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You could use proj4.js. Just install it using npm install proj4. From the documentation: var firstProjection = 'PROJCS["NAD83 / Massachusetts Mainland",GEOGCS["NAD83",DATUM["North_American_Datum_1983",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],AUTHORITY["EPSG","6269"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0....


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You can't preserve the input, unless you convert the raster to polygons - try spex::polygonize (see @mdsumner comment). This is an effective solution for what I was trying to achieve. ## load library library(spex) ## convert raster to polygon r1.p <- polygonize(r_toconvert) ## change projection to desired projection r1.pj <- st_transform(r1.p, crs=...


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I just found a simple library for that - @esri/arcgis-rest-geocoding. using reverseGeocode function, it works perfectly.


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The scale factor states for the accuracy of your data. 0.001 is a millimeter precision. It means that if your coordinate is 0.123456 it will be clamped to 0.123. Depending on your data source 0.01 or 0.001 are good. offset aims to do not get integer overflow. Let say you want to store 123456789.123. In a LAS file you will actually store an integer: ...


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If you want to run gdal_translate in a python script, you can use the subprocess module to call the gdal_translate utility on the command line. You should replace this line: gdal_translate -of GTiff -ot Int32 H:/test/ytest1.tif H:/test/output/int.tif with this: import subprocess subprocess.check_call([ "gdal_translate", "-of", "GTiff", "-ot", "Int32"...


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