Contextualizing Remotely Sensed Crop Yield with Landscape Statistics

Keywords: Landscape Statistics, Conservation, Remote Sensing, Farming
Abstract Type: Paper Abstract

Abstract

Remote sensing applied to yield indices allows for the democratization of yield and extrapolation algorithms at larger scales and finer temporal ranges. The applications of crop yield data is sweeping and varied. Yield statics can provide an enhanced picture of landscape dynamics in rural states. The need for further contextualization of yield data to provide stakeholders with clear landscape metrics is evident within land conversation frameworks. The need to extrapolate meaningful statics from modeled farm yield with the field of rural conversation in rural states exists. This approach uses high spatiotemporal resolution Rainfed Maize yield data created from a revised Production Efficiency model across the state of Nebraska in a 20-year time frame. The yield data were analyzed, applying landscape statics by quantifying groupings of first quartile crop yield (marginal land) to be targeted for conversation within a landscape. These landscape statistics are quantified using different landscape sizes to limit geographic basis. The statistics include patch density, continuity, and median patch size. The resulting analysis will provide targeted groupings of first-quartile crop yield (marginal) farmland to conservation organizations for possible easement applications.