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Geospatial processing library based on GDAL and Google Earth Engine

Project description

GeoSpace

A Python library for geospatial processing based on GDAL.

GeoSpace is a powerful and efficient Python library designed to simplify geospatial data processing. It provides a comprehensive set of tools for working with raster and vector data, leveraging the capabilities of GDAL.

Installation

You can install GeoSpace using pip:

pip install geospace -U

Features

High-Performance Zonal Statistics

GeoSpace excels at performing zonal statistics, offering highly optimized functions for calculating statistics of raster values within polygons.

  • Area-Weighted Averaging: The basin_average function calculates the area-weighted average of raster values for each polygon in a shapefile. It is optimized for memory efficiency and parallel processing, making it suitable for large datasets and high-performance computing environments, including Slurm clusters.

basin_average Example

Here's an example of how to use the basin_average function to calculate the average precipitation and temperature for a set of basins:

import geospace as gs

# Paths to your rasters and shapefile
rasters = ['path/to/P.tif', 'path/to/T.tif']
basins_shp = 'path/to/basins.shp'

# Calculate the average values for each basin
df_stats = gs.basin_average(rasters, basins_shp)

# Rasters as rows and basins as columns
print(df_stats)

Raster Processing

  • Reprojection: Easily reproject rasters to different coordinate systems.
  • Resampling: Resample rasters to new resolutions using various algorithms.
  • Mosaicking: Combine multiple rasters into a single mosaic.
  • Clipping: Clip rasters to the extent of a shapefile.
  • Nodata Filling: Fill nodata values in rasters using various interpolation methods.
  • Data Type Conversion: Convert rasters to different data types (e.g., UInt8).
  • GRIB to GeoTIFF: Convert GRIB files to GeoTIFF format.

Vector Processing

  • Buffering: Create buffers around vector features.
  • Reprojection: Reproject shapefiles to different coordinate systems.
  • Filtering: Filter shapefiles based on attribute queries.
  • Polygonization: Convert rasters to polygon shapefiles.
  • Rasterization: Convert shapefiles to raster datasets.

Google Earth Engine Integration

  • Data Export: Export Google Earth Engine images to GeoTIFF or CSV format.
  • SoilGrids: Download and preprocess SoilGrids data.
  • Wind Data: Calculate wind speed from u and v components.
  • Time Series Analysis: Group image collections by month and calculate seasonality indices.

Utilities

  • Coordinate Conversion: Convert between geographic and image coordinates.
  • Spatial Calculations: Calculate grid cell areas and distances.
  • File Handling: Manage file paths and avoid name collisions.

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