A RESTful API for Python-Based Server-Side Analysis of High-Resolution Soil Moisture Downscaling Data

GeoWATCH (formerly DASSP) is a Python-based software library for nowcasting and forecasting of high-resolution soil moisture and soil strength to support applications in agriculture, forestry, construction, recreation, and defense. GeoWATCH’s ground state predictions are generated via a physics-based downscaling approach that fuses weather-scale (1/4 degree spatial scale) land surface model estimates of soil moisture and land surface water and energy fluxes, with terabytes of high resolution (1 to 3 arc-second spatial scale) geospatial data including topography, land cover, soil classification, and vegetation information. A demonstration version of GeoWATCH is currently hosted on an AWS EC2 server instance at https://mobility.crearecomputing.com/, supporting both WMS and WCS data access.

This paper describes our addition of a RESTful API to GeoWATCH which enables server-side processing and analysis of its soil moisture and soil strength data products. In particular, it provides the ability to perform numerical and statistical analysis of data layers across user‑specified time periods and/or spatial extents. This is enabled through encapsulation of pertinent NumPy and SciPy algorithms for user-invoked server-side processing. We present the structure of our HTTP-based RESTful API which enables specification of the desired NumPy/SciPy analysis methods, user-specified parameters, and time periods. We demonstrate use of these capabilities accessed through a GIS client. Finally, we describe our progress in open-sourcing of GeoWATCH’s Python-based libraries for topographic analysis (pyDEM) and plug-and-play geospatial data processing pipelines (PODPAC).