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It's normal that azimuth and range resolution of SAR sensors differ, because they depend on different variables: The azimuth resolution (AR) of a SAR system is: AR=Length_of_antenna/2 The slant range resolution (SRR) of a SAR system is: SRR=(Speed_of_light*pulse_length)/2 The ground range resolution (GRR) of a SAR system is: ...


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There are many multi-look algorithms. At the most basic, the process reduces noise (or "speckle") in SAR images by averaging adjacent pixels. Often SAR processors allow the user to define some N x N window over which to average. However, other algorithms include using median values rather than mean values. For a comparison of other algorithms, see ...


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You can use data from the Suomi National Polar-orbiting Partnership, but it is quite recent (since 2012). e.g ftp://ftp-npp.class.ngdc.noaa.gov/20150611/VIIRS-SDR/VIIRS-Day-Night-Band-SDR/ For longer time series, you can use NOAA DMSP datasets (1992-2013)


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the original (GAO 1996) NDWI is based reflectance for the wavelength of 0.86 (NIR) and 1.24 µm (SWIR). This corresponds to bands 2 and 5 if you use MODIS. The equation for MODIS is thus (b2-b5)/(b2+b5). There are derived equation with other SWIR bands (e.g. for Landsat OLI the SWIR is around 1.6 µm), as well as NDWI2 (Mc Feeters 1996) which uses green ...


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One short comments regarding your other questions: Why is azimuth resolution worse than range resolution in Sentinel1 (SAR) You are absolutely right that sentinel TOPS have a worse azimuth resolution comparing with other data. This exactly the unique characteristic of TOPS. The working mode of TOPS (also including ScanSAR) is designed to sacrifice azimuth ...


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The "landsat-util" Python package used to support querying Landsat images based on a boundary defined by a shapefile until version 0.5.0, where it was removed to get rid of some dependencies. You could try using a version before that, e.g. v0.2.0. It's only a year old, so there is a chance it might still work. The good news is that the package's devs are ...



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