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geotiff

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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What is noGDAL?

noGDAL is a philosophy for developing geospatial programs in Python without using GDAL.

Installation

Installing this package is as easy as:

pip install geotiff

There is also an Anaconda-based package available, published on conda-forge:

conda install -c conda-forge python-geotiff

For 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]

Usage

Making the GeoTiff object

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_converted

Get 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)

Read the data

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)

Read a section of a large tiff

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 as as_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.

Getting bounding box information

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)

Get coordinates of a point/pixel

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)

Get coordinates of an array

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()

Contributing

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:

Make docstrings and documentation blocks, if appropriate
Use Python typing wherever possible
Format your code with Black

Note The continuous integration has lint checking with mypy, so be sure to check it yourself before making a PR.

Project Road Map

Core Features

read tiff files (including BigTiff)
write tiff files (including BigTiff)
convert between epsg coordinate systems
read a user defined CRS 32767 from tiff file
cut a section (bounding box) of the tiff file
convert the data to numpy arrays