- Peter Carl added an answer:How do I perform IMF analysis to find the harmonics using MATLAB or IDL?
What is IMF or EMD?
Where is it actually needed?
Where can I stop IMFs?
Empirical Mode Decomposition (EMD) is an algorithm (a set of rules) used to decompose a signal (given in form of a time series) into so-called "Intrinsic Mode Functions" (IMFs). As is the case with all ill-posed tasks, this intended deconstruction of a complex signal into a set of simpler components from which one hopes to gain insight into generating mechanisms, for example, requires additional assumptions. In the case of EMD, the components (IMFs) are assumed to fluctuate about their mean values more or less symmetrically. All non-symmetric contents of the time series remain in the residue of the process. Whether or not application of EMD makes sense, depends on both the character of the signal and the target of analysis. Don't "think" EMD in terms of the concepts of Fourier Analysis, and don't use it 'blind', i.e. without clarifying the signal type and the given task (a recommendation that holds for any method of data analysis). Stopping criteria should be described in the software you use.
- Stavros Kolios added an answer:Which is the best classification algorithm for quantifying urban LULC using Landsat images,and kindly specify the reason?
Remote Sensing, Urban, LULC
It is difficult and may wrong to say which the best algorithm for classification is. First of all it depends if you want to use supervised or unsupervised classifiers. Regarding unsupervised algorithms, the parameterization plays a crucial role and in unsupervised algorithms the choice of the class training samples is an important factor (among many others). Nevertheless recent relative bibliography highlights a good performance of Support Vector Machines and Artificial Neural Networks.
I propose a similar work of mine that may help you and get some ideas:
- Xingxing Han added an answer:Which is the most accurate index for recognizing the water-land border
I wanna analyze the landsat images and divide the land area and the water area (a lake)?
how can I do that?
what is the most accurate index?
Try this index: Floating Algae Index (FAI).
It was first developed for the MODIS images, and some studies showed that FAI was less sensitive to the environmental variables and more stable to establish a region-wide and potentially time-independent threshold. I am not sure if it can be used for the Landsat. Anyway you can try it.
Hu C. A novel ocean color index to detect floating algae in the global oceans[J]. Remote Sensing of Environment, 2009, 113(10): 2118-2129.
Feng L, Hu C, Chen X, et al. Assessment of inundation changes of Poyang Lake using MODIS observations between 2000 and 2010[J]. Remote Sensing of Environment, 2012, 121: 80-92.Following
- Anette Eltner added an answer:Is anyone familiar with non-destructive estimates of aboveground biomass using terrestrial laser scanning?
Terrestrial laser scanning (such as LIDAR) is an active remote sensing technique that allows the structure of vegetation to be 3D-mapped to the finest resolution.
Please provide links to research articles and other pertinent information.
Hi Mounir, links to the pdfs are attached.Following
- Muhammad BILAL added an answer:How do you remove clouds from MODIS L1B swath product?
Is there any effective approach to remove clouds from MODIS L1B Swath Product?
How do you use MODIS cloud products (MOD06 & MOD35) to remove clouds?
Dear Dr Reza,
Thank your for your suggestions. I'm working on MOD35 and will see whether it is suitable for application or not.
- Robin Campion added an answer:How to retrieve volcanic SO2 from ASTER TIR?
I want to analyze the amount of SO2 emitted from volcanic activity. I will use ASTER TIR because they provide multispectral TIR data. I read some journal that give method about that such as Campion et al 2010. But, I don't know how to do it.
Hi Kusnadi, Apa khabar?
It is true that a lot of the SO2 remote sensing is done using UV satellites, but IR satellites have their own advantages too. Actually they are very complementary, especially ASTER. The first thing to do is to asses if there is SO2 in your ASTER image. To do this you can apply a simple band ratio to your image (B10+B12)/(2*B11). The higher the SO2 the higher this ratio will be. Usually pixels having this ration >1 are likely to have SO2, but the exact threshold may depend on the characterisitcs of your atmosphere and ground emissivity.
Then the second thing to do is to perform forward modeling of the radiative transfer in the atmosphere. In my 2010 paper I've used a free line-by-line code called Atmosphit, but other researchers have used MODTRAN, or whatever other code that works for the thermal infrared. You will need to get familiar with how the code works, which input files are needed etc... This will probably be the toughest step. The key parameters to take into account in the forward simulation are humidity and temperature profiles in the atmophere and plume altitude. At the end of this step you will have high resolution radiance spectra that you will need to integrate over the spectral response function of ASTER.
Then the third step is to invert the model. In the case of ASTER, you can retrieve the ground temperature using bands 13 and 14, which are unaffected by SO2 (but are affected by ash, so be careful on this) and then used this retrieved ground temperature to retrieve the SO2.
Are you interested in a specific volcano?
- Arne Saatkamp added an answer:What are most accurate data on remote sensed (NDVI etc.) vegetation cover, net primary production (NPP) and living biomass in Mediterranean Europe?
I look for a remote sensed data set (based on NDVI or more) on standing biomass in Mediterranean Europe to better understand fine scale (< 500 x 500 m2) distribution patterns of plants.
Thank You Cristina, I understand better now Your proposal;
I don't need detailed time series,
one reference data-set would be sufficient at the moment,
I hoped to find an existing data set;
300m resolution sounds very appropriate for my questions, I will try the way you propose, if I get news I will give an udpdate here,
all the best, ArneFollowing
- H. T. Basavarajappa added an answer:How do you generate DEM from Cartosat-1 STEREO data?
Remote Sensing Experts kindly answer this question
You can use the software like ENVI ER DAS
using RPM CartosatFollowing
- Abdulwasey Mohammed added an answer:Can I enhance the classification accuracy of habitat mapping with Idrisi Kilimajaro and assess the results properly?
I am mapping the Peat areas where there is ambiguity in different habitats because of the highly similarity of vegetable classes.
As you have rightly said, vegetation spectral signatures are highly overlapping if you follow spectral techniques for features selection for your classification over the peatbog. I had managed to get highly accurate results from peatland using object based classifiers such as eCogniton. But my data was Eagle and LiDar combinations. I would suggest you to try object based classifiers, in a hierarchical segregation schemes and if you can manage to get LiDAR data for the AOI then you will have much higher accuracies. give your email ID I will send you some literature.Following
- Said M.A. Nawar added an answer:How can we estimate soil moisture content from Landsat 8?
Soil moisture information is one indicator of drought and is the basis of action provision of irrigation water for plants to live optimally.
Remote sensing technique is able to record accurately the conditions of soil moisture in a large area.
Soil moisture values can be calculate by the triangular approach vegetation index and surface temperature data obtained from thermal infrared imagery.
I have tested SAR data for estimating soil moisture content and was successfully, but there is a limitation in data availability. Whereas, Landsat 8 is widely available for free. I completely agree that calibration is very important for accurate estimation.
- Michael Wulder added an answer:Does Landsat imagery download geometrically corrected?I am making a time series of coral reef changes in Madagascar and all my images from Landsat 8 and 5 in ERDAS imagine are all projected into UTM 38S, I believe that I am meant to do some work using google earth, but how?
As mentioned above, Landsat data are intended to be ready for analysis. Some regions and/or cloud cover situations may result in some pixel-to-pixel mismatches. Here listed are the specs for L1T: Landsat standard data products are processed using the Level 1 Product Generation System (LPGS) with the following parameters applied:
GeoTIFF output format
Cubic Convolution (CC) resampling method
30-meter (TM, ETM+) and 60-meter (MSS) pixel size (reflective bands)
Universal Transverse Mercator (UTM) map projection (Polar Stereographic projection for scenes with a center latitude greater than or equal to -63.0 degrees)
World Geodetic System (WGS) 84 datum
MAP (North-up) image orientationFollowing
- Amir Aghassi asked a question:How do I solve of the "flaw" error from ASTER data?
If the PC transformation on an ASTER swir data be done, an error comes up called "flaw". You see the orbital path effect as a distinct band in some PC images when loaded as gray scale image. It affects spectral based image processing.Following
- Alessandro Lugari added an answer:How to rectify Band Issues using Quickbird Satellite data?
I have procured data from DigitalGlobe -Quickbird Satellite data for different periods hence some data having different band combination. How can one rectify this problem? or how can I switch default true color band ?
I have attached an example image to show the problem.
I am looking for your guidance. Thanks in advanceFollowing
- Mohammad Safeeq added an answer:How to do a Time Series analysis of NDVI from MODIS image ?
I want to do a time series analysis of NDVI using MODIS dataset. Now if I consider a time span of 12 years say, 2002-2014 with MOD13Q1 (250 m spatial resolution and 16 days temporal resolution), I will be having approximately 288 images.
How to handle these many images, and how to present them in results ?
A single image contains 11 subdatasets should I add them in GIS as RGB image or process them individually. While adding the whole of this as a RGB image I am getting pixel values as 2987, 2349,5756, 6345.... Do these values correspond to the number after decimal i.e, 0.2987, 0.2349, 0.5756, 0.6345...
You might want to check out this: http://www.clarklabs.org/products/Land-Change-Modeler-Overview.cfm
Neeti, N. and Eastman, J.R., (2011) "A Contextual Mann-Kendall approach for the assessment of trend significance in image time series", Transactions in GIS, 15, 5, 599-611.Following
- Erin E. G. Giese added an answer:Large-area maps/data sets of xeroriparian vegetation in the southwestern U.S.?
Desert riparian vegetation is challenging to quantify via remote sensing over large areas (i.e. single or multiple states) due to typically narrow widths (e.g. often narrower than a 30-m Landsat pixel) among other issues. After reviewing some large-area land cover/vegetation data (NLCD 2006/2011 and National GAP v2) it appears that xeroriparian vegetation (e.g. Prosopis velutina, Olneya tesota along intermittent washes) is even more challenging to discriminate from surrounding desert vegetation than meso- or hydroriparian vegetation (owing to spectral properties, I imagine). Does anyone know of any attempts to quantify this vegetation type over large areas?
[update: the National GAP land cover does have a category for this type (North American Warm Desert Wash), though it appears to have been classified differently in different regions/states (e.g. California vs. Arizona). I also found this California data set: http://databasin.org/datasets/5e06338b27b24ac3802bb3b03ad57613 which is generally consistent with GAP data in California.]
I, too, suggest using LANDFIRE. I have used it for my research in the past and have found its categories to be extremely specific and detailed. They have land cover data sets from 2001, 2008, 2010, and 2012.Following
- Petre Voicu added an answer:What is the fastest and easiest way to do in site measurement of soil infiltration?
I want to study land infiltration measurement using remote sensing methods, and I am searching for an in site measurement method that isn't too time consuming.
The fastest and easiest method you are looking for depends on the the area of your interest, on its soilscape and weather. For example, in an arid area, you may use aerial RS with a hyperspectral instrument on-board. I have attached a paper describing this experiement.Following
- Juan-Carlos Jimenez-Munoz added an answer:The Use of Landsat-8 to estimate LST?I am using Landsat-8 to estimate land surface temperature. But the problem is that the Landsat-8 has two thermal bands which are band 10 and 11. My question is what band I should use to estimate the LST. Can I take the average of both bands? And apply this method (http://landsat.usgs.gov/Landsat8_Using_Product.php). Or is there an algorithm that can be used for 2 bands?
with two TIR bands you can use a single-channel algorithm (only 1 TIR band, in this case is better to use band 1, because the atmospheric absorption and this wavelength is lower than band 2), or you can also use a split-window approach, based on the combination of bands 1 and 2. SW algorithms provide typically better results than single-channel algorithms in global conditions, especially with high values of atmospheric water vapor content. However, if the atmospheric absorption is moderate (let's say something about 1-2 g/cm2 in terms of water vapor), the single-channel approach also provides good results. You can use the publication suggested by Subir, where you can find the two algorithms for Landsat-8. As Dr. Gaughan suggested, you should also take care with the calibration of the Landsat-8 TIR bands.Following
- Fillipe Tamiozzo Pereira Torres added an answer:Can we map soil erosion/soil erodibility in an area based solely on remote sensing and GIS data?
I'm not able to get any literature that may include only remote sensing data derived parameters.
Yes we can produce a risk map to erosion based on data from GIS and Remote Sensing . With GIS can analyze the susceptibility to erosion according to the elements of the physical environment (soil type, relief, lithology, structural lineaments, use and land cover, slope, etc ...) assigning weights and notes to the information entered. To check the effectiveness of the methodology used, can spatialize the incidents recorded and consider what risk classes of the most recurrent areas.Following
- Hilario Flores-Gallardo added an answer:Does anyone know a dataset of Drought (maybe PDSI) for the whole Europe?
I would like to use monthly or daily time series of Palmer Drought Index or any other drought index for the modelling of vegetation phenology (spring onset). 2002-2011. I am interested in interpolated grids.
The drought is calculated in a severity index, for that exist a lot of programs or software that calculate the index if you have a data base of precipitation, temperature, evaporation or evapotranspiration of one area specifically. Some names are SPEI (Standardized Precipitation-Evapotranspiration Index), SPI (Standardized Precipitation Index) or the PDSI (Palmer Drought Severity Index). For the above, that's programs are other options to generate you own data base of drought but before you need validate the weather data base to calculate the index of your interest.Following
- Syazwani Siran added an answer:Does anyone have experience with the using of ArcMap in temperature differences of ocean and depth analysis?
Does anyone have experience with the using of ArcMap in temperature differences of ocean and depth analysis?
Thank you for the ideas. I will looking forwardFollowing
- Satya PRAKASH Maurya added an answer:How can I order Cartosat-1 STEREO data through NRSC while it is not showing on their online order services?
Remote Sensing data acquisition
The basic problem is they provide data after giving the information of Path no and row number. of the required sceneFollowing
- Akhil Babu added an answer:What is the best way to represent monthly changes in Sea Surface Temperature (SST) for a year over a certain area?
Remote sensing, Sea Surface Temperature, fish forecasting
You can use Open GrADS software. SST and all climatology data is available at http://apps.ecmwf.int/datasets/data/interim_full_daily/ .
- Said M.A. Nawar added an answer:What method is used to calculate the reflectance factors of the calibration panel?
In the publication the Rpλ withequation 7 from the remote sensing of land surfaces course BIE 6250. The acquisition of these individual reflectance factors is not explained. Could anyone explain me how this is done?
For surface reflectance you can the ATmospheric COrrection and haze Reduction (ATCOR 2) model, which is based on the MODerate resolution atmospheric TRANsmission (MODTRAN 5) code. For more detailed see the next ref.,
- Victor Hugo Gonzalez Jaramillo added an answer:What is the best method to take density measurements in a forest?I intend to take samples of wood in order to determine density and apply to biomass estimations. Some approaches suggest taking cores of wood, and that imply cutting the tree. In this case the alternative is to not do this as invasive/damage activity is used as an increment borer. Can anyone can help me with some advice?
Thanks so much for your answer. Actually I try an experiment with samples of Pinus-Patulla, and obtain the density with the method of water displacement and the use of drying methods …. One problem was with the size of the samples and the time to obtain a constant weight. I intend to do the same but in this case only with cores taken with an incremental borerFollowing
- Bejo Duka added an answer:What are the weaknesses of the geomagnetic positioning systems (such as IndoorAtlas)?
Does such an indoor positioning system depend on the geometry of the interior?
For more information about IndoorAtlas: https://www.indooratlas.com/
It is a correct explanation of G. A. Paterson. I would like to add a comment regarding the effects of the magnetic noise coming from the time variation of the geomagnetic field (mainly diurnal variation) and the local magnetic anomalies coming from the local sources like as the steel constructions pf buildings. The effect of last one is more relevant and may be is not corrected by the "Indoor Atlas" application, while the noise of the diurnal variations can be corrected by using the nearest Geomagnetic Observatory registrations.Following
- Meenu Sojin Kumar added an answer:Can anyone help me find sources of information on Band 1 (Coastal/Aerosol band) of Landsat 8, preferably research articles?
Although I have been able to get most of the information related to Landsat 8 and its bands from landsat.usgs.gov website, still, I haven’t been able to explore the complete potential of its bands, especially the new Band 1 (Coastal/Aerosol Band : 433-453 nm) and its application in coastal and near shore processes research. I tried searching for previous research articles in using coastal band but I was not quite satisfied with the search results.
same here .I am also trying to find relation between band 1 and band 4 for aerosol studies. STILL NO LUCKFollowing
- Germar Bernhard added an answer:What would be the best technique for calibrating a UVER sensor (UVS-E-T) using a UV-B sensor (Solar Light 501 or similar)?
I need to calibrate a UVS-E-T (calibrated in 2012) and I´ve available only a SL 501 radiometer.
You can run the UVS-E-T side by side with Solar Light 501 using the Sun as the light source. I.e., you would calibrate the UVS-E-T vicariously against the SL501. The problem with this approach is that the spectral response of the two instruments is likely different. In this case, ratios of their measurement will depend on the solar zenith angle and total ozone column. The problem is discussed in this report in great detail:
- Ayad Mohammed Fadhil added an answer:Can someone suggest tutorials for learning eCognition?I am reading the user guide and it is not helping me too much. Any suggestion?
Yes, it is better to register at the eCognition community www.ecognition.com/community, then you can ask about what you need. It is a very useful forum, as well as you could find tens of videos in the YouTube. Good luck.Following
- Karim Musálem-Castillejos added an answer:Can forest cover influence ASTER DEM?
I am working in flatlands of the Southamerican Chaco and have found that Aster DEM seems to coincide higher elevations (1 to 2 m higher) with the presence of forests, and native grasslands with lower elevations. Could it be that ASTER is showing higher altitude in these areas because of the tree canopy or is it really reflecting higher topographical areas?
Thank you very much Dean and Cristina for your comments and texts!Following
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