Abstract

Very high resolution (VHR) satellite data is experiencing rapid annual growth, producing petabytes of remotely sensed data per year. The WorldView constellation, operated by DigitalGlobe, images over 1.2billionkm2 annually at <2m spatial resolution. Due to computation, data cost, and methodological concerns, VHR satellite data has mainly been used to produce needed geospatial information for site-specific phenomena. This project produced a VHR spatiotemporally explicit wall-to-wall cropland area map for the rainfed residential cropland mosaic of the Tigray Region, Ethiopia, which is comprised mostly of smallholder farms. Moderate resolution satellite data do not have adequate spatial resolution to capture the total area occupied by smallholder farms, i.e., farms with agricultural fields of ≤45×45m in dimension. In order to accurately map smallholder cropped area over a large region, hundreds of VHR images spanning two or more years are needed. Sub-meter WorldView-1 and WorldView-2 segmentation results were combined with median phenology amplitude from Landsat 8 data to map cropped area. Over 2700 VHR WorldView-1, -2 data were obtained from the U.S. National Geospatial-Intelligence Agency (NGA) via the NextView license agreement and were processed from raw imagery to produce a smallholder crop map in ~1week using a semi-automated method with the large computing capacity of the Advanced Data Analytics Platform. We estimated cropped area in Tigray to be 46% with a commission error of 5%±10% and omission error of 15%±12%. This methodology is extensible to other regions with similar vegetation texture and can easily be expanded to run on much larger regions.

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