5 projects for "geospatial data" with 2 filters applied:

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  • 1
    GDAL.jl

    GDAL.jl

    Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library

    Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly.
    Downloads: 0 This Week
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  • 2
    GeoServer
    GeoServer is an open source software server written in Java that allows users to share and edit geospatial data. Designed for interoperability, it publishes data from any major spatial data source using open standards: WMS, WFS, WCS, WPS and REST
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    Downloads: 46,550 This Week
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  • 3
    GeoTools, the Java GIS toolkit

    GeoTools, the Java GIS toolkit

    Toolkit for working with and mapping geospatial data

    GeoTools is an open source (LGPL) Java code library which provides standards compliant methods for the manipulation of geospatial data. GeoTools is an Open Source Geospatial Foundation project. The GeoTools library data structures are based on Open Geospatial Consortium (OGC) specifications.
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    Downloads: 438 This Week
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  • 4
    3Depict

    3Depict

    atom probe software : visualisation and data analysis

    This software is designed to help users visualize and analyze 3D point clouds with an associated real value, in a fast and flexible fashion. The primary use is in Atom Probe Tomography, which is an atomic imaging technique. However the program may also be useful in other areas, such as geospatial data, lidar, etc.
    Downloads: 3 This Week
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  • 5
    GeoNotebook

    GeoNotebook

    A Jupyter notebook extension for geospatial visualization and analysis

    GeoNotebook is an open-source extension to the Jupyter Notebook ecosystem that equips users with powerful geospatial visualization and analysis capabilities directly within the notebook interface. It integrates with GeoJS and other geospatial services to enable rich, interactive map rendering, layer control, and GIS data manipulation alongside traditional code and markdown cells in a Jupyter environment. Users can execute Python geospatial analysis and immediately visualize results on slippy web maps, allowing them to explore, annotate, and interpret large spatial datasets without leaving the notebook. ...
    Downloads: 0 This Week
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