Questions related to Landsat
Hi Remote sensing Experts,
I was looking for codes to generate time series NPP and GPP from Landsat images using Google Earth Engine. I am aware of the MODIS product. But I don't know about Landsat. Any suggestions would be highly appreciated.
Here I described an issue with the scaling factor for Landsat 8 Level 2 products. I've used the scaling factor from here but when I compute the NDVI the result has many pixels out of the validity range.
Hi. I have three questions about Landsat 8 and LST.
I want to use Landsat 8 TIRS data to calculate Land Surface Temperature (LST) of the arctic regions.
So far, I have pre-processed BT and TOA from Level 1 DN, converted to LSE, and added NDVI to obtain the LST value.
However, I have some anxiety that this method is inaccurate than using Level 2.
Nevertheless, the reason why I could not use Level 2 ST (Band 10) product is because of the data gap due to missing of ASTER GED data (figure).
As you can see from the link below, the high latitude regions such as Greenland and Iceland have data gap issue in ST products.
I wonder if there are some methods or alternative to overcome the data gap.
I know that Sobrino 2004's method is frequently cited in LST calculations, and I know that there was a stray light problem with Landsat 8 TIRS.
However, recently I got to know that there are so many algorithms for converting TIRS images to LST (e.g., Split-Window or Single Channel)
Also, I found out that the stray light issue has already been calibrated in 2019.
Now, I wonder which algorithm is most appropriate for converting Landsat 8 TIRS images to LST.
Is there no need to preprocess Level 2 SR products for NDVI or other band combinations?
I am looking for night images of Las Vegas in summer (june to august), taken by Landsat 8. The goal is a LST analysis.
However, there does not seem to be a single image available for the ascending direction path 137 / row 209 in Earthexplorer. It shows always that there was no image found.
Am I making a mistake here in the search?
A similar question from 2017 (https://www.researchgate.net/post/How_can_I_download_nighttime_landsat_8_images) mentioned to contact customer support for night time images. Is this still up to date and how can I reach them?
There are several ways to contact them, but I do not know who exactly to contact regarding this matter.
Thank you in advance!
Hi everyone, i am facing problem during calculating land surface temperature by landsat 8 image. In my aoi the LST comes high 72 and low 55. In actual temperature never gone high above 50 in my aoi. Anyone can tell me whats problem. In 2000 2005 2010 and 2015 temperature results are accurate. Only problem in 2021 Lst.
Dears members, I am working on shoreline delineation using landsat 8 OLI,
Could you please provide me a link to download the tasseled cap with landsat for arcgis .tbx extension for arcgis 10.5.
Secondly how to extract the shoreline boundary from landsat 8 images using arcgis 10.5
Thanks in advance
please I need scientific reference for my answer.
I'm using Landsat 8 LT1 for fusion of MS and PAN bands of satellite images .
I am following Sadeghi et al., 2015 paper and try to use OPTRAM model for estimating soil moisture and have to use STR (SWIR transformed reflectance). I have no idea on how to calculate STR using SWIR band from Landsat 8. What is the software used for this process? Can you please help me step wise process to estimate soil moisture using OPTRAM model? It will be great help.
Greetings scholars, I am sharing a web based application that might be handy to dedicated researchers. Using this application users can download:- · Time series data and metadata of the satellite imagery selected and algorithm specified (Users can specify the length of the period, location, scale factor, clouds cover) · Time slider to visualize the changes · Time series charts Currently this application supports four algorithms: NDVI, 2BDA, 3BDA, Turbidity Index based on 3 satellite imagery (Landsat, MODIS and Sentinel). This application has been super useful to my current research (time efficient) and I strongly believe it would be supportive to the researchers willing to conduct similar research. I will try my best to include other algorithms based on users’ recommendation and suggestion. I have attached a quick video demonstrating method to use this application. Suggestion will be highly appreciated. Thank you. Happy researching! website link: mapcoordinates.info
video link: https://lnkd.in/e-HkkYnr
I am working on Forest Canopy Density. There is a parameter called "Scaled Shadow Index(SSI)" while computing Forest canopy density. In most of the papers I found that, SSI has been calculated by "Linearly Transforming" Shadow Index. I have computed the Shadow Index. But i am not getting the idea to compute Scaled Shadow Index. Kindly help me out. Moreover, If I am using Landsat 5 and 8 Surface Reflectance Image for FCD Mapping and as the Reflectance value ranges from 0 to 1, is it still mandatory to normalize these Surface Reflectance data before calculating Vegetation Indices?
I want to compare percent vegetation cover on a reclaimed site vs. percent vegetation cover in a reference area (i.e., an adjacent, not disturbed area). Can I do this with Sentinel or Landsat imagery? If so, would it be best to just create a ratio between something like NDVI in the reclaimed area vs. that in the reference?
I am trying to get seasonal changed land use and land classification for 1 km area study area. Most of the years in the wintertime period (November to January) have no image by Landsat 5 and Landsat 8. It will be nice if anyone can give me any hints
How often the LIDAR satellites can revisit the same area: for example every day or 3 months? for example the landsat repeat the cycle every 16 days.
For a multi-temporal study (my master thesis) that uses satellite images to obtain indices, for example, is it right or wrong to use level 2 images? (to save time and avoid mistakes) Would it be better if I process the level 1 images? (Landsat)
Dear colleagues I'm trying to calculate the land surface temperature for the Bakun Catchment, Sarawak, Malaysia region using different landsat satellite images of different years with the help of Google Earth Engine Code Editor. I'm not sure why I'm getting incomplete results for just this region and even the pixel values are too high in some of the years (please check the attached screenshots). Yes, for the NDVI and NDWI the results are covering the whole region.
I tried the same code for other regions of Pakistan and the results are very well.
So, my question is can anyone help me to get to know that this region the Bakun Catchment, Sarawak, Malaysia comes under special consideration or are there any other satellite data issues or maybe something wrong with the code? Also, does this region's LST goes down to -3 to -10?
For our new project, we are considering the use of Thermal Infrared satellite imagery. While the temporal resoltion is not important for us, we are looking for the highest spatial resolution in terms of Thermal infrared sensor. Aprat the available satellite data of MOODIS, Landsat and Sentinel is there any commercial satellite that provide very high saptial resolution of Thermal Infrared images?
Any information would be grateful in this regard.
I need specifically The method step by step to determine the:
I have an image Landsat MSS dated in 1975 with 4 bands
Any tutorial, guideline,
Thank you for your help in advance
I want to detect what cooling effect (intensity and distance) a group of small green areas can have, for example in one part of the town. And also for the the whole town, preferably from satellite images.
I am planing to make a comparison of forest cover between 1984 and 2021. I will use Landsat 5 and Landsat 8 images.
Could some recommend any pre process corrections or calibrations for both satellites ?
If I do radiometric calibration and dark objects subtraction for Landsat 8, Should I do the same for Landsat 5?
Or do landsat 5 accept radiometric calibration and dark objects subtraction? Or just a Quick Atmospheric correction can fulfill it ?
- What is the difference between Landsat Collection 1, Collection 2 Level 1and Collection 2 Level 2?
- What are the specifications included in each type?
- Do these types include atmospheric correction?
- What is the most appropriate collection for Land Use landcover and ecological related analysis?
I have a shapefile which is the ground survey data of the forest type.
The shapefile data contained multiple kinds of land cover data, including the artificial conifer, artificial broadleaf, artificial bamboo, natural conifer, natural broadleaf, and natural bamboo.
I am trying to use the Landsat image with the Random Forest Classification and the ground survey shapefile data to classify the forest type.
The training sample of each forest type is 30. The area of each training sample larger is than 4500 m2
The variable I select to split is five, and the training tree is 1000.
The variables I use include band 1~5 & 7, NDVI, CTVI, EVI, RVI, TTVI, TVI, SoilSalinity_ndsi, SoilSalinity_s1~s6, SoilSalinity_si, SoilSalinity_si1~si3, Water_Index_lswi, Water_Index_mndwi, Water_Index_nddi, Water_Index_ndwi.
The software I used is TerrSet 2020(idrisi).
I have tried several times, but the result is not good.
The Kappa value only has 0.47 for conifer, 0.38 for broadleaf, and 0.37 for bamboo.
The OOB Accuracy is 0.49.
Is there any method to use Landsat image to classify the conifer and broadleaf?
Or are there any other soft wares recommended?
Thanks for helping
I have been doing image classification of landsat 4-5 of year 1997 in ARC MAP, but it is difficult to proper classify the image. As i am using band 4, 3, 2 band combination, and settlements are mixing with bareland etc.. And there is a difference in bareland color, as some locations it is white, at some it is brown, and at some it is cyan color.
Is there any proper band combination to classify the landsat4-5 of year 1997.
I am currently doing research that finds the applicability of Landsat 8 satellite images for Soil Salinity Mapping.
01) In order to do that I generated a few soil salinity indexes based on a few methods such as NDSI, VSSI, etc.
02) As the second step, I generated the actual soil salinity map by collecting samples and interpolating that sample points.
Now I have a problem about what is the best way to find the correlation between 2 raster images?
Can I use Fishnet in ArcGis and generate points for each pixel and then use Microsoft Exel or Python to generate the correlation or are there any other methods to find that correlation?
Please be kind enough to enlighten me if You know any methods, thank you.
Hi everybody! as I've asked in the question I'd need to know how to extract the landsat 8 image within the polygon I created. I've already tried with .clip() but it does not work. Here I leave the link to my code. Looking forwards for your answers. Many thanks.
I am getting this error again & again.
Also I want to know what exactly is difference among bands, layers & channels of a geotiff image..? Kindly provide the reference documents which will give details about the bit frame of geotiff image format.
I am working on calculating NDVi and EVI indices from different years (50 year time period) and comparing them. I have a few questions regarding the datasets that I have found on Google Earth Engine (GEE).
- In the Landsat 8 Surface Reflectance dataset that is given on Google Earth Engine, do I have to do any additional preprocessing as it is already atmospherically corrected or do i have to just scale it using the scaling factor?
- What is the difference between the Landsat Surface Reflectance datasets and Landsat TOA Reflectance datasets?
After downloading the SLSTR Level 2 scene, I noticed the range of values is 0 to 255 i.e., 8bit. I need to convert this DN value into temperature reading in Kelvin units, of the respective pixels. Like Landsat has a coversion factor in the form of (a*x + b). Couldn't find relevant information in the website (https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-3-slstr/level-2/products).
Want to know if anyone has information on the conversion factors for senitnel 3 LST DN values to temperature in Kelvin.
Hello everyone. I need to calculate the upwelling and downwelling radiances and atmospheric transitivity for Landsat images prior to 2000 for my research therefore I cannot use the NASA calculator (https://atmcorr.gsfc.nasa.gov/). Does anyone know a way how to determine these parameters for images between 1984 and 2000? I do not have MODTRAN software.
I wonder if anyone know how to calculate the fractional vegetation cover (FVC) from Landsat imagery? As far as I have read about that NDVI, NDVIs, and NDVIv are three required input for calculation FVC as follow equation:
FVC = ( NDVI − NDVIs )/( NDVIv − NDVIs ) (1)
- NDVI is given by: NDVI = (nir − red)/(nir − red); nir and red are corrected reflectance obtained from the sensor bands located in the near infrared (NIR) and the red spectral regions for each pixel within an image
- The NDVIs and NDVIv are values of the NDVI for bare soil (FVC = 0) and pure green vegetation (FVC = 1) within an image, respectively
However, the major problem when applying Eq.(1) is how to accurately estimate the NDVIs and NDVIv values on the Landsat imagery. Therefore, I need you support on how to retrieve the values for NDVIs and NDVIv and the way we can calculate them from Landsat or other RS images pls?
Thank you very much with kind regards
Hello everyone, I'm Arjun.
I am working on large scale LU/LC change in whole India. I want to use landsat imageries as it has data for almost 50 years. But in the selection procedure, when I am looking images for a particular time period I found in many scenes there are large cloud covers.
How can I search for cloud free data for whole India for a particular period (say January 1990)?
Secondly, what is the ignorable percentage of cloud cover which we can use for our analysis ?
Hey , I'm currently doing undergraduate research and checking the applicability of Remote Sensing images to obtain soil salinity over paddy areas? I derived few soil salinity indexes using few methods such as NDSI etc.
Now I wanted to know the general soil salinity index range (ex NDVI = -1~+1) to check my output is correct or not...
I used Landsat 8 Level 1 it gives - 0.01 ~ 1. 49
(after apply TOA + Sun angle correction)
when used Landsat 8 Level 2 it gives - 1126 ~ 427115
Want to mark High tide Line from Open source Satellite data series. Apart from Landsat is there any other data sources? If yes than what are the alternatives to mark or define HTL?
I want to do a long-term (1990-2018) study which Enhanced vegetation index (EVI) is needed. However, the temporal coverage of MODIS can't meet the demand of this study. Therefore, I want to use both Landsat 5 and Landsat 8 in one study. I don't know if it will influence the accuracy of the study or not be permmited.
I use ENVI 5.3. Recently in May 2021 I have downloaded several landsat images from landsat 5 to 8 for my research purpose. Unfortunately ENVI cannot open Geotiff and metadata file for these images.Showing error that this file format dooesnot support.
Does anyone face this problem? How can I solve this problem?
I already saw this question somewhere, but haven't seen any answers to it. So I am asking it again.
For some reasons that I don't know (and I would be glad if anyone could tell), though Landsat 8 surface reflectance data exist and can be accessed directly using google earth engine, Several authors (including myself) still do their own atmospheric correction and radiometric calibration.
Is there any reason for that? Is there a reason to doubt the quality of ready to use surface reflectance data provided by USGS, available as lansat 8 surface reflectance images?
I recently obtained excessive values of EVI (circa 2) when I used surface reflectance in the calculation (I am sure of the formula). I would like to mention that all other indices I computed are in range (SAVI and several normalized difference vegetation indices such us NDVI, GNDVI, LSWI, MNDWI,...). I don't know if someone also encountered such a problem with ENVI.
In any case, to conform to one of my previous research, I would like to continue using Dark Object Substraction instead of ready to use Landsat 8 SR.
Question: Does anyone know how to perform dark object substraction in google earth engine?
I needed to download two satellite maps of the year-2020 and year-2000 to study the land use changes. I visited usgs.gov site to download the LandSat map, where I found that LandSAT8 OLI/TIRS C2L2 is available for 2020 and LandSAT4-5 TM C2L2 is available for 2000.
Can I use these two different LandSat level for comparing land use changes?
I have used the natural color band, and here is the result.
LandSat_2000 is made by using LandSAT4-5 TM C2L2, while LandSat_2020 map is made by using LandSAT8 OLI/TIRS C2L2.
Are they Okay?
One more thing.
From 2000 (satellite) map, it is clear that the area has more vegetation, while from 2020 (satellite) map, it is clear that the area has rarely any vegetation.
When I performed NDVI analysis, I found that 2000 map has more water bodies than 2020 (though in satellite, we see that 2000 has more vegetation).
I don't understand what's wrong. I must have a gap. Can you please help?
I am applying supervised classification on landsat 5 images. But there is certian problem in obtaining the results. As you can see in the picture that there are settlements along the stream but if I see on google map it doesn't show the settlements along the river.
Hello Experts from PCI Geomatica,
I have successfully installed PCI Geomatica 2017 software for automatic cloud and haze removal from landsat TM and santinel 2A_Level 2A images. But when i start processing after sometime the window of FOCUS automatically disappeared. how can i solve this problem? Thanks in advanced.
I am performing a time-series analysis and using Sentinel-2 for the latest data and Landsat-5 for the older data. Now in the time-series graph, I see a significant rise in the output values for the last two years' data (sentinel imagery). The first step of my algorithm is to derive NDVI so does the difference between the two sensors still matter? If so then how to correct the process?
P.S- I am using top-tier products for all the imagery so is there a question of DN to TOA conversion?
After downloading the Landsat satellite image particular area how we can identify or detect tea throughout the agricultural land utilization. Are there any method?
for example for Landsat I upload MTL format for some of the calculations such as spectral indices. about worldview, I get error for the calculation.
I am new to DL and I'm trying to classify 1 Landsat8 image into 3 categories using VGG-19. I am using 8 bands (B2 to B7 ,B10 and Panchromatic). I performed the sampling procedure and my samples are named "1_id_b2" (category_id sample_Landsat band). I have my training and test samples into separate folders. The folder structure is similar to the image attached (folder_str). I've read that I need to create training and test labels. I don't understand why to create the labels, because I already labeled my samples.
Any persons who have knowledge about this may answer to help my some research student of Yemen.
Steps that I need:
1. EVI L8 time series reduced by montly median values;
2. Fit a curve using Savitsky-Golay, Whitakker or Harmonic model;
3 - Extract phenometrics, for example, SOS (start of the growing season) and EOS (end of the growing season).
Do someone knows how to perform these steps using Google Earh Engine?
I'm preparing land use maps for various years using Landsat 8 and Landsat 7 imagery. For Landsat 7, I've decided to not fill the gaps for SLC as it might result in inaccuracies.
For the Land Change maps, I intend to use post classification approach. I'm going to do this in ArcGIS desktop.
How should I detail about the loss of area via SLC in my technical report? Can someone refer me to technical papers that haven't used gap filling for their analysis?
PS: I cannot use Landsat 5 data as it is not available for my AOT for some years.
I face a problem in LULC classification, like as an industrial area showing as a water body.
Please help me.
is there anyway to download big satellite imagery (like Landsat 8 or sentinel) by rectangle focused on just my study area of research not whole the scene!
i want to examine drought progress in last 20 years for example by NDVI but in smaller area of interest
so i need data like Landsat 8 or sentinel for more detailed investigations in smaller basins
MODIS like data are so big and universal
but i prefer smaller regions to be investigated by detail
is there any way or site that provide such huge data in such way
selective download of satellite data for regions of interest
I just created a "Quick Stats" histogram to view my Landsat 8 data after I divided each band by 10,000, and I see that the maximum reflectance values of all 7 bands are between 3-6. Do I need to correct this? My mean values are between 0 and 1, but I am not sure if they are correct either.
The layer stack image of the 7 bands came out cyan, which means that these values may be skewed by cloud reflectivity. How can I correct this to get the BOA values?
I have already calculated the original NDSI index, and I would like to use PCA analysis for more accurate results. I read in a study that I need the brightest and the darkest component for the index calculation (NDPCSI). I also read that this corresponds to the PCA component 1 and component 2. That is also mean Band 1 and Band 2? (if not, which bands should I use) Because I did the PCA analysis with Landsat 8 Bands (1-8), but I'm not sure what I supposed to use. I am a little bit confused about it.
Somebody could help me in this case, please?
I would be very glad if you tell me.
I am looking for satellite imagery of last 10 years so that i can find out change detection in such place. The possible solution to download the historical solution is by using google earth pro but due to the contrast problem in such imagery it become very difficult for me to classify it and another solution i have found was Declassified imagery in earth explorer but all those images were taken in range of 1970's and another landsat but due to the coarse resolution i find it is also unsuitable for this project, santinel-2 contains the datasets only after 2015. What may be the possible solution for this probelem ? Please tell me if you have any idea , i will apreciate your help
In metadata file Lmin and Lmax has been given. Also Saturation radiance and solar radiance has been given. I want to perform it in ENVI.
It is easy to perform this operation for satellites like landsat, sentinel as the method is predefined in software itself.
I want to extract SO2 and NO2 from Landsat or Sentinel images. Any help from the remote sensing community.
While Using a Landsat image of 30 mts resolution, a map of what scale will be produced?? So how do u derive the scale of a map to be produced from certain resolution of satellite image???
- I am wondering if you let me know the limitations of Landsat 8 to getting the bathymetry.
- LIDAR data is capable of giving us the water depth in relation to water surface. Can we get the water level in gauge station using LIDAR?
- Interms of expense and availability of data source should I prefer the LIDAR or the Landsat 8?
I am conducting an image classification of a Landsat 5 image and I generated 5 classes using training samples but each time I try to extract my area of interest, the output only shows 2 classes. How can I maintain the 5 classes I generated?
I have downloaded landsat 5 and landsat 8 atmospheric correct images, as provided by USGS nowadays.
Do I need to perform radiometric correction of these images?