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Turf is a JavaScript and TypeScript geospatial analysis library and toolkit used for performing spatial analysis and geometric operations on GeoJSON data. It functions as a modular spatial engine that allows for the generation, manipulation, and classification of geographic datasets within web and node environments. The library provides a set of utility functions to programmatically create structured points, lines, and polygons. It enables the calculation of distances, areas, and geometric relationships between geographic coordinates, supporting both browser-based geospatial analysis and clie
Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr
SpatialLM is a spatial modeling framework that uses large language models to transform monocular video and sensor data into structured indoor semantic maps. It functions as a system for indoor layout estimation and a point cloud semantic parser, converting raw geometric data into representations of architectural elements and object categories. The project aligns multi-modal sensor inputs with linguistic tokens, allowing a language model to serve as a reasoning engine for inferring room topology. It employs mechanisms to convert 3D point clouds and 2D image sequences into discrete tokens and s
GeoPandas is a Python library that extends pandas with native support for geospatial data. It treats geographic geometries—points, lines, and polygons—as a first-class column type within DataFrames, enabling users to store, manipulate, and analyze vector spatial data alongside traditional tabular attributes. The library is built on top of proven geospatial components: it uses Shapely for all geometric operations, Fiona and GDAL for reading and writing standard spatial file formats, PyProj for coordinate reprojection, and an R‑tree spatial index (from Shapely) to accelerate spatial queries. Wh
Classes and methods for spatio-temporal data
The main features of edzer/spacetime are: Spatial Analysis.
Projects with overlapping indexed features include: turfjs/turf — Turf is a JavaScript and TypeScript geospatial analysis library and toolkit used for performing spatial analysis and… memgraph/memgraph — Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management.… manycore-research/spatiallm — SpatialLM is a spatial modeling framework that uses large language models to transform monocular video and sensor data… lchiffon/remap — create a map by R. mtennekes/tmap — R package for thematic maps. pysal/pysal — PySAL: Python Spatial Analysis Library Meta-Package.