Gis

TL;DR: If your QGIS buffer is the wrong size, your CRS is EPSG:4326 (degrees) — switch to a projected CRS (e.g. a local UTM zone) before buffering, or enable the Geodesic Distance option in the QGIS 3.28+ Buffer dialog. The QGIS Buffer tool has one requirement that is easy to miss: the distance you enter is in the unit of the layer’s CRS, not the unit of your project CRS, and not any intuitive real-world unit you might have in mind. ...

Drop a DXF file onto your GIS and the geometry lands in the middle of the ocean, rotated 90 degrees, scaled by 25.4. Or it lands in the right country but offset by a few hundred metres. Or it imports cleanly into QGIS but every feature ends up on a single layer called “0” with no attributes beyond the original AutoCAD entity type. This is not a bug you can fix with a setting. The CAD-GIS format gap is structural. DWG and DXF were designed for engineering drawings, not for placing things on Earth. GIS formats were designed for the opposite. The two worlds have different answers to three fundamental questions: where are these objects, what do we know about them, and how do they relate to each other? ...

A shapefile arrives in your inbox, or you need to verify what’s in a .shp file before importing it into your pipeline. The two questions that come up immediately: what software do you need, and do you have to install anything? The short answer: no install required for a quick look. For anything involving CRS inspection, attribute filtering, or geometry validation, a desktop tool is worth the effort. What You’re Actually Inspecting A shapefile isn’t a single file — it’s a bundle that requires at least four components to be useful: ...

You have a CSV of postal addresses — a membership list, a customer database, a survey response set. Someone wants to know where these people are concentrated. A heatmap is the right output: it shows density without exposing individual addresses, it scales from 100 to 100,000 records without changing the workflow, and it overlays cleanly on basemaps, zoning layers, or any other spatial data you have. The full pipeline in QGIS: geocode addresses to coordinates using MMQGIS and Nominatim (OpenStreetMap’s free geocoding service), reproject the resulting point layer to a metric CRS, and run kernel density estimation in the QGIS Processing Toolbox. Three steps. The traps are in the rate limits, the CRS handling, and the distinction between two different “heatmap” tools inside QGIS that look alike and behave differently. ...

The problem with most “free GIS tools” roundup lists is that they treat GDAL, QGIS, GRASS, and PostGIS as competing products when they’re actually layers of the same stack. GDAL underpins QGIS. QGIS calls GRASS as a processing backend. PostGIS sits behind both for production data. Choosing between them isn’t “which is best” — it’s “which layer do I need to interact with directly.” This is a functional comparison: what each tool does well, where it breaks down, and which one to reach for when you receive a shapefile, a GeoJSON, or a KML and need it in something your software actually reads. ...

The thread A post in r/gis hit 101 upvotes this spring after a demo showed Claude performing CAD-adjacent spatial tasks. The 96 comments divided into three camps: alarm (entry-level GIS is gone), pragmatism (analysts who use AI will outcompete those who don’t), and dismissal (spatial analytics requires domain knowledge that LLMs don’t have). All three positions contain something true. The useful question is not “will AI replace GIS analysts?” — that framing produces either denial or panic, neither of which helps. The useful question is: which specific tasks are genuinely automatable, and what does that mean for how you spend your time? ...

A surveyor sends you a DWG with what looks like UTM coordinates. You open it in QGIS, the layer appears 100 kilometers from where you expected, and when you zoom to it the geometry is microscopic — a thirty-meter parcel that displays as a 30-millimeter sliver. You set the project CRS to the right UTM zone. Nothing changes. You build a custom CRS in metric units. Nothing changes. You ask the surveyor and they swear the file is correct in AutoCAD. ...

GeoJSON keeps showing up in places it shouldn’t. Someone drops a 2 GB .geojson into a processing pipeline, the script that used to run in 20 seconds runs for eight minutes, and the team spends a Thursday wondering whether the problem is their query planner, their RAM, or their patience. The problem is the format. GeoJSON is a perfectly good interchange format — human-readable, one-spec wonder, works everywhere a text editor opens. It’s a terrible working format as soon as your dataset has more than a few hundred thousand features. This post is about when to stop loading GeoJSON directly and what to convert to instead, based on what teams handling real-scale data actually reach for. ...

A GIS analyst exports a parcel layer from QGIS as DXF, opens it in Rhino for an urban design project, and a third of the parcels are missing. The ones with courtyards — inner holes — come in as the outer boundary only. A few with weird digitizing errors don’t come in at all. The analyst checks the QGIS layer: everything is there. The DXF is the problem, and so is the path that was used to produce it. ...

A state environmental agency analyst posted on r/gis last week, describing the same problem every public-sector GIS team deals with: contractors, federal agencies, and utility companies all send shapefiles that are technically valid per the format spec, and yet every batch requires hours of cleanup. The analyst was scoping an open-source CLI tool to run preflight checks — field truncation, CRS mismatch, missing indexes, null geometry. The tool they need already exists in pieces inside GDAL. The problem is that nobody publishes the checklist. Here is the full preflight — the specific failure modes, the ogrinfo and ogr2ogr commands that detect them, and the decisions each check forces. ...