terrio v0.5.0：纯 Rust 地理空间工具新增矢量处理与 MCP 工具
terrio v0.5.0 发布，纯 Rust 读写转换重投影栅格/矢量/点云，新增矢量叠加、栅格分区统计、SQL 命令、GRIB 格式与 WASM 多线程，所有新命令同时是 MCP 工具。
terrio v0.5.0 is here! terrio reads, writes, converts and reprojects geospatial rasters, vectors and point clouds in pure Rust, with no GDAL and no C dependencies. Use it from the command line, Python, JavaScript (WebAssembly) or Rust, or let an AI agent drive it. What's new in v0.5.0 - Vector processing: buffer, overlay (intersection, union, difference), dissolve, is-valid, make-valid and clean, plus centroid, singlepart, vertices and footprint. - Raster analysis: contour lines, zonal statistics across bands and rasters, and sampling many rasters at points. - SQL: a standalone terrio sql command for querying vector layers. - A rio command line: terrio-rio runs rasterio's rio commands (info, clip, merge, warp, calc and more). - New formats: GRIB1 and GRIB2 weather data, read lazily from local files or remotely from NOAA and ECMWF. - Point clouds: more of PDAL's filters (dbscan, covariancefeatures, lof, dem, colorization, overlay and more), and appending points to EPT datasets in place. - Coordinates: transformations between vertical CRSs, point motion between coordinate epochs. - Multidimensional data: Zarr arrays with more than three dimensions, netCDF groups written from Python and JavaScript, and xarray subdatasets, GCPs and RPCs opened as rioxarray opens them. - STAC: POST searches with paging, and Microsoft Planetary Computer signing. - WebAssembly: multithreading (6 to 8x faster decoding and COG writing in Node.js, Chromium and Firefox), a terrio-js/core module that is less than half the download, and terrio-js/memory64 for datasets larger than 4 GB. Every new processing command is also an MCP tool, so AI agents can run them too. Try it out - Playground in your browser: https://terrio.opengeos.org/playground/ - Documentation: https://terrio.opengeos.org - GitHub: https://github.com/opengeos/terrio - Release notes: https://github.com/opengeos/terrio/releases/tag/v0.5.0 #GIS #Rust #OpenSource #Geospatial #Python #WebAssembly #GDAL