Output; (D) (Qout) flow; to OSHUN River (SaaS) Digital Output; (D) (Qout) flow; to Midstream (IaaS)(PaaS) (SaaS)(Shared Networking);
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https://www.facebook.com/share/r/JkHMSeLVwdZFZVrS/?mibextid=oEMz7o
Https://www.ncbi.nlm.nih.gov.unicef.un/ Mortality and Primary Causes of Death in Mothers of
Children. / NIH / National Library of Medicine / impacting Model (IaaS) Community. (PaaS)
Maternal Healthcare. (PaaS) Satellite. (SaaS) Clinics. (CMHSC). (SaaS) (Shared Networking);
Relevant answer
  • 22 Mar 2024
Answer
Buenas tardes. Experiencia: logré asignar un DOI en preprint en Research Gate siguiendo los pasos de ésta plataforma para unos de los artículos de los estudiantes, esperamos tener obervaciones en la plataforma. No la obtuvimos, así que lo postulamos para la publicación en una revista de nuestro medio, en la cual siguió el proceso normal de revisión de pares para la publicación con lo cual se asignó un DOI final.
Me queda la duda si debemos eliminar el DOI inicial del preprint de Research Gate y eliminar los archivos de ésta plataforma y unicamente presentar el DOI y versión final de la publicación en la revista.
Saludos cordiales
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Deepthi ..
Deepthi ..
  • asked a question related to Satellite
Is the satellite hyperspectral data mosaiced or stitched?
Question
4 answers
  • 15 Mar 2024
Is the multispectral and hyperspectral satellite data that we downloaded from the USGS website, mosaiced or stitched? What percentage of overlap is used? Where can we find out this information?
Relevant answer
  • 22 Mar 2024
Answer
Deepthi .. INRE: "mosaiced or stitched". Without knowing the specifics, the answer is that "some is, and some is not". Some are even 'stitched' temporally for the real time products ( ex. https://www.nasa.gov/nasa-earth-exchange-nex/earth-observations-geonex/data-products/ ). The metadata for an individual granule / tile / scene may or may not include the overall information processing that occurred, those are in the documentation for the overall collection / campaign / application ( Ex. the NASAdem, which has evolved over decades from the original SRTM elevation only products to the current parallel NASADEM_SC data product layers including slope, aspect angle, profile curvature, plan curvature, and water mask. Another is the Harmonized Landsat and Sentinel-2 (HLS) series, and GeoNEX. If the product is from a commercial provider, there be even more factors.
You 'simply' want what is involved, unfortunately the algorithms in play for your specific data product may or may not be so simple - and for somebody else impossible without knowing exactly what you are referring to.
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Paul K. Sherard
Paul K. Sherard
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Do the orbits of space junk create a real hazard?
Question
1 answer
  • 15 Mar 2024
As is understood, for objects orbiting a large mass, at the same radial distance, the period of revolution (assuming circular orbits) is the same independent of mass. This means, objects of any mass in the same orbit move at the same velocity. Although, it is always stated that satellites can be struck by space “junk” at very high speeds. I can see this if the space junk is moving in an opposite direction in its orbit but if they are moving in the same direction the relative speeds should be negligible. Is the concern that most objects are in elliptical orbits and that orbits may intersect moving at different velocities? If that is the case, shouldn’t intersecting orbits be quite rare?
Relevant answer
  • 18 Mar 2024
Answer
I understand your question. Let's look at this question in more detail.
When we state that objects orbiting a large mass at the same radial distance have the same period of revolution, we are referring to Newton's principle of universal gravitation. According to this principle, the gravitational force between two bodies is determined by the mass of the bodies and the distance between them. For objects in circular orbit around a celestial body, the centripetal gravitational force that keeps the object in orbit is balanced by the centrifugal force due to orbital motion, resulting in a stable orbit.
This means that for objects of different masses orbiting in the same orbit, they move with the same orbital velocity. However, as you mentioned, the concern with space "junk" lies in the fact that these objects may be in different orbits and therefore moving at different relative speeds.
Space "junk" can consist of a variety of objects, such as fragments of decommissioned satellites, rocket stages, and other debris left in Earth orbit. Although they may share the same orbit initially, gravitational interactions with other celestial bodies, as well as non-gravitational forces such as solar pressure and atmospheric drag, can cause variations in orbits over time.
These variations can result in cross-orbits or trajectories that get close enough to pose a risk of collision with other orbiting objects. Therefore, even if objects in similar orbits initially move with similar orbital velocities, variations in orbits over time can lead to dangerous encounters in space.
In summary, while objects in similar orbits initially move with the same orbital speed, variations in orbits over time can result in significant relative velocities between these objects, increasing the risk of collisions in space.
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Clarence Lewis Protin
Clarence Lewis Protin
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What is the height of the orbit of a geostationary satellite ?
Question
2 answers
  • 25 Feb 2024
Researching this I routinely find that both the numbers 35768 km and 35786 km are given. Which one is correct or most accurate ?
Relevant answer
  • 1 Mar 2024
Answer
The correct height of the orbit of a geostationary satellite is approximately 35,786 kilometers (22,236 miles) above the Earth's equator. At this height, the satellite orbits the Earth at the same rate as the Earth's rotation, allowing it to appear stationary relative to a fixed point on the Earth's surface. This specific orbit enables geostationary satellites to provide continuous coverage of a particular area on the Earth's surface, making them ideal for applications such as telecommunications, weather monitoring, and broadcasting.
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Ariadna Mondragon-Botero
Ariadna Mondragon-Botero
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Does anyone knows where I can get free and CC by 4.0 satellite images?
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2 answers
  • 28 Feb 2024
The journal I want to publish in is asking that the satellite images I used (to show my remote field site) need to be CC by 4.0. Does anyone knows how can I obtain those images with good resolution?
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  • 29 Feb 2024
Answer
Thanks!!! I will try the website!
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Roy Liang
Roy Liang
  • asked a question related to Satellite
How does 3GPP NTN multi-beam bent-pipe satellite know which beam should be used to send signal?
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1 answer
  • 19 Sept 2023
Say, when it received a UE's signal from a specific beam, amplified the signal and sent it to the Gateway, how does the Satellite know which beam should be used?
Afterwards, if the Satellite received a signal from Gateway to specific UE, how does it know which beam to be used to send the signal back to the UE? after all, the bent-pipe Satellite doesn't maintain UE's RNTI, right?
Thanks.
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  • 6 Feb 2024
Answer
Did you get the answer?
If not, I was wondering if you are considering the case with earth fixed cells?
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Sipra Biswas
Sipra Biswas
  • asked a question related to Satellite
How to create a map of strip cultivation?
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2 answers
  • 26 Jan 2024
I want to create a map of specific cultivation, which is very narrow. It is not possible to identify in satellite image with 15 m resolution and also not possible to digitize on Google Earth Pro. Is there any process to extract the map with strip cultivation?
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  • 28 Jan 2024
Answer
The world is a very big place, so it would be helpful if you provided the extents of your AOI (Area of Interest) - the Latitude (Min, Max) and Longitude (Min, Max). Even better if you provided a shapefile or KML/KMZ as an attachment to your post (or in a Direct Message). There are all sorts of strategies to increase apparent resolution, but they are heavily dependent of local conditions of topography, vegetation, etc.
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Loc Loc
Loc Loc
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How can I calculate meter square from images which was segmented from satellite image?
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4 answers
  • 4 Jan 2024
I had a lot of satellite images and I already segmented them after previous step I wanted to calculate the real meter square of buildings which in the image from the images was segmented.
Now, I am stuck at this step please give me instructions or a formula
Thanks & Best Regards
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  • 8 Jan 2024
Answer
Dear Loc Loc ,
To calculate the real-world area in square meters from segmented building regions in satellite images, you'll need to perform a process known as "georeferencing" or "geo-referencing." This involves mapping the pixels in your segmented image to their corresponding locations on the Earth's surface.
https://eo4sdg.org/wp-content/uploads/2017/08/4.-Report_Pilot_Project_Colombia_v3-1.pdf
Regards,
Shafagat
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Anitha Vijayakumar
Anitha Vijayakumar
  • asked a question related to Satellite
Why did the NDBI values for a tropical urban area shows a decrease in Value when using Landsat 5 (1988 Jan 19) and landsat 8 (2020 Jan 27)?
Question
6 answers
  • 4 Dec 2023
Why did the Normalized Difference Built-Up Index (NDBI) values for a tropical urban area decrease from -0.03 in 1988 to -0.16 in 2020 when using Landsat 5 and Landsat 8 data? Given the expected urban growth, why do the NDBI values also differ (-0.82 to 0.62 in 1988 and -0.45 to 0.35 in 2020)? What factors could explain these changes, and how should we consider these differences when comparing data from different satellites and time periods?
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  • 9 Dec 2023
Answer
Nikolaos Tziokas
Dear Nikolaos Tziokas,
I wanted to express my sincere gratitude for your valuable insights and recommendations. Your suggestion to explore the paper on the evaluation of spectral built-up indices for impervious surface extraction using Sentinel-2A MSI imageries in Addis Ababa has been immensely helpful. I have downloaded the paper and am in the process of thoroughly reviewing it.
I am particularly intrigued by the mention of the SWIR band and the indices NBAI and BRBA, which do not rely on the NIR band. Your guidance aligns perfectly with my objective to investigate indices without the NIR band for NDBI analysis. I appreciate your willingness to share knowledge and point me in the right direction.
Thank you once again for your assistance. I am confident that the information from the paper will significantly contribute to my research and analysis.
Anitha
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Stefan Gohl
Stefan Gohl
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Does someone know how to use Quaternions to determine the orientation of a satellite in orbit?
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27 answers
  • 6 Aug 2015
I have given the GPS coordinates of the satellite (altitude, longitude, latitude) and the quaternion for every data frame of my detector which is attached to a satellite. Now, I wrote a C++ script to compute some angles that tell me the orientation of the satellite. I think I did everything like in the books, but the angles I get seem to be wrong. Unfortunately I don't see the error. contact me for more details if you like.
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  • 3 Dec 2023
Answer
Greetings to all
Assume I have the coordinates of satellite xs(t) and the ground station xg(t) in the Earth-Centered Earth-Fixed (ECEF) Coordinate System. Also, the attitude of satellites in the form of quaternions is available in the J2000 reference system. I want to correct the instantaneous vector D(t) = xs(t) – xg(t).
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Fakhreddin Moradi
Fakhreddin Moradi
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Does anyone have information about satellite leak detection from the water supply network? Is there any research in this field?
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4 answers
  • 20 Oct 2023
Does anyone have information about satellite leak detection from the water supply network? Is there any research in this field? Research has been done on the leak detection of lines that do not have asphalt on them, but no research has been done on the leak detection under the asphalt, which uses the dielectric property of water, and the knowledge is available to commercial companies.
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  • 7 Nov 2023
Answer
Probably maybe one way for satellite detection would synthetic aperture radar (SAR) inferometry ( Ex.
( not a great reference, but should give you an idea ). It would come with a lot of complexity, like dependencies on some set of baseline information ( the 'before leak' state ) and especially variation in the pavement surface, substrate, and soil types and behaviors when water is introduced ( some clay soils expand considerably when wetted ).
Another possibility might be that there is some amount of thermal lag for pavement over water during the daily cycle. "... this thermal delay will result in time lag between the peak surface temperature and peak temperature at other positions ". Maybe looking at the NASA applications of EMIT https://earth.jpl.nasa.gov/emit/
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Ruben Portas
Ruben Portas
  • asked a question related to Satellite
Recommended satelite GPS tags for vultures?
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4 answers
  • 23 Oct 2023
Hi there,
I would like to know your experiences with GPS satellite trackers for vultures. We use mostly Eobs for areas with GSM and we are very happy. We will start a new project in a remote area in Namibia without cellphone network and we are looking into satellite trackers. Any advices based on your experience of trackers that perform (and advices on which ones do not perform) well?
Thank you in advance!
Regards,
Ruben
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  • 26 Oct 2023
Answer
You can either do this or also ask in this open forum. Both ways are not exclusive. I assume you don't have expertise on satellite tags for vultures to share with us? Ok, thank you then, move on.
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Arun S H
Arun S H
  • asked a question related to Satellite
Is there any additional input parameters are required for radiance estimation using SBDART model for TIR (10.8 micrometer) channel?
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1 answer
  • 21 Dec 2018
I have been using SBDART model for the simulation of brightness temperature difference between 3.9 and 10.8 micrometer channels. For 3.9 micrometer channel, the radiance and the corresponding brightness temperature obtained are in agreement with the satellite observations. For 10.8 micrometer channel, I am facing some problem. The Brightness temperature observed were much less than the expected values. Can anybody please give me a proper guidance so that i can solve the problem?
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  • 24 Oct 2023
Answer
Hi，i don‘t know how to set the output in the sbdart so that the model can simulate the radiance of 3.9um and 11um，i hope you can give some suggestions，thanks for a lot
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Jhony Benavides
Jhony Benavides
  • asked a question related to Satellite
How to monitor illegal irrigation operations through Google Earth Engine?
Question
6 answers
  • 20 Sept 2023
Dear all, I work for a big irrigation district. It seems that some farmers are illegally using irrigation water from the main canals at night which is prohibited. The crop areas are around 5-20 ha and are located in the Valle del Cauca region (Southwest part of Colombia). I'd like to know if there is a way of using RADAR (Sentinel-1) or multispectral data (Sentinel-2) through Google Earth Engine to determine if some fields have been recently irrigated. Thanks in advance for any reference or tutorial you might share.
Relevant answer
  • 4 Oct 2023
Answer
Thanks Glicherie Caraivan
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Arunima Panigrahi
Arunima Panigrahi
  • asked a question related to Satellite
In which time zone Landsat and Sentinel satellites are giving imagery?
Question
1 answer
  • 13 May 2020
In the metadata file of satellite images, image acquisition time is there. In which time zone format they are giving the data?
Relevant answer
  • 25 Sept 2023
Answer
UTC
Field Definition: The date and time at the beginning of the data acquisition period in UTC time zone.
https://www.usgs.gov/centers/eros/science/sentinel-2-data-dictionary#acquisition_date
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Harish Kumar K S
Harish Kumar K S
  • asked a question related to Satellite
How to Converting instantaneous PAR (μE/m^2/sec ) - - - - > Daily average insitu par( Einstein m-2 d-1) ?
Question
5 answers
  • 8 Aug 2018
I am estimating daily average Photosynthetically available Radiation (PAR) on ocean by using different par algorithm (Frouin - seadas algorithm, gregg and carder model etc.,).
I downloaded insitu par data from SEABASS. They are providing instantaneous par (μE/m^2/sec). But I need to generate correlation between insitu dalily average Par vs Satellite derived Daily average PAR (Einstein m-2 d-1).
I need guidance for converting insitu instantaneous par(μE/m^2/sec) into Daily average insitu par (Einstein m-2 d-1).
μE/m^2/sec - - - - > Einstein m-2 d-1.
I tried to by multiplying 864 with insitu instantaneous PAR. It gives very high value. For example insitu data recorded at 10 AM, But satellite passing around 2 PM. So I am not getting averaged par value.
Relevant answer
  • 23 Sept 2023
Answer
Hello, I've got the same question, perhaps you've found the answer How to Converting instantaneous PAR (μE/m^2/sec ) - - - - > Daily average insitu par( Einstein m-2 d-1)?
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Luís Pereira
Luís Pereira
  • asked a question related to Satellite
Calibrate satellite temperature data with in situ sensor?
Question
4 answers
  • 2 Aug 2023
Hi
I'm trying to find a solution for a problem related to satellote temperature data.
I work with intertidal environment, and I have temperature sensores deployed in these environment for years. Data shows the temperature observed by these in situ sensors are quite diferent from the satellite.
The problem is, I intend to do mechanistic species distribution models, but my mechanistic data was based on data colected by the in situ sensors, and these only exist on a few places, whereas the satellite data is everywhere.
Assuming, my in situ sensors are the 'correct ones', is there a way to calibrate the satellite data for the places where I have no sensors according to the diferences observed between satellite and in situ sensors in the places I do have sensors?
Thank you.
Cheers, Luís Pereira.
Relevant answer
  • 22 Sept 2023
Answer
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Borys Kapochkin
Borys Kapochkin
  • asked a question related to Satellite
Can tectonic faults form linear clouds?
Question
7 answers
  • 15 Sept 2023
Look please at satellite images of the linear cloud in the visual and infrared spectral ranges. https://en.sat24.com/en/eu/infraPolair Compare these linear clouds with a grid of tectonic faults with an azimuth of 62 degrees. These tectonic faults formed the Sea of Azov (a tectonic block of 140x140 km doun) and the Crimean peninsula (a tectonic block of 140x140 km up).
Relevant answer
  • 21 Sept 2023
Answer
Orographic uplift isn't the only atmospheric mass movement that positions a given volume of air with it's water vapor constituent into conditions for droplet formation, it is only the most obvious one on the windward side, and gravity wave linear clouds on the leeward side ( https://en.wikipedia.org/wiki/Lee_wave ). I say obvious because I live between two major mountain ranges, the Olympics and Cascades
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Assad H. Thary Al-Ghrairi
Assad H. Thary Al-Ghrairi
  • asked a question related to Satellite
What are the best type of satellite Image Segmentation?
Question
2 answers
  • 18 Sept 2023
Hi, I need to know the best type of satellite image segmentation according your experience
Best Wishes
Relevant answer
  • 20 Sept 2023
Answer
Dear Assad H. Thary Al-Ghrairi ,
Image segmentation is a very versatile technique which enables the identification of targets which range in size from a small cluster of pixels up to targets that fill an entire image. This post introduces segmentation and clarifies the different types of segmentation (semantic, instance and panoptic). It then discusses image annotation since this is very time consuming yet important task for segmentation projects. Some significant open source datasets are then reviewed, before there is a discussion about the range of models commonly used. The post wraps up with practical advice for approaching your first segmentation project.
https://medium.com/@robmarkcole/a-brief-introduction-to-satellite-image-segmentation-with-neural-networks-33ea732d5bce
Regards,
Shafagat
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Dariusz Prokopowicz
Dariusz Prokopowicz
  • asked a question related to Satellite
Can Artificial Intelligence and Big Data Analytics help in satellite-based analysis of the rate of biodiversity loss of natural ecosystems?
Question
5 answers
  • 26 May 2023
In your opinion, can the new technologies of Industry 4.0, including, above all, artificial intelligence, machine learning, deep learning applied in combination with large sets of data, information and knowledge collected and processed on Big Data Analytics platforms, help in the satellite analysis of the rate of biodiversity loss of the planet's different natural ecosystems?
As part of the technological advances that have been taking place in recent years, which are also rapidly advancing as part of the development of ICT information technologies and Industry 4.0, more and more sophisticated analytical instruments and research techniques are being developed to carry out increasingly complex, multifaceted and Big Data-based analyses of the various processes taking place in nature and to obtain increasingly precise results from the research conducted. With the combination of ICT information technology and Industry 4.0 with satellite analysis technology, the analyses of changes in the biodiversity of the planet's various natural ecosystems carried out using satellites placed in planetary orbit are also being improved. Taking into account the negative human impact on the biodiversity of the planet's natural ecosystems that has been taking place since the beginning of the development of the first technological and industrial revolution, and especially in the Anthropocene epoch from the mid-20th century onwards, there is a growing need to counteract these negative processes, a need to increase the scale and outlays allocated to the improvement of nature conservation systems and instruments, including the protection of the biodiversity of the planet's natural ecosystems.
Improving nature conservation and biodiversity protection systems also requires cyclic surveys of the state of biodiversity of individual terrestrial and marine natural ecosystems of the planet and analyses of progressive environmental degradation and the rate of biodiversity loss. In the situation of obtaining more precise results of research concerning changes in the state of the natural environment and the rate of loss of biodiversity of particular terrestrial and marine natural ecosystems of the planet occurring in various climate zones, changes in the state of the climate and diagnosing key civilisational determinants generating those changes, it is possible to apply specific actions and systemic solutions within the framework of counteracting negative processes of degradation of the natural environment and loss of biodiversity within the framework of improving nature protection techniques more effectively and adapted to the specific nature of a given local biosphere, climate conditions, diagnosed processes of the aforementioned changes but also economic factors. In this connection, the technology of artificial intelligence, which has been developing particularly rapidly in recent years, can also prove helpful in the process of improving the planning, design, management and restoration of natural ecosystems, taking into account a high degree of sustainability, biodiversity and naturalness, i.e. the restoration of natural ecosystems that existed in a specific area centuries ago. In the process of the aforementioned restoration of sustainable, highly biodiverse terrestrial and marine natural ecosystems of the planet, many primary factors must also be taken into account, including geological and climatic factors as well as the modifications previously applied to the area by man concerning geology, land irrigation, drainage, microclimate, soil quality, environmental pollution, the presence of certain invasive species of flora, fauna, fungi and microorganisms. Therefore, the process of planning, design, management and restoration of biodiverse natural ecosystems should take into account many of the above-mentioned factors that are a mix of natural biotic, climatic, geological and abiotic factors and changes in these factors that have taken place over the last centuries or millennia, i.e. changes and side-effects of the development of human, unsustainable civilisation, the development of a robber economy based on intensive industrial development with ignoring the issue of negative externalities towards the surrounding natural environment.
Considering how this should be a complex, multifaceted process of planning, designing, arranging and restoring the planet's biodiverse, natural ecosystems, the application in this process of the new generations of Industry 4.0 technologies, including, above all, artificial intelligence based on large sets of data, information and knowledge concerning many different aspects of nature, ecology, climate, civilisation, etc., collected and processed on Big Data Analytics platforms, can be of great help. On the other hand, artificial intelligence technology combined with satellite analytics can also be of great help in improving research processes aimed at investigating changes in the state of the planet's biosphere, including analysis of the decline in biodiversity of individual ecosystems occurring in specific natural areas and precise diagnosis of the rate of the aforementioned negative changes resulting in environmental degradation and the key determinants causing specific changes.
I will write more about this in the book I am currently writing. In this monograph, I will include the results of my research on this issue. I invite you to join me in scientific cooperation on this issue.
Counting on your opinions, on getting to know your personal opinion, on an honest approach to discussions in scientific problems, and not on ready-made answers generated in ChatGPT, I deliberately used the phrase "in your opinion" in the question.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
In your opinion, can the new technologies of Industry 4.0, including especially artificial intelligence, machine learning, deep learning applied in combination with large datasets, information and knowledge collected and processed on Big Data Analytics platforms help in the satellite analysis of the rate of biodiversity loss of the planet's various natural ecosystems?
Can artificial intelligence and Big Data Analytics help in the satellite analysis of the rate of biodiversity loss of the planet's different natural ecosystems?
What do you think about this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Counting on your opinions, on getting to know your personal opinion, on an honest approach to discussing scientific issues and not ChatGPT-generated ready-made answers, I deliberately used the phrase "in your opinion" in the question.
The above text is entirely my own work written by me on the basis of my research.
I have not used other sources or automatic text generation systems such as ChatGPT in writing this text.
Copyright by Dariusz Prokopowicz
Thank you very much,
Warm regards,
Dariusz Prokopowicz
Relevant answer
  • 14 Sept 2023
Answer
In my opinion, thanks to the combination of the above-mentioned technologies (artificial intelligence, Big Data Analytics, satellite technologies, broadband data transfer, etc.), there are new opportunities to analyze changes in the state of nature, changes in biodiversity loss, climate change and the impact of these changes on the state of the planet's natural ecosystems.
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Warm regards,
Dariusz Prokopowicz
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Aadityan Sridharan
Aadityan Sridharan
  • asked a question related to Satellite
Difference in GPS coordinates between field and satellite data?
Question
5 answers
  • 2 Sept 2023
When I try to correlate the gps coordinates among points obtained from field and satellite for the same location there is a big difference among the two. I assume that this is partly due to the satellite image shift. Can anyone tell me how to correlate the two datasets that are actually same but have difference in coordinates?
Relevant answer
  • 13 Sept 2023
Answer
Publish your paper for free
_________________________
Dear Researchers and postgraduate students
MESOPOTAMIAN JOURNAL OF BIG DATA (MJBD) issued by Mesopotamian Academic Press, welcomes the original research articles, short papers, long papers, review papers for the publication in the next issue the journal doesn’t requires any publication fee or article processing charge and all papers are published for free
Journal info.
1 -Publication fee: free
2- Frequency: 1 issues per year
3- Subject: computer science, Big data, Parallel Processing, Parallel Computing and any related fields
4- ISSN: 2958-6453
5- Published by: Mesopotamian Academic Press.
6- Contact: email: ahmed.h.ali@mesopotamian.press
Managing Editor: Dr. Ahmed Ali
https://mesopotamian.press/journals/index.php/bigdata/index
The journal indexed in
1- Croosref
2- DOAJ
3- Google scholar
4- Research gate
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Latu Khanikar
Latu Khanikar
  • asked a question related to Satellite
How to prepare a LULC map of a country/region for a particular time period using ARC GIS ?
Question
4 answers
  • 7 Sept 2023
I want to prepare a LULC map of a region using ARC GIS software. I am a beginner in this topic. Could anyone help me please in this regard such as
1. any websites from where I can can get or download satellite imaginary freely for a country/region.
2. satellite imagines of a country for a 5-10 year interval
2. further steps in classification of images etc
I would be very grateful.
Relevant answer
  • 9 Sept 2023
Answer
There are so many options for satelltie imagery (Sentinel, Landsat, MODIS, Nighttime light and so on) which you can choose from. For the classification steps you mentioned, again there is a plethora of algorithms. What you are asking is to give you a tutorial (step-by-step instructions) on how to do a classification. I think you should find an algorithm you want to use, the data set, the GIS software you prefer, try something yourself and if you have any (specific) issues then edit your question with your focused problem you faced.
In general, for a classification problem you need training samples (to train your classifier). The more samples you have the better. It's a good approach to start with an automatic classification algorithm just to get a rough idea of the spatial distribution of your classes and then move on with a semi-automatic approach (were you have to create training samples for your classes).
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Javid Hojabri
Javid Hojabri
  • asked a question related to Satellite
The authoritative reference for the LST formula?
Question
3 answers
  • 2 Sept 2023
Could you please provide me with 2 or 3 Elsevier or Springer articles that utilize this formula:
LST = BT / (1 + w * (BT / p) * ln(e))?
Relevant answer
  • 3 Sept 2023
Answer
Check Google
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Krishna Kumar S
Krishna Kumar S
  • asked a question related to Satellite
Ground and Satellite based rainfall correlation?
Question
2 answers
  • 29 Aug 2023
I am working on rainfall data using ground-based IMD rainfall data and Persiann CDR rainfall data. When compared I can see a very large difference in the data. I want to know if there is any data conversion/ processing that needs to be done before correlation.
Relevant answer
  • 30 Aug 2023
Answer
Hi, you can also use NASA's dataset.
The website is:
NASA POWER | Prediction Of Worldwide Energy Resources
If you have any problem with downloading the dataset, let me know
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Leônidas Luiz Volcato Descovi Filho
Leônidas Luiz Volcato Descovi Filho
  • asked a question related to Satellite
How to set the date in an image of the QGIS in QuickMapServices plugin?
Question
2 answers
  • 29 Jun 2019
It may be the image of MapBox, Google, Bing Satellite or others but how do I set the date of the image?
Relevant answer
  • 27 Aug 2023
Answer
Yes it is possible by going into layers setting you can do it easily.
All the best.
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Yuka Sashihara
Yuka Sashihara
  • asked a question related to Satellite
Where are coordinates stored in sentinel 1 data?
Question
3 answers
  • 3 Aug 2023
Hi, I’m a beginner in satellite image analysis. I want to know the lat/lon coordinates of some bursts of a sentinel-1 image. I looked at the file names of the downloaded zip, but couldn’t find any promising files(attached: file structure). Can someone teach me how I can obtain them?
Context: My purpose is to generate a coherence image and project to QGIS. I used SNAP following up to p12 of this tutorial(https://step.esa.int/docs/tutorials/S1TBX%20TOPSAR%20Interferometry%20with%20Sentinel-1%20Tutorial_v2.pdf). but the coordinates were somehow lost from the first step(importing and choosing bursts so as to produce a split file). not sure why but it apparently happens with other satellites(https://earthenable.wordpress.com/2016/11/21/how-to-export-sar-images-with-geocoding-in-esa-snap/). I was able to produce the coherence without coordinates, so i’m thinking if I can get the coordinates from the sentinel file, I can just add it to the geotiff myself.
I also want to ask, is this idea wrong? are the sentinel coordinates different from the coherence image as it undergoes back geocoding?
Relevant answer
  • 21 Aug 2023
Answer
Maybe you should study the SENTINEL-1 PRODUCT DATA TYPES.
Candidate Reference:
https://sentinel.esa.int/documents/247904/1653442/Guide-to-Sentinel-1-Geocoding.pdf
Regards,
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Asfandiyar Khan
Asfandiyar Khan
  • asked a question related to Satellite
Can I use different spatial resolutions satellite datasets for a city or there is need of upscaling or downscaling?
Question
1 answer
  • 28 Jul 2023
I want to study the monthly spatiotemporal variability of air pollutants in a city having 1,772 km2 area. I want to use satellite-based datasets but my datasets' spatial resolution is different. The specifications are given below:
1) PM2.5: Two datasets are available, one has 0.01 x 0.01 spatial resolution & the other has 0.1 x 0.1 degrees - Monthly
2) NO2: 0.25 x 0.25 degrees - Daily
3) Ozone: 0.25 x 0.25 degrees - Daily
4) SO2: 0.25 x 0.25 degrees - Daily
5) CO2: 0.01 x 0.01 degrees - Daily
Can I use these datasets with different spatial resolutions for my purpose or I need to make them same by either applying upscaling or downscaling? If you think that it needs to be the same then what do you suggest "Upscaling or Downscaling" and which techniques and software are best?
Relevant answer
  • 30 Jul 2023
Answer
In general, using datasets with different spatial resolutions is not necessarily an issue if the pollutant distributions and variability are studied separately. However, if your study aims to analyze interactions between these pollutants, or if you plan to conduct an integrated air quality assessment, having a consistent spatial resolution is essential for a fair comparison and to ensure the reliability of your results.
Considering the differences in spatial resolution of your data:
  • PM2.5 datasets have higher resolution than NO2, Ozone, and SO2 datasets.
  • CO2 data has the highest resolution of all.
It's important to consider the spatial variability of the air pollutants you're studying. For instance, PM2.5 and CO2 might have high spatial variability, while the other pollutants might not vary as much over the same area. In such cases, downscaling might lead to an overestimation of the variability of pollutants with originally lower-resolution data.
Generally, upscaling (or spatial aggregation) is preferred to downscaling, because downscaling requires making assumptions about the spatial distribution of data within each coarser pixel, which could introduce errors. In contrast, upscaling involves aggregating finer-resolution data to a coarser scale, which retains more of the original information.
To do this, you could use the maximum, minimum, mean, or median of the finer-resolution pixels that fall within a coarser pixel. The choice depends on the nature of the data and the research questions. You would probably want to aggregate the PM2.5 and CO2 data to match the 0.25 x 0.25 degrees resolution of the other datasets.
There are various software and tools available for spatial resampling, including:
  • ArcGIS: A popular geographic information system software, has tools for resampling raster data.
  • Python with libraries like Rasterio or GDAL: Both have powerful tools for spatial data processing, including resampling.
  • R with the raster package: This package provides a number of functions for handling raster data, including resampling.
Resampling methods in these tools include nearest neighbor, bilinear interpolation, and cubic convolution for upscaling and majority, minimum, maximum, mean, and median for downscaling.
Remember to consider the nature of your data when choosing the method: for example, if your data is not continuous (like certain types of categorical data), some methods like bilinear interpolation would not be appropriate.
In conclusion, whether you should adjust your spatial and temporal resolution depends on the specific requirements of your study. The most important consideration is to ensure that your methods are appropriate for your data and research questions. I hope this helps you.
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Justice Allotey Pappoe
Justice Allotey Pappoe
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How can I convert the magnetic field data from satellite dataset into the mean-field aligned coordinate system?
Question
1 answer
  • 10 Jun 2023
I have a satellite dataset from GOES-10 and I want to convert the vector magnetic field data into the mean-field aligned coordinate system. Thanks in advance.
Relevant answer
  • 26 Jul 2023
Answer
To convert magnetic field data from a satellite dataset into the mean-field aligned coordinate system (MFAC), you'll need information about the mean magnetic field at the location and time of interest. The MFAC system is commonly used in magnetospheric and ionospheric research to express magnetic field measurements relative to the average magnetic field orientation in a given region. Here's a general outline of the steps to perform the conversion:
  1. Acquire Mean Magnetic Field Model: Obtain a suitable mean magnetic field model that represents the average magnetic field orientation for the region and time period of interest. Such models are usually based on ground-based magnetic field observations and may be provided by scientific organizations or research institutions.
  2. Extract Satellite Magnetic Field Data: Retrieve the satellite magnetic field data that you want to convert. This data typically consists of time-series measurements of the magnetic field components (e.g., Bx, By, Bz) recorded by the satellite at various locations and times.
  3. Time and Coordinate Transformation: To align the satellite data with the MFAC system, you need to transform the satellite measurements to the appropriate time and coordinate system used by the mean magnetic field model.
  4. Subtract Mean Magnetic Field: Subtract the mean magnetic field values obtained from the mean magnetic field model from the corresponding satellite magnetic field measurements. This step ensures that the resulting magnetic field data are referenced to the mean field orientation instead of the geomagnetic coordinate system.
  5. Optional: Rotate to Local Mean Field Direction: In some cases, you may want to further align the data with the local mean field direction at each satellite location. This step involves rotating the magnetic field measurements based on the local mean magnetic field orientation provided by the model.
  6. Analyze and Visualize: Once the conversion is complete, you can analyze and visualize the magnetic field data in the MFAC system. This system allows for a clearer understanding of the deviations from the average magnetic field orientation in the region of interest.
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Lal Mohammad
Lal Mohammad
  • asked a question related to Satellite
How to know satellite overpass time over any place of the globe???
Question
2 answers
  • 26 Jul 2023
Please, give me the link from where I can get the overpass time (local time) of any satellite in any place in the globe...
Relevant answer
  • 26 Jul 2023
Answer
Lal Mohammad
To find the overpass time of a satellite over any place on the globe, you can use various online tools and websites that provide satellite tracking and prediction services.
One of the most commonly used tools for this purpose is "Heavens Above." Here's how you can use it:
  1. Go to the Heavens Above website: https://heavens-above.com/
  2. Create a free account (optional, but recommended for customizing settings).
  3. Once logged in, enter your location by clicking on "Select from map" or by manually entering your latitude and longitude coordinates.
  4. After selecting your location, click on "Satellites" in the top menu.
  5. A list of visible satellites will appear. You can choose the satellite you are interested in tracking (e.g., the ISS, weather satellites, or other Earth observation satellites).
  6. Click on the satellite name to see its upcoming passes over your location.
  7. The website will provide you with a list of dates and times when the satellite will be visible from your location, along with its brightness and altitude information.
  8. To convert the UTC (Coordinated Universal Time) provided by Heavens Above to your local time, you'll need to account for the time zone difference.
Please note that the availability of satellite tracking data might vary based on the specific satellite you are interested in.
Also, some other websites and apps like N2YO, Celestrak, and Satflare can also be used for satellite tracking and overpass time predictions.
As an Academic and Researcher in Remote Sensing, GIS, and Artificial Intelligence tools, you might find these tools beneficial in your work and research.
They can help you plan observations and data collection with satellites that pass over specific locations of interest.
Please recommend my rely if you find it useful .Thanks
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Ansith Sivadasan
Ansith Sivadasan
  • asked a question related to Satellite
Which deep learning algorithm is best suited for land cover classification?
Question
14 answers
  • 16 Jun 2020
I need to know about the deep learning algorithms used in land cover classification and which one is best suited. Planning to use Sentinel-2 satellite images.
I also want to know about GAN in Landcover classification.
Relevant answer
  • 25 Jul 2023
Answer
The choice of the best deep learning algorithm for land cover classification depends on several factors, including the characteristics of the data, the complexity of the classification task, the available computational resources, and the desired level of accuracy. As of my last update in September 2021, some of the commonly used deep learning algorithms for land cover classification are:
  1. Convolutional Neural Networks (CNNs): CNNs are widely used for image-based tasks, including land cover classification. They are particularly effective at automatically learning spatial patterns and features from input images. CNNs have shown excellent performance in tasks like object recognition and image segmentation, making them well-suited for land cover classification where pixel-wise labeling is required.
  2. U-Net: U-Net is a variant of CNNs specifically designed for semantic segmentation tasks, where each pixel in the input image is assigned a class label. U-Net's architecture incorporates both downsampling and upsampling pathways, making it efficient at capturing spatial context and accurately delineating boundaries between different land cover classes.
  3. Recurrent Neural Networks (RNNs): RNNs are designed to process sequential data, and they can be useful for classifying time series data in land cover applications, such as analyzing vegetation changes over time. However, for most land cover classification tasks, CNN-based architectures tend to be more commonly used.
  4. Deep Belief Networks (DBNs): DBNs are generative models that have been used for land cover classification, especially in cases where unsupervised learning or feature learning is desired. However, they have been largely overshadowed by the success of CNNs in recent years.
  5. Transfer Learning with pre-trained models: Many deep learning models pre-trained on large-scale image datasets (e.g., ImageNet) can be fine-tuned for land cover classification tasks. Transfer learning allows leveraging the knowledge learned from these large datasets and applying it to land cover classification, even with limited labeled data.
  6. Attention-based models: Attention mechanisms have been introduced to deep learning architectures to focus on relevant parts of the input data. They can improve the performance of land cover classification by allowing the model to emphasize important spatial regions in the images.
Ultimately, the most suitable deep learning algorithm depends on the specific land cover classification task and the characteristics of the available data. It's essential to consider factors such as the size of the dataset, the spatial and spectral resolution of the imagery, and the presence of temporal data. Additionally, it's beneficial to experiment with different architectures, hyperparameters, and training strategies to determine the best-performing model for a given land cover classification project.
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Arkadiy Mastin
Arkadiy Mastin
  • asked a question related to Satellite
Jilin-1 MF02A04 Laser terminal parameters ?
Question
1 answer
  • 12 Jul 2023
Changguang Satellite Technology with Aerospace Information Research Institute of Chinese Academy of Sciences set up a satellite-to-ground laser communication link 10 Gbps for 100 sec.
https://www.chinadaily.com.cn/a/202306/29/WS649d82e7a310bf8a75d6c629.html
Any technilcal parameters of satellite laser terminal ? (Optical scheme, photo)
Relevant answer
  • 12 Jul 2023
Answer
Uydunun yeryüzüne zarar vermemesi için evrenin diğer yerlerinde ve dünyada oluşumuna neden olduğu olaylar doğal olmalıdır. Teknik parametreler oluşum sırasında oluşan küçük etkiler ses, yansıma, parlama vb. Büyük etkiler doğa olayları yaşanabilir ve doğada farklı oluşumlar meydana gelebilir. Ayrıca güneşe, aya ve diğer gezegenler, yıldızlar, meteor, uydular vb. Üzerinde veya etkisiyle farklı olaylar oluşabilir.
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Saeed Izanlou
Saeed Izanlou
  • asked a question related to Satellite
How can I get TERRA satellite position or precise orbit determination (POD) file?
Question
1 answer
  • 9 Jul 2023
I need geodetic or ECEF coordinates of TERRA satellite.
Relevant answer
  • 11 Jul 2023
Answer
You can find it here:
https://celestrak.org/NORAD/elements/gp.php?GROUP=resource&FORMAT=json-pretty
"OBJECT_NAME": "TERRA", "OBJECT_ID": "1999-068A", "EPOCH": "2023-07-11T11:11:32.156160", "MEAN_MOTION": 14.59286438, "ECCENTRICITY": 0.0001916, "INCLINATION": 98.0935, "RA_OF_ASC_NODE": 260.2513, "ARG_OF_PERICENTER": 40.6451, "MEAN_ANOMALY": 15.3853, "EPHEMERIS_TYPE": 0, "CLASSIFICATION_TYPE": "U", "NORAD_CAT_ID": 25994, "ELEMENT_SET_NO": 999, "REV_AT_EPOCH": 25332, "BSTAR": 9.7977e-5, "MEAN_MOTION_DOT": 4.18e-6, "MEAN_MOTION_DDOT": 0
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Taghi Mahdavi
Taghi Mahdavi
  • asked a question related to Satellite
Question about satellite precipitation data?
Question
1 answer
  • 29 Jun 2023
I have downloaded two types of half-hourly and three-hourly satellite precipitation data for the study area from Gportal. Now I have a question about those data, please help in this regard.
GPM_3IMERGHH half-hourly NetCDF file
3B-HHR.MS.MRG.3IMERG.20170322-S000000-E002959.0000.V06B.HDF5.SUB.nc4
Question 1: Does this file cover the amount of precipitation from 23:45 UTC of the previous day to 00:15 UTC of the current day or it represents the period from 23:30 UTC of the previous day to 00:00 UTC of the current day?
GPM_3IMERGHH half-hourly NetCDF file
3B-HHR.MS.MRG.3IMERG.20170321-S103000-E105959.0630.V06B.HDF5.SUB
Question 2: Does this file cover the amount of precipitation from 10:00 UTC of the current day to 10:30 UTC of the current day or it represents the period from 10:15 UTC of the current day to 10:45 UTC of the current day?
TRMM_3B42RT three-hourly NetCDF file
3B42.20170302.00.7.HDF.nc4
Question 3: Does this file cover the amount of precipitation from 22:30 UTC of the previous day to 01:30 UTC of the current day or it represents the period from 21:00 UTC of the previous day to 00:00 UTC of the current day?
GSMAP 1-hourly HDF file
GPMMRG_MAP_1703021800_H_L3S_MCH_04C.h5
Question 4: Does this file cover the amount of precipitation from 17:00 UTC of the current day to 18:00 UTC of the current day or it represents the period from 17:30 UTC of the current day to 18:30 UTC of the current day?
Kindest regards
Mahdavi
Relevant answer
  • 3 Jul 2023
Answer
Thanks to everyone, I got the necessary response from the support of the above products.
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Shahrul Nizam
Shahrul Nizam
  • asked a question related to Satellite
How to know that our correction (include radiometric, atmospheric correction) in Landsat 8 is successful?
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2 answers
  • 30 May 2023
How to identify our corrected image for Landsat 8 after all the corrections including atmospheric and radiometric is good to use before deriving the depth using the stumpf algorithm in the satellites derived bathymetry work?
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  • 27 Jun 2023
Answer
hi, Jude Paho Nteinmusi Another simple way to verify the
success of the atmospheric correction is to analyze the
spectral values ​​of a pixel where there is healthy vegetation
and verify that the values ​​have the expected pattern for
healthy vegetation. I attach a sheet about it
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Nourhan Hamdy
Nourhan Hamdy
  • asked a question related to Satellite
How to solve: Attempt to convert a value (<closed DatasetReader name= mode='r'>) with an unsupported type (<class 'rasterio.io.DatasetReader'>) ?
Question
1 answer
  • 13 Jun 2023
the error is as a result of augmenting a satellite image that is read by rasterio module
Relevant answer
  • 14 Jun 2023
Answer
Nourhan Hamdy
Hi,
o solve the error "Attempt to convert a value (<closed DatasetReader name= mode='r'>) with an unsupported type (<class 'rasterio.io.DatasetReader'>)", you can try the following steps:
  1. Make sure you have the latest version of the rasterio module installed. You can update it using the command: pip install --upgrade rasterio.
  2. Check if you are correctly opening the satellite image using rasterio. Verify that you are using the proper file path and the correct mode for reading the image. For example, you should use the mode 'r' for reading.
  3. Ensure that you are closing the rasterio dataset properly after you have finished reading it. The error message suggests that the dataset is already closed. Make sure you are not trying to perform any operations on a closed dataset.
  4. If you are performing any operations on the dataset using rasterio, ensure that you are using the appropriate methods and functions for the task. Double-check the documentation or examples related to the specific operation you are trying to perform.
  5. If you are using the rasterio dataset reader as an input to another function or process, verify that the function supports the input data type. It's possible that the function you are using doesn't accept a rasterio dataset reader as input. In that case, you may need to convert the dataset reader to a compatible format before passing it to the function.
  6. If none of the above steps resolve the issue, you can try to provide more specific information about the code you are executing, including any relevant code snippets. This would help in understanding the context and identifying the exact cause of the error.
Please recommend my reply if you find it useful . Thanks
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Ajay Kumar
Ajay Kumar
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What is satellite peak in XPS? Why it not appears in every materials?
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6 answers
  • 24 Aug 2022
There is a satellite peak in Cu2+ but it is absent in titanium. What factors are responsible for the appearance of satellite peaks? Please elaborate.
Relevant answer
  • 24 May 2023
Answer
The appearance of satellite peaks in XPS can be attributed to various physical processes and interactions occurring during the photoemission process. These processes include:
Shake-up and Shake-off Excitations: When a core-level electron is excited and ejected by an incident X-ray photon, energy is transferred to the remaining electrons in the atom. This energy transfer can lead to excitations of other electrons, causing them to be promoted to higher energy levels. The subsequent relaxation of these excited electrons can result in the emission of additional photoelectrons, leading to the observation of satellite peaks.
Auger Electron Decay: After the ejection of a core-level electron, the resulting core hole can be filled by an electron from a higher energy level within the atom. This filling process may be accompanied by the emission of an Auger electron, which carries away excess energy. The kinetic energy of the emitted Auger electron can overlap with the binding energy range of the main peak, resulting in the appearance of satellite peaks.
Plasmon Excitations: Plasmons are collective oscillations of electrons in a solid material. When the incident X-ray photon interacts with the material, it can excite plasmons within the surface region. The relaxation of these plasmons can lead to the emission of photoelectrons with higher binding energies, contributing to the observation of satellite peaks.
Final State Effects: The interaction between the emitted photoelectron and the surrounding atoms or lattice can influence its kinetic energy. Final state effects, such as screening and charge rearrangements, can cause a shift in the binding energy of the emitted electron, resulting in the appearance of satellite peaks.
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Li Hui
Li Hui
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What procedures can be used for post-processing Level 2 products of GRACE satellite gravity data?
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1 answer
  • 11 May 2023
After learning and understanding, we know that GRACE Level 2 RL06 data needs further post-processing before it can be used. Including the replacement of C20 items, C21, S21 items, different filtering methods, GIA correction and so on. Wondering if there is any program or code that can do this? And be able to manipulate the data freely.
Relevant answer
  • 11 May 2023
Answer
Some tips on how to post-process GRACE Level 2 RL06 data are:
- Download the GRACE Level 2 RL06 data products from the GRACE Tellus website or the PO.DAAC website. You can choose between different data centers (JPL, CSR, GFZ) and different solutions (GSM, GAC, GAD). The GSM solution contains the spherical harmonic coefficients of the gravity field variations¹.
- Subtract a long-term mean field from the data products. You can use the mean field provided by GFZ or calculate your own mean field as an unweighted average of the available GSM products in a certain period².
- Replace the coefficients C20, C30, C21 and S21 and their formal standard deviations by values estimated from a combination of GRACE/GRACE-FO and Satellite Laser Ranging (SLR). You can use the values provided by GFZ or other sources².
- Apply a filter to reduce the noise and enhance the signal in the data products. You can use different types of filters, such as Gaussian, DDK, VDK, or Swenson¹. The choice of filter depends on your research question and the spatial and temporal resolution that you need.
- Subtract a linear trend caused by Glacial Isostatic Adjustment (GIA) from the data products. You can use a numerical model for GIA correction, such as ICE-6G_D_VM5a provided by GFZ or other sources².
- Insert geocenter coefficients (C10, C11, S11) into the data products. You can use the geocenter coefficients estimated by GFZ or other sources².
- Remove the estimated aliased signal of the S2 tide (161 days period) from the data products. This step is optional and depends on your research question².
(1) Data Updates & Announcements | Data – GRACE Tellus. https://grace.jpl.nasa.gov/data/data-updates/.
(2) Post-processed GRACE/GRACE-FO Geopotential GSM Coefficients GFZ RL06 .... https://dataservices.gfz-potsdam.de/gravis/showshort.php?id=escidoc:4175889.
(3) UTCSR/JPL GRACE Level-2 RL06 datasets release | PO.DAAC. https://podaac.jpl.nasa.gov/announcements/2018-07-16_UTCSR/JPL_GRACE_Level-2_RL06_datasets_release.
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Naresh Palaiya
Naresh Palaiya
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Hi, Can someone please guide me on the best way to work with Sentinel-3 SLSTR data using Python or R?
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2 answers
  • 7 Apr 2020
Hi,
I have experience working with Landsat, Modis and Sentinel-2 data; Right now I need to use Sentinel-3 data also to fuse with Sentinel-2 data, however, I am finding converting the Sentinel-3 data which is in NCDF4 format to Geotiff format correctly very difficult. I have come across snappy API which can be used from python but found the documentation and examples a tad inadequate when it comes to Sentinel-3 data. Since the lat-long information is provided in a separate file, my main problem is how to overlay geo-coordinates and radiance values from S6 and write it in a tiff file with the correct projection and resolution. Any help would be highly appreciated.
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  • 27 Apr 2023
Answer
Did you Sotirios Soulantikas find an solution for this problem?
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Jihane Guenoun
Jihane Guenoun
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What are the limitations of actual crop evapotranspiration estimation using satellite remote-sensing techniques?
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3 answers
  • 17 Apr 2023
Hi,
I am trying to understand the limitations of the Simplified Surface Energy Balance (SSEB) approach and Landsat Collection 2 (C2) Provisional ETa Science Products to estimate actual evapotranspiration of different crops in various locations.
These would be used by an agribusiness to monitoring water consumption and water availability for crops (wheat, rice and corn) grown in 14 different countries
I am struggling to understand if and how these can be applied to different crop / locations couples as Landsat Collection 2 (C2) Provisional ETa Science Products are yet to be validated.
Thanks for your help,
Best regards.
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  • 18 Apr 2023
Answer
Jihane Guenoun
while satellite remote-sensing techniques can provide valuable insights into crop water use and water availability, there are several limitations to their accuracy and reliability. These limitations must be carefully considered when using satellite-derived ETa estimates for monitoring and managing crop water use in different locations and for different crops.
There are several limitations to estimating actual crop evapotranspiration (ETa) using satellite remote-sensing techniques such as the Simplified Surface Energy Balance (SSEB) approach and Landsat Collection 2 (C2) Provisional ETa Science Products.
Spatial resolution: The spatial resolution of satellite imagery may not be fine enough to capture small-scale variations in ETa, particularly in heterogeneous landscapes with multiple crop types, varying topography, and soil characteristics.
Atmospheric interference: Atmospheric conditions such as cloud cover, haze, and aerosols can interfere with satellite measurements of ETa, particularly in regions with high levels of atmospheric pollution.
Sensor limitations: The accuracy of ETa estimates can be affected by sensor limitations, such as saturation of sensor values, band-to-band misregistration, and sensor noise.
Surface characteristics: The accuracy of ETa estimates can also be affected by surface characteristics, such as the presence of vegetation canopies, soil moisture, and surface temperature variations.
Crop variability: Crop variability, including differences in planting dates, crop management practices, and genetic traits, can result in variations in crop growth and water use that are difficult to capture using satellite remote-sensing techniques.
Calibration and validation: Accurate calibration and validation of satellite-derived ETa estimates is critical to ensure the accuracy and reliability of the data. This requires ground-based measurements of ETa, which can be difficult and expensive to obtain, particularly in remote or inaccessible areas.
Cost and accessibility: The cost of acquiring, processing, and analyzing satellite imagery can be prohibitive, particularly for small-scale farmers or resource-limited agribusinesses. Additionally, satellite imagery may not be readily accessible in some regions, particularly in areas with limited internet connectivity or data infrastructure.
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Manish Jain
Manish Jain
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Web Coupling figure of satellite?
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2 answers
  • 29 Mar 2023
Can anyone please send me the web coupling figure of satellite.
Regards,
Manish Jain.
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  • 31 Mar 2023
Answer
Sir, web coupling means
The thin sheet joining the two cylindrical satellites
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Md Imam Mahdi
Md Imam Mahdi
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Any software or website to track satellite in LEO and direct data transmission ?
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2 answers
  • 20 Mar 2023
Recently, I'm working in Direct to Satellite project. How data transmit direct to satellite and the tracking system, all the overview done by any software or website?
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  • 25 Mar 2023
Answer
Aahed Alhamamy
Thank you very much sir... This information really help me a lot.
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Hugo Bendini