Rioxarray

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

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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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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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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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Merge rasters in Python using Rioxarray

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Rasters merging/mosaic is one of the common task in raster processing. In this tutorial, we will merge multiple rasters into one in python using Rioxarray. Merging/mosaic multiple rasters into one is also known as union of rasters. Rioxarray is open source gis package that extends the functionality of xarray by rasterio. Before merging multiple rasters

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Upsample and Downsample raster in python using rioxarray

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Raster resampling refers to altering the raster resolution by changing raster grid. Upsampling refers to reducing pixel size and increasing resolution. And downsampling refers to increasing pixel size and reducing resolution. The raster resampling or upscaling/downscaling is done when you want to convert 10 meter cell to 50 meter cell or vice versa. Even when

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Clip raster by polygon geometry in Python using Rioxarray

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Clip/crop raster by polygon geometry in Python using Rioxarray Raster clipping is one of the common task in raster processing. In this tutorial, we will clip a raster by polygon geometry in python using Rioxarray. Rioxarray is open source gis package that extends the functionality of xarray by rasterio. Before cropping/clipping the raster data, we

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Polygonize Raster using Rioxarray and GeoPandas

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Rioxarray is python library which combines xarray and rasterio library for raster analysis. Xarray is open source and python packages that makes working with labelled multi dimensional array very efficient. RasterIO is open source and python package based on gdal to read/write and analyze raster data. Rioxarray extends xarray with rasterio accessor. One of the

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