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Line Simplification Algorihtms in Python

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Here is an example of how the Douglas-Peucker, Visvalingam-Whyatt, and Reumann-Witkam line simplification algorithms can be implemented in Python: Douglas-Peucker algorithm: Visvalingam-Whyatt algorithm: Reumann-Witkam algorithm: In these implementations, the input is a list of points, and the tolerance value is a real number used to define the level of simplification. The output is a simplified version of the input line, represented as a list of points. It’s important to note that these implementations make use […]

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Saving GIS Data to Another File Format using Python

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In this example, the data is read from a shapefile and written to a geojson file. The properties, crs, and schema of the new file are defined from the source file using the src.schema and src.crs attributes. It’s important to note that when saving the data to a new file, the file format and the driver must be specified correctly, and the schema and properties must match the data being written. You can also use

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How to Read Several Common GIS Data Types using Python

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This example shows how easy it is to read a shapefile using Fiona, you can open a file, iterate over the features and access the data, and close the file using the “with” statement. Fiona also supports other formats such as geojson, KML, and others, you can use the same approach to read these other formats, by simply changing the file path and extension when opening the file with the fiona.open() method. For example, to

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How to Read Features and Coordinates from ESRI Shapefile using Python

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This line imports the OGR library, allowing you to use its functions and methods to read in features and coordinates from the shapefile. It’s important to note that you may need to install GDAL library to use the OGR library, you can install it via pip by running pip install gdal in your command prompt or terminal.

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10 Python Libraries for GIS and Mapping

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Python Libraries for GIS and Mapping Python libraries are the ultimate extension in GIS because it allows you to boost its core functionality. By using Python libraries, you can break out of the mould that is GIS and dive into some serious data science. There are 200+ standard libraries in Python. But there are thousands of third-party libraries too. So, it’s endless how far you can take it. Today, it’s all about Python libraries in

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