Examining raster data properties

As a geospatial analyst, understanding the metadata and properties of these raster images is crucial as they provide insights into the image’s spatial reference, resolution, number of bands, data type, and other essential attributes. This information is vital for ensuring that the raster data is compatible with other datasets, aligns correctly within a spatial analysis, and is suitable for the intended analytical methods.

The following script serves as a practical tool for examining the metadata and properties of a raster image using the GDAL library in Python. By running this code, you can quickly assess the characteristics of a raster file, such as its projection, size, band properties, and more. This information is not only valuable for initial data exploration but also plays a critical role in preprocessing and quality control. Whether you’re integrating raster data with other spatial datasets, preparing it for analysis, or troubleshooting...