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        "description": "Anyone is free to copy, modify, publish, use, compile, sell, or\ndistribute this software, either in source code form or as a compiled\nbinary, for any purpose, commercial or non-commercial, and by any\nmeans.\n\nIn jurisdictions that recognize copyright laws, the author or authors\nof this software dedicate any and all copyright interest in the\nsoftware to the public domain. We make this dedication for the benefit\nof the public at large and to the detriment of our heirs and\nsuccessors. We intend this dedication to be an overt act of\nrelinquishment in perpetuity of all present and future rights to this\nsoftware under copyright law.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR\nOTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,\nARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\nOTHER DEALINGS IN THE SOFTWARE.\n\nFor more information, please refer to <http://unlicense.org/>\nDescription: ## Background\n        \n        Landsat-8 Level 1 scenes come with a quality assessment band (BQA) that shows various forms of atmospheric and other interference present in the image.\n        \n        The accompanying BQA file is a GeoTIFF with bit-packed values corresponding to an internal USGS numbering scheme. You can learn about these values and the BQA band in general by reading the USGS overview located [here](https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1-level-1-quality-assessment-band?qt-science_support_page_related_con=0#qt-science_support_page_related_con). There is also a more in-depth PDF titled 'Landsat Quality Assessment (QA) Tools User's Guide'.\n        \n        ## Usage\n        \n        This CLI tool may be useful to you if you are working with Landsat-8 quality assessment data in Python 3.\n        \n        This tool is written to search the directory where it is run, and all sub-directories for Landsat-8 BQA bands. It then 'unpacks' the bit packed BQA raster and creates a new GeoTIFF for each USGS quality measure that the user specifies. Finally, the tool takes the new quality bands for each scene and creates a composite image stack for each quality control measure.\n        \n        For example, you can take a directory of Landsat-8 scenes, pull out all cloudy pixels, and create a composite image showing all cloudy pixels in the stack.\n        \n        This is helpful for time series analysis because you can identify atmospheric interference over time.\n        \n        Flags correspond to each quality assessment layer identified by USGS.\n        The following will produce individual BQA band files for every quality assessment type identified by USGS and then build composites from each quality assessment type.\n        \n        ```commandline\n        cd /filepath/to/top_dir_for_landsat_scenes\n        landsat_L1_qa_tool -c -f -t -r -cl -cc -cs -ci -s\n        ```\n        \n        Quality assessment types:\n        ```commandline\n        -c --clear-terrain\n        -f --fill\n        -t --terrain-occlusion\n        -r --radiometric-saturation\n        -cl --clouds\n        -cc --cloud-confidence\n        -cs --cloud-shadow\n        -ci --cirrus\n        -s --snow-ice\n        ```\n        \n        ## Other Tools\n        \n        Other great tools exist, and are more comprehensive.\n        \n        -USGS has several offerings [here](https://www.usgs.gov/land-resources/nli/landsat/landsat-quality-assessment-tools).\n        \n        -USGS EROS offers [landsat-qa-arcgis-toolbox](https://github.com/USGS-EROS/landsat-qa-arcgis-toolbox), [espa-science-validation](https://github.com/USGS-EROS/espa-science-validation), and [espa-l2qa-tools](https://github.com/USGS-EROS/espa-l2qa-tools).\n        \n        -Rasterio's Landsat-8 QA tools is [here](https://github.com/mapbox/rio-l8qa).\n        \n        \nPlatform: UNKNOWN\nClassifier: Programming Language :: Python :: 3\nClassifier: License :: Unlicense\nClassifier: Topic :: Landsat :: data conversion\nDescription-Content-Type: text/markdown\n",
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