Soil scientists interested in landscape processes are faced with a trade-off when it comes to data collection: spatial vs. temporal resolution. We can infrequently measure static soil properties at many locations and interpolate spatially using external variables (e.g. terrain) or geostatistics. Or we can frequently monitor dynamic soil properties at relatively few locations. The goal of the collaborative project we present here is to think about how best to combine high spatial and high temporal resolution data to construction high spatio-temporal resolution soil process models. Toward this end, at the 90 acre Cook Agronomy Farm in Eastern Washington, we have installed 60 EC-TE sensors that measure volumetric water content, electrical conductivity and temperature. Using landscape analysis, 12 representative sites were selected using a stratified random procedure and sensors were installed at 1, 2, 3, 4 and 5 ft depths. Radio frequency wireless transmitters link sensors to a central data station where it is made available to anywhere in the world via a cell phone link. For spatial modeling, we have analyzed soil cores at approximately 180 locations, with 5-m resolution terrain, electrical conductivity (wet and dry season), and yield. For this talk we will present an overview of this work and initial scaling approaches.