GeoWombat is an open-source Python library for geospatial raster data processing and remote sensing analysis at scale. It provides a high-level API built on xarray, rasterio, Dask, and geopandas, enabling lazy, parallel processing of multi-spectral satellite imagery (Landsat, Sentinel-2, NAIP, etc.). The library's architecture centers on a custom xarray accessor (`.gw`) that exposes geospatial properties and methods, and a configuration context manager for setting sensor profiles, reprojection parameters, and other global settings. Key capabilities include raster I/O with on-the-fly warping/mosaicking, vegetation indices, radiometric corrections (BRDF, 6S, topographic), QA masking, time-series analysis, moving-window statistics (Cython-accelerated), and machine/deep learning classification and object detection (YOLO, TorchGeo, SAM). It supports STAC cloud access and distributed computation via Dask. The codebase demonstrates solid engineering with modular backends, extensible patterns, and comprehensive test coverage, though it carries some technical debt from pinned dependencies and large monolithic modules. It is actively maintained, with a broad user community and integrations with wider geospatial ecosystems.