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Showing results for tags 'Landsat'.
Found 9 results
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Hi all, I'd like to share a tool I created to automate the calculation of spectral indices for remotely sensed imagery. Currently, 22 spectral indices and the following sensors are supported: Landsat 1-5 MSS Landsat 4-5 TM Landsat 7 ETM+ Landsat 8 OLI Worldview-02 MODIS Terra and Aqua Just run the Python script (arcpy or GDAL) and use the GUI interface to select your sensor, indices to calculate, stacked image, and output directory. I haven't shared the tool yet and thus it has not been extensively tested. My personal tests have worked fine, but be sure to validate y
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I am creating annual water percentage image over a region. There is lof of missing data as far as water/land mask is concern as there are clouds or nodata values for the landsat 7 gaps. How can I show percentage of water over an year with such missing data values. I don't think that my denominator should be the same in calculating the percentage. Also, taking zero for missing data is also wrong. What is the industry standard when doing this. Help! -
hello, saya ingin bertanya, dimana kita bisa mendapatkan citra landsat yang belum terkoreksi geometris? terima kasih.
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I pan-sharpened one Landsat Image on ERDAS using the resolution merge resource, with brovey transform and nearest neighbor techniques. But I was told that in terms of land-use classification, it would be a mistake doing it, since pan-sharpening creates false pixels that would add erros. Is it true? Thank you.
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Hi, I have a question I appreciate if somebody could help me. I need to estimate daily catchment scale evapotransporation. My catchment consist of irrigation farms ( varied vegetation type), Natural land , Small lakes and bare soil (almost 30 % of the catchment area). The study area located in semi arid region. I have already got ET-ref from weather stations in the area and prepared spline interpolated Et-ref map . I have got landsat R S image as well. Friend of mine suggested using average NDVI for the whole catchment and then use (Et =ET0*Kc, kc = 1.37 * NDVI-0086) equation. I am not sure if
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Hi guys! I`m working on land cover change detection project of Kyiv province in Ukraine using Landsat data and ancillary information. I want to find change in Land Cover from 1990 to 2014 of Kyiv province using Decision Tree approach in ENVI. I have already done radiometric correction, atmospheric correction and apply cloud mask to whole Landsat`s scenes, and now I have question and request. Do I need to do mosaicking before classification or mosaicking classified image ? Does anybody have some decision rules for splitting pixels for appropriate land cover classes using Landsat
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I am new to this forum, so hello to everyone has anyone expereince with global Landsat datasets? I am aware of GLOVIS, EarthExplorer and in particular the "Global Land Survey" (GLS) products. What I am looking for is a way to bulk download a global (land surface) coverage of at least two time slots. One slot should be about 6,000 scenes, so a lot of work if done manually. Thanks and kind regards Lucas
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Hi folks, I need some analysis module to discriminate Built-up areas and Baren Land. And I've found it http://www.mdpi.com/2072-4292/4/10/2957/pdf from MDPI. But when I calculate EBBI index, the result index value is out-of-range and the index values for Built-up area and Baren Land aren't significantly different.. So, if any body have idea for it, please share to me. Thank's folks Regards
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Hello everybody! I am trying to make a relatively simple LULC classification of a region with only 5 categories - grassland, agricultural, built-up, forest and other. I have the data for summer seasons. I tried with several RGB combinations, PCA, band ratios from every possible tutorial, still I can't differentiate barren land (in this case "agricultural" category") and built-up. Is there any algorithm or some procedure which would select some of the possible good combinations? I am working with ArcGIS 9.3 and am very frustrated. Also, when I tried with several procedures, I did it paralle
