New answers tagged geotiff
If you have a raster and a vector in different coordinate systems (i.e., one in lat/lon and the other not lat/lon), you will need to set up two GRASS Locations. One Location with the coordinate system of the raster and the other for the vector. Import the raster and vector into their respective Locations. Then run r.proj from the vector Location to reproject ...
I was not aware of the Rsenal package. It looks very nice and easy. Will have to take a look. What I did here was Robert Hijmans code from r-sig-geo 1 require(raster) # trmm template trmm <- raster(xmn=-180, xmx=+180, ymn=-50, ymx=50, ncol=1440, nrow=400) filename <- "3B43.980101.7.precipitation.accum" trmm <- readBin(filename, 'double', ...
I once wrote some functions to automate data download and processing of TRMM 3B42 binary data. downloadTRMM and rasterizeTRMM are included in our working group's Rsenal package. You can either install it via devtools devtools::install_github("environmentalinformatics-marburg/Rsenal") library(Rsenal) or, if installation fails (after all, it's a package in ...
I have the exact same problem for single tif files. If there are multiple tif files in the directory using the ImageMosaic plugin works without problems. To get rid of the error ERROR [geotools.rendering] - Argument "bgColor" should not be null. I just had to adjust the InputTransparentColor (FFFFFF) for the layers that are part of the grouplayer: ...
Reprojecting can be done by going to Raster then Projection and then Transform.Hope it helps.
Try Orux maps. It allows downloading tiles for offline viewing and you can also use your own georeferenced images. It also has some other nice functionalities that might be useful to you. And it's free!
As an alternative to Custom Maps mentioned below, I would suggest GeoViewer. It can do what you need. It can load MrSID and JPEG2000 formats from local storage and arrange them automatically. https://play.google.com/store/apps/details?id=com.lizardtech.activity
Try: red = np.array(red, dtype = float) nir = np.array(nir, dtype = float) Besides I think you mean: check = np.logical_or ( red > 0, nir > 0 )
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