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Back to geospatialpython/pyshp

Open-source alternatives to Pyshp

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.

  • cmla/s2pAvatar de cmla

    cmla/s2p

    259Voir sur GitHub↗

    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…

    Python
    Voir sur GitHub↗259
  • earthlab/earthpyAvatar de earthlab

    earthlab/earthpy

    536Voir sur GitHub↗

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

    Python
    Voir sur GitHub↗536
  • osgeo/gdalAvatar de OSGeo

    OSGeo/gdal

    5,942Voir sur GitHub↗

    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

    C++
    Voir sur GitHub↗5,942
  • googlemaps/android-maps-utilsAvatar de googlemaps

    googlemaps/android-maps-utils

    3,597Voir sur GitHub↗

    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

    Javaandroidgeojsongoogle-maps
    Voir sur GitHub↗3,597

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  • planetlabs/numpytiles-specAvatar de planetlabs

    planetlabs/numpytiles-spec

    24Voir sur GitHub↗

    NumpyTiles is an open standard for communicating map raster data.

    Voir sur GitHub↗24
  • rgeo/rgeo-shapefileAvatar de rgeo

    rgeo/rgeo-shapefile

    98Voir sur GitHub↗

    RGeo component for reading ESRI shapefiles

    Ruby
    Voir sur GitHub↗98
  • robintw/xarrayandrasterioR

    robintw/XArrayAndRasterio

    0Voir sur GitHub↗

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

    Voir sur GitHub↗0
  • sshuair/awesome-gisAvatar de sshuair

    sshuair/awesome-gis

    5,388Voir sur GitHub↗

    😎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.

    awesomegeogeospatial
    Voir sur GitHub↗5,388
  • sshuair/dl-satellite-dockerS

    sshuair/dl-satellite-docker

    0Voir sur GitHub↗

    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.

    Voir sur GitHub↗0
  • addresscloud/aws-lambda-docker-rasterioAvatar de addresscloud

    addresscloud/aws-lambda-docker-rasterio

    19Voir sur GitHub↗

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

    Python
    Voir sur GitHub↗19
  • up42/image-similarity-measuresAvatar de up42

    up42/image-similarity-measures

    643Voir sur GitHub↗

    :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.

    Python
    Voir sur GitHub↗643
  • airbusgeo/godalAvatar de airbusgeo

    airbusgeo/godal

    177Voir sur GitHub↗

    golang wrapper for github.com/OSGEO/gdal

    Go
    Voir sur GitHub↗177
  • azavea/loamAvatar de azavea

    azavea/loam

    227Voir sur GitHub↗

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

    JavaScript
    Voir sur GitHub↗227
  • corteva/rioxarrayAvatar de corteva

    corteva/rioxarray

    619Voir sur GitHub↗

    rioxarray README

    Python
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