Search Results for "geospatial"
Sort By:
Showing 126 open source projects for "geospatial"
View related business solutions-
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
1
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. ... -
2
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. -
3
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). -
4
GeoLibre
A lightweight, cloud-native GIS platform
GeoLibre is a free, open-source GIS platform for visualizing, exploring, and analyzing geospatial data. It is built to run across browsers, desktop apps, mobile screens, Android, and Jupyter notebooks. The platform keeps data local and private while still supporting cloud-native geospatial workflows. It uses technologies such as Tauri, React, TypeScript, MapLibre GL JS, DuckDB-WASM Spatial, and deck.gl. Users can load many local and remote geospatial formats, style map layers, inspect attributes, and run spatial analysis. ... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
5
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. -
6
leafmap
A Python package for interactive mapping and geospatial analysis
A Python package for geospatial analysis and interactive mapping in a Jupyter environment. Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). However, not everyone in the geospatial community has access to the GEE cloud computing platform. -
7
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. -
8
GeoServer
GeoServer repository
...GeoServer forms a core component of the Geospatial Web. -
9
Apache Sedona
Cluster computing framework for processing large-scale geospatial 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. According to our benchmark and third-party research papers, Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems for large-scale in-memory query processing. Sedona offers Scala, Java, Spatial SQL, Python, and R APIs and integrates them into underlying system kernels with care. ... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
10
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. ... -
11
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. -
12
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). -
13
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. ... -
14
Techniques
Techniques for deep learning with satellite & aerial imagery
...The guide includes code snippets, links to research papers, and hands-on tools, making it valuable for researchers, engineers, and enthusiasts working in remote sensing and geospatial AI. -
15
supercluster
A very fast geospatial point clustering library for browsers and Node
A very fast JavaScript library for geospatial point clustering for browsers and Node. supercluster supports property aggregation with the following two options. Map, a function that returns cluster properties corresponding to a single point. Reduce, a reduce function that merges properties of two clusters into one. -
16
Tile38
Ultra Fast Geospatial Database & Geofencing Server
When you need the best performance for your location-based applications, you can rely on Tile38. Tile38 is an ultra-fast, open source geospatial database and geofencing server capable of real-time geofencing, fast spatial indexing and more. It supports a variety of object types including lat/lon, Geohash, bbox, GeoJSON, QuadKey, and XYZ tile; and is capable of operations like Nearby, Within, and Intersects. There’s also built-in support for many popular tools. Tile38 is made up of 3 main components: the server, command line interface tool and server benchmark tool. ... -
17
Arnis
Generate any location from the real world in Minecraft
...By converting geographic information into Minecraft blocks and structures, Arnis allows users to explore real cities, neighborhoods, and landscapes in a virtual environment that mirrors the real world. 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. -
18
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. ... -
19
Martin
Blazing fast and lightweight PostGIS, MBtiles and PMtiles tile server
Martin is a fast and lightweight tile server for serving vector and raster tiles from PostGIS-enabled PostgreSQL databases. Written in Rust, it is optimized for performance and low memory usage, making it suitable for production geospatial applications. Martin supports modern web mapping standards and integrates seamlessly with MapLibre and other mapping libraries. -
20
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. -
21
Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in notebooks or the Code Editor, and export results to Cloud Storage, Drive, or asset collections. ... -
22
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. ... -
23
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. -
24
Digital Earth Australia notebooks
Repository for Digital Earth Australia Jupyter Notebooks
...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. -
25
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.
