Category: Hiking & Activities

Reproject masked array with rasterio

Reprojecting Masked Arrays with Rasterio: A Human’s Guide Geospatial data can be a real beast, especially when coordinate systems clash or you’re dealing with areas riddled with missing data. That’s where Rasterio, a seriously handy Python library, comes to the rescue. It’s your go-to tool for reading and writing geospatial raster data, and it’s got

Multiple Conditional Reclassification – ArcGIS

Getting Down and Dirty with Conditional Reclassification in ArcGIS Okay, so you’re diving into the world of Geographic Information Systems (GIS) and want to wrangle your spatial data into something truly insightful, right? That’s where reclassification comes in – it’s like taking raw ingredients and turning them into a gourmet meal. And when you need

QGIS OS grid overlay

Decoding the OS Grid in QGIS: A Friendly Guide If you’re messing around with maps and spatial data in the UK, you’re almost certain to bump into the Ordnance Survey (OS) grid. Think of it as the UK’s special way of pinpointing locations. Now, QGIS, being the awesome open-source GIS software it is, gives you

How to turn a shapefile into a table?

Shapefiles to Tables: Unleashing Your Geospatial Data Shapefiles. We’ve all been there, right? They’re the go-to for storing maps and geographic info as points, lines, and polygons. But let’s be honest, sometimes you just need that data in a table – something you can easily open in Excel, load into a database, or analyze with

Inserting X,Y to Geometry in Spring Boot and PostgreSQL?

Inserting X,Y to Geometry in Spring Boot and PostgreSQL: A Human’s Guide Let’s face it, geospatial data is everywhere these days. From your phone’s maps app guiding you to the nearest coffee shop to complex logistics operations tracking shipments across the globe, location matters. And if you’re building applications that deal with location, you’re going

How to fill the gap by using IDW(inverse distance weighting method) in R?

Filling the Gaps: A Human’s Guide to Inverse Distance Weighting (IDW) in R Okay, let’s face it: spatial data is rarely perfect. We’ve all been there – staring at a map with frustrating holes in it. Missing weather readings, sensor failures, patchy survey results… it’s enough to make you want to throw your hands up!

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