A noGDAL tool for reading geotiff files
Warning This package is under development and some features are unstable. Proceed with caution.
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noGDAL is a philosophy for developing geospatial programs in Python without using GDAL.
Installing this package is as easy as:
pip install geotiffThere is also an Anaconda-based package available, published on conda-forge:
conda install -c conda-forge python-geotiffFor local development from sources, you can install geotiff with its development requirements using:
git clone git@github.com:KipCrossing/geotiff.git
cd geotiff
pip install -e .[dev]from geotiff import GeoTiff
tiff_file = "path/to/tiff/file"
geo_tiff = GeoTiff(tiff_file)This will detect the crs code. If it's 'user defined' and you know what it should be, you may supply a crs code:
geo_tiff = GeoTiff(tiff_file, crs_code=4326)By default, the coordinates will be in WGS 84, however they can be specified by using the as_crs param:
geo_tiff = GeoTiff(tiff_file, as_crs=7844)Or you can use the original crs by setting as_crs to None:
geo_tiff = GeoTiff(tiff_file, as_crs=None)If the geotiff file has multiple bands, you can specify which band to use:
geo_tiff = GeoTiff(tiff_file, band=1)The default band is 0
Get information (properties) about the geotiff:
# the original crs code
geo_tiff.crs_code
# the current crs code
geo_tiff.as_crs
# the shape of the tiff
geo_tiff.tif_shape
# the bounding box in the as_crs CRS
geo_tiff.tif_bBox
# the bounding box as WGS 84
geo_tiff.tif_bBox_wgs_84
# the bounding box in the as_crs converted coordinates
geo_tiff.tif_bBox_convertedGet coordinates of a point/pixel:
i=5
j=6
# in the as_crs coords
geo_tiff.get_coords(i, j)
# in WGS 84 coords
geo_tiff.get_wgs_84_coords(i, j)To read the data, use the .read() method. This will return a Zarr array as often geotiff files cannot fit into memory.
zarr_array = geo_tiff.read()If you are confident that the data will fit into memory, you can convert it to a numpy array:
import numpy as np
array = np.array(zarr_array)In many cases, you are only interested in a section of the tiff. For convenience, you can use the .read_box() method. This will return a numpy array.
Warning This will fail if the box you are using is too large and the data cannot fit into memory.
from geotiff import GeoTiff
# in WGS 84
area_box = [(138.632071411, -32.447310785), (138.644218874, -32.456979174)]
geo_tiff = GeoTiff(tiff_file)
array = geo_tiff.read_box(area_box)Note For the
area_box, use the same crs asas_crs.
In some cases, you may want some extra points/pixels around the outside of your area_box. This may be useful if you want to interpolate to points near the area_box boundary. To achieve this, use the outer_points param:
array = geo_tiff.read_box(area_box, outer_points=2)
This will get 2 extra perimeters of points around the outside of the the area_box.
There are also some helper methods to get the bounding box of the resulting cut array:
# col and row indexes of the cut area
int_box = geo_tiff.get_int_box(area_box)
# lon and lat coords of the cut points/pixels
wgs_84_box = geo_tiff.get_bBox_wgs_84(area_box)Again, you can also get bounding box for an extra n layers of points/pixels that directly surround the area_box:
# col and row indexes of the cut area
int_box = geo_tiff.get_int_box(area_box, outer_points = 2)
# lon and lat coords of the cut points/pixels
wgs_84_box = geo_tiff.get_bBox_wgs_84(area_box, outer_points = 2)You may want to get the coordinates of a value in your array:
i=int_box[0][0] + 5
j=int_box[0][1] + 6
geo_tiff.get_wgs_84_coords(i, j)You may want to simply get all the coordinates in the array:
array = geo_tiff.read_box(area_box, outer_points=2)
lon_array, lat_array = geo_tiff.get_coord_arrays(area_box, outer_points=2)This will return two arrays that are in the same shape as the array from the read_box() method. The output coords will be in the as_crs crs.
If your tiff file is small and can fit into memory, simply:
lon_array, lat_array = geo_tiff.get_coord_arrays()If you would like to contribute to this project, please fork this repo and make a PR with your patches.
You can join the conversation by saying "hi" in the project discussion board.
To help users and other contributes, be sure to:
Note The continuous integration has lint checking with mypy, so be sure to check it yourself before making a PR.
32767 from tiff file