Another map has been were georeferenced in WGS84LL using Georeferencing Qgis Plugin:
No Datum change:
move the source WGS84LL source GeoTiff file to the WGS84UTM37 huge, uncompressed target file, so you need to reduce it with
Datum change:
In this case you can add right info to the header of the result with:
In this way we obtained:
./Raster/21037:
21037_Agro_Eco_Zones.tif
21037_Arusha_soil.tif
21037_EcoClimatic_Zones.tif
21037_HRImage.tif
21037_Topo.tif
The same structure is repeated for 32737 and 4326.
With
The same transformation procedures work with vector data:
http://www.gdal.org/gdalwarp.html
- "Agroecological zones of Tanzania", Ministry Of Agriculture, Food and Cooperative
No Datum change:
gdalwarp -t_srs EPSG:32737 4326_HRImage.tif 32737_HRImage.tif
move the source WGS84LL source GeoTiff file to the WGS84UTM37 huge, uncompressed target file, so you need to reduce it with
gdal_translate -co "COMPRESS=JPEG" -co "PHOTOMETRIC=YCBCR" -co "JPEG_QUALITY=100" 32737_HRImage.tif 32737_HRImage2.tifand add pyramid overviews (load very fast in Qgis) with
gdaladdo --config COMPRESS_OVERVIEW JPEG --config PHOTOMETRIC_OVERVIEW YCBCR --config INTERLEAVE_OVERVIEW PIXEL 32737_HRImage2.tif 2 4 8 16
Datum change:
gdalwarp -t_srs EPSG:32737 -s_srs "1285_TZ.prf" 21037_Topo.tif 32737_Topo.tifmove the source ARC60UTM37 source GeoTiff file to the WGS84UTM37 file, using the right transformation parameters written in:
1285_TZ.prfThe process works backward: from standard EPSG_code --> to custom_CRS
+proj=utm +zone=37 +south +a=6378249.145 +b=6356514.96582849 +units=m +towgs84=-175,-23,-303
In this case you can add right info to the header of the result with:
gdal_translate -a_srs "21037_WK.txt" source.tif 21037_target.tifwith 21037_WK.txt:
PROJCS[" Projection Name = Arc_1960_UTM_Zone_37S Units = meters GeoTIFF Units = meters",that can be extract with gdalinfo>info.txt on the original toposheets (see Defining the Area of Intervention)
GEOGCS["Arc 1960",
DATUM["Arc_1960",
SPHEROID["Clarke 1880 (RGS)",6378249.145,293.4649999999983,
AUTHORITY["EPSG","7012"]],
AUTHORITY["EPSG","6210"]],
PRIMEM["Greenwich",0],
UNIT["degree",0.0174532925199433],
AUTHORITY["EPSG","4210"]],
PROJECTION["Transverse_Mercator"],
PARAMETER["latitude_of_origin",0],
PARAMETER["central_meridian",39],
PARAMETER["scale_factor",0.9996],
PARAMETER["false_easting",500000],
PARAMETER["false_northing",10000000],
UNIT["metre",1,
AUTHORITY["EPSG","9001"]]]
In this way we obtained:
./Raster/21037:
21037_Agro_Eco_Zones.tif
21037_Arusha_soil.tif
21037_EcoClimatic_Zones.tif
21037_HRImage.tif
21037_Topo.tif
The same structure is repeated for 32737 and 4326.
With
gdaltindex index.shp *.tifwe obtained the coverage of all the rasters in every folder.
The same transformation procedures work with vector data:
ogr2ogr 4326_Index.shp 21037_Index.shp -t_srs EPSG:4326 -s_srs "1285.prf"or
ogr2ogr mosaic2.shp mosaic.shp -t_srs EPSG:4326 -s_srs "+init=EPSG:21037 +wgs84=-175,-23,-303"Links:
http://www.gdal.org/gdalwarp.html
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