Raster

Building Georeferenced Datasets from HDF5 Files with h5py, xarray, and Rasterio

Leave a Comment / GIS, Raster, Rioxarray, xarray /

Introduction HDF5 (.h5) files are widely used in scientific computing, particularly for storing large-scale datasets from remote sensing missions, climate models, and other geospatial applications. These files are self-describing, meaning they store both the data and metadata (e.g., spatial extent, resolution, units, etc.) in a hierarchical structure. However, working with HDF5 files can be challenging […]

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How to Compare DSMs in Python: Analyze Surface Elevation Changes and Generate Heat Maps

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Introduction Digital Surface Models (DSMs) represent the Earth’s surface, including all features such as buildings, trees, and other objects above the ground. They are widely used in geospatial analysis for applications like urban planning, flood modeling, and vegetation monitoring. By comparing two DSMs from different time periods, we can detect changes in surface elevation caused

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Parallel Processing and Saving Raster Chunks Using Xarray and Dask

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In this tutorial, we’ll walk through how to process and save raster chunks in parallel using Xarray and Dask. This technique is particularly useful when working with large raster datasets where chunking and parallel processing can significantly improve efficiency. Prerequisites Before we begin, ensure you have the following Python libraries installed: You can install them

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Creating a GeoTIFF raster XYZ tile service in python with caching capability

2 Comments / GIS, OpenLayers, Python, Raster, Rioxarray /

In this tutorial, we’ll create a tile service for GeoTIFF files using Python, FastAPI, and various libraries such as xarray, rioxarray, rasterio, and Pillow. This service will dynamically generate map tiles on-the-fly and cache them for efficient retrieval. Prerequisites Before starting, ensure you have the following installed: Overview To get full source code for this

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Exploring 3D Terrain Visualization with Python: A DEM and PyVista Tutorial

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Introduction: Exploring Digital Elevation Models (DEMs) in 3D with Python Digital Elevation Models (DEMs) are crucial in geospatial analysis, providing a representation of the Earth’s surface topography. These gridded datasets encode elevation information, making them valuable for various applications, including terrain analysis, hydrology, and environmental modeling. In this tutorial, we will delve into the fascinating

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Line-of-Sight Analysis in Digital Elevation Models using Python

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This tutorial demonstrates a line-of-sight (LOS) analysis algorithm based on Digital Elevation Models (DEMs) in python. The script processes elevation data to determine the visibility between two points, assessing terrain obstruction along the direct line connecting them. The implementation is explained, and potential applications of LOS analysis are telecommunications, urban planning, and environmental monitoring. To

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Read raster data from postgis using python

1 Comment / Database, GIS, PostGIS, Psycopg2, Python, Raster, Rioxarray /

In this tutorial, we will learn how to read raster data from postgis table using python. Python is a powerful tool for raster data analysis due to rich library ecosystem: Python has a large number of libraries specifically designed for geospatial data analysis, such as rasterio, rioxarray, gdal, geopandas, shapely, etc. These libraries provide a

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