Search Results for "geospatial data"
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Showing 101 open source projects for "geospatial data"
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segment-geospatial
A Python package for segmenting geospatial data with the SAM
The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. ... -
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GeoAI
GeoAI: Artificial Intelligence for Geospatial Data
GeoAI is a comprehensive open-source Python package designed to integrate artificial intelligence techniques with geospatial data analysis, enabling users to perform advanced geographic modeling and visualization tasks with ease. It provides a unified framework that combines machine learning libraries such as PyTorch and Transformers with geospatial tools, allowing users to process satellite imagery, aerial photos, and vector datasets in a streamlined workflow. ... -
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GeoNode
GeoNode is an open source platform for geospatial data
GeoNode is a geospatial content management system, a platform for the management and publication of geospatial data. It brings together mature and stable open-source software projects under a consistent and easy-to-use interface allowing non-specialized users to share data and create interactive maps. Data management tools built into GeoNode allow for integrated creation of data, metadata, and map visualization. -
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GeoInterface.jl
A Julia Protocol for Geospatial Data
This Package describe a set of traits based on the Simple Features standard (SF) for geospatial vector data, including the SQL/MM extension with support for circular geometry. Using these traits, it should be easy to parse, serialize and use different geometries in the Julia ecosystem, without knowing the specifics of each individual package. In that regard it is similar to Tables.jl, but for geometries instead of tables. -
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QGIS
Cross platform (lin/win/mac) geographical information system (GIS)
Create, edit, visualize, analyze and publish geospatial information on Windows, Mac, Linux, BSD and mobile devices. For your desktop, server, in your web browser and as developer libraries. QGIS is a user-friendly open-source Geographic Information System (GIS) licensed under the GNU General Public License. QGIS is an official project of the Open Source Geospatial Foundation (OSGeo). -
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leafmap
A Python package for interactive mapping and geospatial analysis
...Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium and ipyleaflet (for creating interactive maps), WhiteboxTools and whiteboxgui (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface [GUI]). -
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GeoServer
GeoServer repository
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. Being a community-driven project, GeoServer is developed, tested, and supported by a diverse group of individuals and organizations from around the world. GeoServer is the reference implementation of the Open Geospatial Consortium (OGC) Web Feature Service (WFS) and Web Coverage Service (WCS) standards, as well as a high-performance certified compliant Web Map Service (WMS), compliant Catalog Service for the Web (CSW) and implementing Web Processing Service (WPS). ... -
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NYC Taxi Data
Import public NYC taxi and for-hire vehicle (Uber, Lyft)
...It also contains example analyses—spatial and temporal visualizations like maps, time-series plots, and hotspot detection—highlighting insights such as patterns of demand, peak times, and geospatial distributions. The repository is often used as a benchmark dataset and example for teaching, benchmarking, and demonstration purposes in the data science and urban analytics communities. -
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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. -
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geemap
A Python package for interactive geospaital analysis and visualization
A Python package for interactive geospatial analysis and visualization with Google Earth Engine. Geemap is a Python package for geospatial analysis and visualization with Google Earth Engine (GEE), which is a cloud computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. During the past few years, GEE has become very popular in the geospatial community and it has empowered numerous environmental applications at local, regional, and global scales. GEE... -
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ... -
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GeoStats.jl
An extensible framework for geospatial data science
GeoStats.jl is a Julia framework for geospatial data science and geostatistical modeling. It’s fully implemented in Julia and designed to provide an extensible, high-performance stack that handles spatial domains, interpolation, simulation, learning, and visualization. The package is modular: it breaks out geometry, spatial domains, transforms, variograms, covariance models, and modeling into subpackages (e.g., GeoStatsBase, GeoStatsModels, GeoStatsTransforms). -
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Koop
Transform, query, and download geospatial data on the web
Koop is a JavaScript toolkit for making requests to spatial APIs. It exposes a Node.js web server that facilitates on-the-fly transformations of geospatial data from one format to another and delivers it to clients by HTTP. Koop allows you to keep your data in its native format while making it accessible in any format required. Out-of-the-box, Koop can translate your data into the GeoServices specification supported by ArcGIS products. Its plugin architecture supports output in other formats including vector-tile, WMS, and plain old GeoJSON. ... -
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Digital Earth Australia notebooks
Repository for Digital Earth Australia Jupyter Notebooks
The knowledge hub brings together information about Digital Earth Australia’s products and services, allowing you to utilize our free and open-source satellite imagery archive. Browse our catalog of data products to find supporting information and ways to access the data. The Digital Earth Australia notebooks and tools repository (dea-notebooks) hosts Jupyter Notebooks, Python scripts and workflows for analyzing Digital Earth Australia (DEA) satellite data and derived products. This documentation is designed to provide a guide to getting started with DEA, and to showcase the wide range of geospatial analyses that can be achieved using DEA data and open-source software including Open Data Cube and xarray. -
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Cloudberry
One advanced and mature open-source MPP
Apache Cloudberry is a distributed real-time analytics engine designed for querying massive social media datasets. It integrates with Apache AsterixDB and supports efficient ad-hoc queries and aggregations across large volumes of data. Cloudberry is especially useful for dashboards, trend analysis, and time-series social data exploration. -
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L7
Large-scale WebGL-powered geospatial data visualization analysis
L7 is a WebGL-based open source large-scale geospatial data visual analysis development framework launched by Ant Financial's AntV data visualization team. The L in L7 stands for Location, and the 7 stands for the seven continents of the world, implying the ability to provide visual analysis for global location data. L7 focuses on the visual expression of data, and realizes clear and effective expression from data to information through the setting of visual variables such as color, size, texture, direction, and volume. ... -
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BuntDB
Database for Go with custom indexing and geospatial support
...It is built for scenarios where you want a lightweight, fast store (reads and writes in memory) but also durability (via append-only file format) and transactional semantics (ACID with single-writer, multiple-reader locking). Among its distinguishing features are support for custom indexing (even within JSON values), spatial (geospatial) indexes with support up to 20 dimensions, flexible iteration over keys (ascending, descending, ranges), TTL/expiry eviction, and embeddability. Because it keeps its data in memory (with persistent backing), it's well suited for caching, session stores, small-scale databases inside Go applications, or applications that prefer simplicity and speed over massive scale. ... -
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Superset
Apache Superset is a data visualization and data exploration platform
Apache Superset is a modern data exploration and visualization platform. Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. Quickly and easily integrate and explore your data, using either our simple no-code viz builder or state-of-the-art SQL IDE. -
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Kibana
Your window into the Elastic Stack
Kibana is a analytics and search dashboard for Elasticsearch that allows you to visualize Elasticsearch data and efficiently navigate the Elastic Stack. With Kibana you can visualize and shape your data simply and intuitively, share visualizations for greater collaboration, organize dashboards and visualizations, and so much more. -
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Arnis
Generate any location from the real world in Minecraft
...The tool handles large-scale geospatial processing and transforms raw mapping data into a format compatible with Minecraft world generation. Users can generate entire regions, including detailed urban layouts and natural terrain, making it useful for education, visualization, or creative world-building projects. -
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MobilityDB
MobilityDB is a geospatial trajectory data management & analysis
MobilityDB is an extension for PostgreSQL and PostGIS that adds support for managing and querying moving object data, such as vehicles, vessels, or wildlife. It allows developers to store temporal and spatiotemporal data types and execute complex mobility analytics using SQL. It is particularly suited for GIS applications and location-based services. -
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CKAN
CKAN is an open-source DMS for powering data hubs
CKAN is the world’s leading open-source data portal platform. CKAN makes it easy to publish, share and work with data. It's a data management system that provides a powerful platform for cataloging, storing and accessing datasets with a rich front-end, full API (for both data and catalog), visualization tools and more.CKAN is used by national and regional government organizations throughout the European Union, the Americas, Asia, and Oceania to power a variety of official and community data... -
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HeavyDB
HeavyDB (formerly MapD/OmniSciDB)
...Its architecture allows users to query datasets containing billions of rows in milliseconds without requiring traditional indexing, pre-aggregation, or sampling techniques. HeavyDB was originally developed as part of the OmniSci platform (formerly MapD) and is commonly used for large-scale analytics and geospatial data processing. The database compiles queries into optimized machine code that executes efficiently on GPU hardware, significantly accelerating analytical workloads. It supports hybrid deployment environments where queries can run on both CPU and GPU architectures depending on the available resources. -
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Redis
An in-memory database that persists on disk
Redis is an open-source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions, and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster. ... -
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S2 Geometry
Computational geometry and spatial indexing on the sphere
s2geometry is Google’s open source geometry library designed for representing, analyzing, and manipulating geometric shapes on a sphere rather than a flat plane. This makes it particularly suited for applications involving geospatial data, such as mapping, spatial indexing, and geographic information systems (GIS). The library provides a robust mathematical framework for spherical geometry, allowing developers to work with polygons, points, and regions on the Earth’s surface using consistent and precise algorithms. Unlike traditional 2D geometry libraries, S2 ensures accuracy over large scales by modeling the globe directly, avoiding distortions caused by map projections. ...
