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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #340489
Title: Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

Author
item YANG, YANG - US Department Of Agriculture (USDA)
item Anderson, Martha
item Gao, Feng
item Yang, Yun
item SUN, L. - US Department Of Agriculture (USDA)
item Dulaney, Wayne

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/11/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: In global agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska (part of the Platte River-High Plains Aquifer Long-Term Agricultural Research site) that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date.