This is a full-stack, self-hosted satellite ground station, not a data-research repository, though it contains substantial orbital-data ingestion, telemetry parsing, and signal-processing components. The application connects software-defined radios (RTL-SDR, Airspy, UHD, SoapySDR, SDRplay) to a real-time web UI for satellite tracking, hardware control, IQ/waterfall visualization, demodulation, decoding, recording, and observation scheduling. The backend is Python with FastAPI/Socket.IO, SQLAlchemy/Alembic, multiprocessing workers, and pub/sub broadcaster components; the frontend is React/Redux Toolkit/Material-UI. The user-facing system manages rotators and rigs via Hamlib, propagates TLE/OMM orbital elements, predicts passes, applies Doppler correction, schedules automated observations, and exposes file browsing, telemetry analysis, and audio transcription through external AI providers.
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.