Dataset for Physics-Informed Geo-AI for Irrigation Quantification_CA Central Valley

This data element contains the foundational datasets required to execute the Physics-Informed Geo-AI irrigation mapping framework. These files provide the spatial and hydrological constraints necessary for the TabNet-parameterized SM2RAIN model.Included Files:Master_ML_Ready_Data.csv: The primary dataset used for model training and inference. This file integrates AlphaEarth satellite embeddings with hydrological forcing data (Soil Mosture from SMAP, Precipitation, ET from OpenET) and ground-truth irrigation from USGS, pre-processed for immediate use in the TabNet architecture.Grid_updated.csv: The geospatial index for the California Central Valley study area, containing 1km-resolution grid cell identifiers and coordinates.Usage Note:To ensure successful execution of the submitted Jupyter Notebook, these files should be placed in a directory labeled /Data within the project root. You may directly unzip the folder to have the folder Data. The notebook uses relative pathing to reference these elements for seamless reproducibility.