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The good folks at the Remote Sensing Applications Center (RSAC) noticed from the metadata that the Lidar data specs are insufficient to calculate many of these grid metrics. In particular: NPS is 1.0 – 1.5 pulses/sq m Side Lap (Minimum): 25% Field of View (full): 40 degrees These three parameters, especially when combined, will likely result in data ...


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Classifying urban areas from Landsat data is a common practice and usually yields accurate results. To improve your accuracy I would reassess your training data. As a rule-of-thumb: 1) the more samples the better, 2) samples should be distributed evenly throughout the scene. There are numerous studies on just this topic: Extraction of urban built-up ...


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Related to answer I gave to a similar question (determine min and max elevation ... within my current extent), I wonder if this would work: import arcpy # this sets extent to current display, you can instead set it to ROI polygon arcpy.env.extent = arcpy.mapping.MapDocument.activeView.Extent # for a multi-band raster, pay attention to the band index (last ...


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You could still use zonal statistics with the minimum option. It produces a raster would could be used for further processing Zonal Statistics


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Use LDOPE-1.7 (https://lpdaac.usgs.gov/tools/ldope_tools), using "create_mask". this function takes MOD35_L2 HDF and creates a cloud mask in hdf. use MRTSwath tool for projection/re-sampling/clipping and convert new hdf to GeoTiff.


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The first thing you will want to do is look at the Google Terms of Use and Licensing. Google is very particular on how their data and software can be used. I would look at this first as it may be a show-stopper. The second thing I would consider is that the imagery in Google isn`t raw imagery; they are chips or tiles of data saved in a web tiling format. ...


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One of the most common reason for the covariance matrix that is not invertible from samples is the presence of null variance for one band (all your pixel in one band have the same value). In this case, increasing the size of the sample increase the chances to have a non null variance. Note that the band 6 (thermal) is the most likely to be constant, ...


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.ers - header file .ecw - data file


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The use of infrared data (presumably gathered by a FLIR camera) can be used to detect petroleum releases, but the FLIR approach has several issues... Mainly, background noise. Two approaches are commonly used: A temperature differential between the surrounding soil and hydrocarbon being released can be see on the FLIR camera A illuminating source (laser, ...


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Problem: applying moving window in matrix/raster to calculate Kappa statistics between classified map and reference dataset Solution: using focal{raster package}. This will implement moving window in raster function "modal" fun=modal to keep the majority values of neighbour values movingFun() from the {Raster}is mostly for vectors R code for focal() ...


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Differential Absorption LiDAR (DIAL) can assess gases releasing by scanning the target with (at least) two wavelengths in the electromagnetic energy spectrum: one wave length that is absorbed by the gas of interest and one that is not. By the difference in the absorption of this two wavelengths it is possible to account for 2D and 3D gas concentration ...


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those are different things. Image classification is the process of creating a thematic image where each pixel is assigned a number representing a class (can include the class 'unclassified'). In an aerial image the classes can be soil, vegetation, water etc. image classification algorithms examples are k-means or ISO-DATA. Pattern recognition is the ...



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