14 open-source projects similar to geospatialpython/pyshp, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Pyshp alternative.
S2P is a Python library and command line tool that implements a stereo pipeline which produces elevation models from images taken by high resolution optical satellites such as Pléiades, WorldView, QuickBird, Spot or Ikonos. It generates 3D point clouds and digital surface models from stereo…
EarthPy makes it easier to plot and manipulate spatial data in Python.
GDAL is an MIT-licensed open source translator library that provides a unified abstract data model for reading and writing geospatial raster and vector data across hundreds of file formats. It serves as a foundational geospatial data translation library, enabling access to diverse geospatial data formats through a single, consistent interface. The library exposes its core functionality through command-line utilities that allow users to translate, convert, and process geospatial data between formats. A coordinate transformation engine handles conversions between spatial reference systems, whil
This project is a utility library for the Google Maps SDK for Android, providing a suite of specialized tools for rendering geospatial data, calculating spherical geometry, and visualizing map markers and heatmaps. It serves as a helper collection to handle complex geospatial tasks within Android applications. The library features a marker clustering tool to group nearby markers into single icons and a map data visualizer for generating heatmaps based on the intensity and distribution of geographic points. It also includes a polyline encoding tool for compressing coordinate sequences into com
NumpyTiles is an open standard for communicating map raster data.
Experimental code for loading/saving XArray DataArrays to Geographic Rasters using rasterio
😎Awesome GIS is a collection of geospatial related sources, including cartographic tools, geoanalysis tools, developer tools, data, conference & communities, news, massive open online course, some amazing map sites, and more.
Deep learning docker files and docker images for geospatial anaysis. It contains the most popular deep learning frameworks(PyTorch and Tensorflow) with CPU and GPU support (CUDA and cuDNN included). And some other commonly used packages in machine learning and geospatial anaysis.
AWS Lambda Container Image with Python Rasterio for querying Cloud Optimised GeoTiffs.
:chartwithupwards_trend: Implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.