Abstract: Some embodiments include a method. The method can include mapping a spatial pattern of yield for a crop of an agricultural field and prescribing spatially-variable application rates of one or more nutrients for the agricultural field. Other embodiments of related methods and systems are also disclosed.

Abstract: A system and method to use remote sensing to estimate crop water use that is forecasted and is updated as weather and new satellite data become available. From these data the system and method uses a water accounting algorithm to prescribe irrigation differentially for regions of a field or for the entire field as an average. Irrigation prescription is delivered remotely through Internet technology.

Abstract: A method for prescribing variable seed density planting. The method can include: obtaining first EOS data collected approximately on an estimated day (DOY?) during a past crop-growing season in which NDVI* data most closely resembles a spatial-yield pattern measured during harvest in the past crop-growing season; converting the first EOS data to first reflectance data and first NDVI data; calculating first NDVI* data on a per pixel basis for the first EOS data based on the first NDVI data using satellite scene statistics of the first EOS data; generating an NDVI* map for a first field using the first NDVI* data for the first EOS data; and generating a variable seed density prescription map using the NDVI* map. The variable seed density prescription map can be spatially defined. Other embodiments are provided.

Abstract: A method for precisely applying chemicals targeted by digital maps developed from remotely sensed data, including: obtaining EOS data through a growing season of a crop growing in a field; processing the EOS data to reflectance values; removing error-inducing effects of atmospheric alteration from the processed EOS data; calculating from the processed EOS data a crop performance index that indicates one or more poor performing areas of the field; generating one or more maps of the crop performance index to allow a user to determine whether each of the one or more poor performing areas of the field are due to biological pests instead of topographic or soil constraints in discrete locations of the field; guiding the user to the one or more poor performing areas of the field using the one or more maps to allow the user to scout the one or more poor performing areas of the field to confirm and identify the biological pests; and providing guidance for a chemical application at the one or more poor performing areas