边界地理空间数据：不同的途径和方法源代码

# Bounding Geospatial Data: Different Approaches and Methods <p align="center"> <img src="https://github.com/akhilchibber/Bounding-Geospatial-Data/blob/main/bounding_geospatial_data.jpg?raw=true" alt="earthml Logo"> </p> Welcome to the Geospatial Shapefile Processing Toolkit! This repository contains a collection of Python scripts, each designed to perform a specific type of processing on polygon shapefiles. Whether you're looking to extract geometrical shapes, analyze spatial boundaries, or transform data, these scripts provide a range of functionalities to suit your needs. ## Scripts Overview 1. **Delaunay Triangulation (TRIANGULATION.py)**: Generates a Delaunay Triangulation from a given polygon shapefile, useful for spatial analysis and triangulating points in a plane. 2. **Rotational Bounding Box (RO_BBOX.py)**: Calculates the rotational bounding box for a given polygon shapefile, which can be used in spatial data visualization and analysis. 3. **Convex Hull Extraction (CONVEX_HULL.py)**: Creates the Convex Hull of a polygon shapefile. This is helpful in understanding the outer boundary of a shape or dataset. 4. **Concave Hull Extraction (CONCAVE_HULL.py)**: Extracts the Concave Hull from a polygon shapefile, offering a tighter fitting boundary than the convex hull for irregular shapes. 5. **Circle Extraction (CIRCLE.py)**: Determines the smallest enclosing circle for a given polygon shapefile, useful in various geometrical computations. 6. **Bezier Envelope (BEZIER_ENVELOPE.py)**: Generates a Bezier Envelope from a polygon shapefile, which can be used for advanced geometrical representations and analyses. 7. **Bounding Box (BBOX.py)**: Extracts the standard bounding box of a polygon shapefile, essential for many spatial analysis tasks. ## Getting Started To use these scripts, you'll need Python installed on your system along with libraries such as `geopandas`, `shapely`, `scipy`, `numpy`, and others specific to each script. ### Prerequisites - Python 3.x - Libraries: `geopandas`, `shapely`, `scipy.spatial`, `numpy`, `alphashape`, `smallestenclosingcircle`, etc. ### Running the Scripts 1. Clone this repository to your local machine. 2. Install the required libraries. 3. Run the desired script with the appropriate shapefile as input. ## Contributing We welcome contributions to enhance the functionality and efficiency of this script. Feel free to fork, modify, and make pull requests to this repository. To contribute: 1. Fork the Project. 2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`). 3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`). 4. Push to the Branch (`git push origin feature/AmazingFeature`). 5. Open a Pull Request against the `main` branch. ## License This project is licensed under the MIT License - see the `LICENSE` file for details. ## Contact Author: Akhil Chhibber LinkedIn: https://www.linkedin.com/in/akhilchhibber/ Blog: https://medium.com/@akhil.chibber/bounding-geospatial-data-different-approaches-and-methods-704cff4eafed