Abstract: A method and system for automatically capturing and extracting data from images of agricultural field crops, weeds, and soil within management zones representing soil, water, and topography (SWAT) features of a field wherein the camera system is mounted onto and powered by any vehicle that may pass over agricultural fields. Images and data extracted from the images are automatically uploaded to a processing server for viewing and analysis by farmers and agricultural service providers. The images are analyzed by machine learning processes to document critical weed and crop data by SWAT management zone and entire fields.

Abstract: A method and system for a hydrological process that describes and characterises either statically or temporally, soil moisture variability within agricultural fields, specific to zone-based field recommendations. Surface and subsurface hydrological processes are combined with soil physical properties, electrical conductivity (EC), topography, soil moisture sensors and climate parameters from weather stations, to produce a zone-based soil moisture balance. This process facilitates in-season optimization of crop inputs such as water from irrigation, seed, nutrients, herbicides, or pesticides based on the soil moisture conditions throughout a field.

Abstract: The invention relates to the analysis of field characteristics to help determine prescriptions for crop input levels. A non-conductive enclosure houses a mapping system. The enclosure has a rectangular base and four walls extending from the base. A removable cover is received by the four walls. A foam interior receives at least one conductivity sensor. A port receives at least one electrical connection from an agricultural equipment in order to interface with the mapping system. A mounting assembly may mount the non-conductive enclosure to the agricultural equipment.