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Category: GDAL

link to GDAL Python Tutorial: Reading and Writing Raster Datasets

GDAL Python Tutorial: Reading and Writing Raster Datasets

The Geospatial Data Abstraction Library (GDAL) is the standard for managing spatial data formats. GDAL has been incorporated into many different enterprise and open source GIS projects. Because GDAL...

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link to How to Install GDAL for Python with pip on Windows

How to Install GDAL for Python with pip on Windows

Installing GDAL for Python with pip , the package installation package, is not as easy as it may seem. If you try to install GDAL to a python environment with a command like python -m pip install...

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link to How To Install GDAL for Python with Anaconda

How To Install GDAL for Python with Anaconda

The Geospatial Data Abstraction Library (GDAL) is a fundamental package for spatial analysis with Python. GDAL is a powerful package with a lot of functionality. However, it is notoriously difficult...

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link to Use Python to Convert Polygons to Raster with GDAL.RasterizeLayer

Use Python to Convert Polygons to Raster with GDAL.RasterizeLayer

When you work with spatial data it's inevitable that you will need to implement information from both a vector and raster data source for the same location. This task can easily be accomplished...

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link to Unsupervised Land Cover Classification with Python

Unsupervised Land Cover Classification with Python

Aerial imagery is used for purposes ranging from military actions to checking out the backyard of a house you might buy. Our human brains can easily identify features in these photographs, but it's...

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link to Python: Geographic Object-Based Image Analysis (GeOBIA) – Part 2: Image Classification

Python: Geographic Object-Based Image Analysis (GeOBIA) – Part 2: Image Classification

Use the random forests algorithm to classify image segments into land cover categories. This post is a continuation of Geographic Object-Based Image Analysis (GeOBIA). Herein, we use data describing...

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