Awesome GitHub RepositoriesGeospatial Data Tools

GDAL 是一个 MIT 许可的开源转换器库，它提供了一个统一的抽象数据模型，用于读取和写入数百种文件格式的地理空间栅格和矢量数据。它作为一个基础地理空间数据转换库，通过单一、一致的接口实现对多种地理空间数据格式的访问。 该库通过命令行实用程序公开其核心功能，允许用户在不同格式之间转换、处理地理空间数据。坐标转换引擎处理空间参考系统之间的转换，而格式驱动程序插件系统在运行时加载特定格式的读写逻辑。虚拟文件系统层提供跨本地文件、HTTP、云存储和压缩归档的统一 I/O 访问，栅格块缓存管理内存中的切片缓存以减少 I/O 操作。 GDAL 支持读取和写入栅格和矢量地理空间数据，其矢量特征迭代器可以单独流式传输特征，而无需将整个数据集加载到内存中。该项目通过其广泛的格式支持，实现了不同地理空间软件生态系统之间的数据交换，从而促进了地理空间互操作性。

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

The Python Shapefile Library (PyShp) reads and writes ESRI Shapefiles in pure Python.

rioxarray README

EarthPy makes it easier to plot and manipulate spatial data in Python.

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…

A wrapper for running GDAL in the browser using gdal-js

golang wrapper for github.com/OSGEO/gdal

AWS Lambda Container Image with Python Rasterio for querying Cloud Optimised GeoTiffs.

NumpyTiles is an open standard for communicating map raster data.

Experimental code for loading/saving XArray DataArrays to Geographic Rasters using rasterio

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.