6 dépôts
Operations for combining geometry objects using convex hulls or point set unions.
Distinct from Spatial Data Extensions: Distinct from Spatial Data Extensions: focuses on aggregation operations rather than storage types.
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Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing
Combines multiple geometry objects into single results using spatial operations.
This project is a declarative visualization library and geospatial framework designed for rendering large-scale data sets within web browsers. It functions as a high-performance graphics engine that leverages hardware acceleration to display complex 2D and 3D visual layers, enabling the visualization of millions of data points through a structured, component-based syntax. The framework distinguishes itself through its ability to synchronize custom data visualizations with third-party mapping platforms. By managing camera states and coordinate systems, it allows developers to overlay high-perf
Provides hardware-accelerated spatial aggregation functions to summarize large datasets into grids or hexagons for visualization.
Kepler.gl is a web-based geospatial visualization framework designed for rendering large-scale location datasets. It functions as a modular React mapping component that enables developers to embed interactive, high-performance geographic visualizations into web applications, serving as a comprehensive engine for building browser-based GIS dashboards. The library distinguishes itself through a highly extensible architecture that centers on centralized state management. By utilizing a predictable state-driven model, it allows for the programmatic control of map layers, filters, and viewport set
Groups point-based data into grids, hexagons, or clusters to visualize density, distribution, and statistical trends.
H3 is an open-source library that provides a hierarchical hexagonal grid system for geospatial indexing. It projects the Earth onto an icosahedron and tiles each face with hexagons to minimize distortion, then encodes each hexagon as a 64-bit integer that stores its resolution and position in the hierarchy. This integer encoding enables fast bitwise operations for grid navigation and spatial analysis. The library offers a comprehensive set of grid topology algorithms for computing neighbor relationships, distances, and paths between cells directly on the hexagonal grid without geographic coor
Groups geographic data into hexagonal cells for multi-resolution spatial aggregation and analysis.
GeoPandas est une bibliothèque Python qui étend pandas avec une prise en charge native des données géospatiales. Elle traite les géométries géographiques — points, lignes et polygones — comme un type de colonne de premier ordre au sein des DataFrames, permettant aux utilisateurs de stocker, manipuler et analyser des données spatiales vectorielles parallèlement aux attributs tabulaires traditionnels. La bibliothèque s'appuie sur des composants géospatiaux éprouvés : elle utilise Shapely pour toutes les opérations géométriques, Fiona et GDAL pour la lecture et l'écriture de formats de fichiers spatiaux standard, PyProj pour la reprojection de coordonnées, et un index spatial R-tree (via Shapely) pour accélérer les requêtes spatiales. Ce qui distingue GeoPandas, c'est son intégration transparente de flux de travail d'analyse spatiale complets au sein de l'écosystème pandas. Les utilisateurs peuvent effectuer des transformations de systèmes de référence de coordonnées pour aligner les données entre différentes projections, calculer des propriétés géométriques telles que l'aire et la longueur, générer des zones tampons (buffers) et des centroïdes, et effectuer des opérations d'ensembles comme des intersections et des unions. La bibliothèque prend également en charge le filtrage basé sur la localisation, les jointures spatiales qui combinent des jeux de données basés sur des relations géométriques, et les analyses de superposition qui produisent des résultats agrégés. Pour l'exploration, elle offre des capacités de visualisation cartographique, produisant des tracés statiques et des cartes interactives directement à partir de tables spatiales. Au-delà de ces différenciateurs clés, GeoPandas gère le cycle de vie complet des données géographiques : importation et exportation vers des formats courants comme Shapefile, GeoJSON et GeoPackage ; gestion de tables spatiales liant la géométrie aux colonnes d'attributs ; et interrogation ou filtrage d'entités par localisation, conditions d'attributs ou prédicats spatiaux. Sa documentation couvre l'installation, une référence API complète et des guides utilisateur qui détaillent les tâches géospatiales courantes.
Combines geographic datasets based on spatial relationships to enrich attributes or aggregate results.
H2 is a JDBC-compliant relational database management system written in Java. It functions as an embeddable SQL database that can run directly within an application process to remove network latency, or as an in-memory database for high-performance volatile storage. It also includes a web-based console for executing SQL commands and administering schemas. The system is characterized by its flexible deployment modes, including a standalone server mode for remote TCP/IP access and a mixed mode for simultaneous local and remote connectivity. It features a dialect emulation layer and compatibilit
Computes the minimum bounding box that encloses a collection of geometry values using spatial aggregation.