Python has over 200 standard libraries and thousands of third-party libraries. Here are some of the frequently used libraries for GIS purposes:

1. ArcPy: ESRI's ArcGIS Python library for performing geoprocessing operations. It is a useful and productive way to perform geographic data analysis, data conversion, data management, and map automation with Python.

2. Geopandas: Python library capable of adding geographic components to tabular analysis, thereby make working with geospatial data in python easier.

3. GDAL: Python library used for translating between GIS data formats and extensions.

4. RSGISLib: It is a Remote Sensing and GIS software Library for raster processing and analysis. It is a collection of tools for processing remote sensing and GIS datasets.

5. PyProj: Library for performing GIS data projection and datum transformation within a range of geographic referencing systems. It can also be used to perform geodetic calculations and distance measurements for any datum.

6. LiDAR: Python library used for processing and visualizing Light Detection and Ranging (LiDAR) dataset. It is a Python package for delineating the nested hierarchy of surface depressions in Digital Elevation Models (DEMs). It is particularly useful for analyzing high-resolution topographic data, such as DEMs derived from LiDAR data.