This article builds a mathematical model using dual‑landmark triangulation and perspective geometry to estimate the distance of a PLA drone that captured a high‑resolution image of Taipei 101, providing calculations, error analysis, and confidence intervals for the drone’s range.
This guide explains how to store and query GPS trajectory data in MongoDB using time‑series collections or traditional collections, covering schema design, indexing, sharding, TTL expiration, and practical query examples for high‑performance, schema‑free applications.
This article documents a Java implementation of a forest fire spread algorithm based on Wang Zhengfei's model, detailing the purpose, parameter definitions, and a series of computational methods—including wind and slope corrections, flame intensity, coordinate conversion, and spread speed—while noting the limitations of default parameter values.
The article explains ByteHouse's GIS capabilities, describing its R‑Tree and Google S2 spatial index implementation, OGC‑compatible data types and functions, and presents benchmark results that show ByteHouse outperforming ClickHouse, StarRocks, PostGIS, and DuckDB on key geospatial queries.
This article introduces the open‑source Python package TransBigData, explains how to install it, and demonstrates step‑by‑step methods for reading mobile signaling data, preprocessing, identifying stays and moves, extracting home and work locations, and visualizing individual activity patterns using Jupyter notebooks.
This guide explains how to choose and implement map visualization layouts—primary map focus, side‑by‑side view, or dual‑panel designs—and details point, line, and area visual elements along with common chart types to improve logistics efficiency and user experience.
This article introduces Redis's five extended data types—Stream, Geospatial, Bitmap, Bitfield, and HyperLogLog—explaining their concepts, common commands, and practical code examples, and highlights how they address specific internet‑scale scenarios more efficiently than traditional relational solutions.
This article demonstrates how to create detailed terrain maps in Python by installing and importing rasterio, geopandas, cartopy, and related libraries, configuring map fonts, and executing a comprehensive script that reads vector and raster data, applies custom color maps, and renders the final visualization.
This article explains how to use Baidu Maps' API with Python to programmatically generate map images covering a 1‑kilometer radius around a point, including step‑by‑step instructions, required API registration, coordinate setup, and a complete code example.
This article explains how Redis implements geospatial indexing with GEOADD and GEORADIUS commands, walks through their source‑code implementations, describes the underlying geohash calculations and nine‑cell grid search strategy, and derives the O(N + log M) time complexity for nearby‑people queries.
This article provides a comprehensive overview of UAV‑based oblique photogrammetry for real‑world 3D modeling, detailing background, step‑by‑step field capture, control‑point handling, aerial triangulation, model reconstruction, internal processing, and emerging trends in smart‑city applications.
This article provides an in‑depth tutorial on creating and customizing Cesium entities and primitives—including boxes, points, and various geometric shapes—explaining their properties, visual attributes, performance considerations, and offering complete JavaScript code examples for interactive 3D earth visualizations.
This article explains the Redis Geo module’s GEOADD and GEORADIUS commands, analyzes their source code, and details the geohash‑based algorithm that enables efficient “nearby people” queries by converting coordinates to 52‑bit scores, searching nine‑grid cells, and filtering by spherical distance.
This tutorial demonstrates how to load a large US census Parquet dataset, convert WebMercator coordinates, filter by geographic regions, and generate high‑resolution visualizations of population density and racial distribution using Python's Datashader library with various colormaps and export options.
This article demonstrates a step‑by‑step Python workflow for reading two Excel sheets, calculating haversine distances between latitude‑longitude pairs, identifying the nearest point for each record, and exporting the results, complete with code snippets, progress display, and performance advantages over traditional GIS tools.
Facing the post‑pandemic slowdown of e‑commerce growth, SuNing pioneered an O2O “smart retail” strategy by integrating online and offline channels through its “Anytime Business System,” which combines PostGIS‑enabled geospatial analysis, PostgreSQL high‑availability clustering with Citus, and seamless data flow across front‑end, transaction, and support layers.
Starting January 6, the U.S. government will enforce new export restrictions on AI software, especially geospatial image analysis tools, requiring licenses for shipments to China, a move that could impact drone, autonomous vehicle, and mapping companies worldwide while sparking debate among policymakers.
Amap leverages large‑scale visual intelligence—camera‑captured imagery, AI‑driven road‑sign and POI recognition, and compressed AR navigation overlays—to automate map creation, enhance real‑time positioning, and deliver richer travel experiences for its billion‑scale user base.
The study presents a four‑step pipeline that normalizes community data for rental platforms by clustering records using longest‑common‑prefix patterns, geographic filtering, Levenshtein similarity, and pattern‑based parent‑child assignment, achieving under 8 % false positives and 5 % false negatives.
This article explains the fundamentals of Geographic Information Science (GIS), recounts John Snow's historic cholera map as an early GIS example, and details how GIS technology can be leveraged to build a road‑logistics platform that enables real‑time monitoring, dispatch, path planning, and data‑driven decision making for transportation companies.
This article explores how Baidu Map’s open platform leverages web‑based visualization libraries such as ECharts, MapV, Canvas, SVG and WebGL to render point, line and polygon geospatial data—including heatmaps, clustering, and 3D charts—while addressing performance challenges of large‑scale datasets and outlining the front‑end technologies used.
This article explains the GeoHash algorithm, how it converts latitude‑longitude coordinates into hierarchical string codes, the precision trade‑offs of different code lengths, the binary encoding process, the use of space‑filling curves, and practical considerations when applying GeoHash for nearby point‑of‑interest searches.
This tutorial explains Redis 3.2 GEO capabilities, showing how to add geographic data with GEOADD, retrieve positions, calculate distances, query nearby points with GEORADIUS/GEORADIUSBYMEMBER, and implement practical features like "find nearby users" and an efficient "shake" random selector.
This article explains the challenges of location‑based services, why a two‑dimensional index is needed, and how Redis Geo provides precise, high‑performance geospatial operations that handle millions of requests per second for mobile applications.
