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Remote Sens. 2013, 5(11), 5926-5943; doi:10.3390/rs5115926

A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US

1
Ministry of Education Key Laboratory for Earth System Modeling, and Center for Earth System Science, Tsinghua University, Beijing 100084, China
2
Department of Environmental Science, Policy and Management, University of California, Berkeley, Berkeley, CA 94720, USA
3
Plant Functional Biology and Climate Change Cluster Department, University of Technology Sydney, Broadway, NSW 2007, Australia
4
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
5
Department of Earth and Environment, Boston University, Boston, MA 02215, USA
*
Authors to whom correspondence should be addressed.
Received: 26 September 2013 / Revised: 6 November 2013 / Accepted: 7 November 2013 / Published: 14 November 2013
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Abstract

Remote sensing techniques that provide synoptic and repetitive observations over large geographic areas have become increasingly important in studying the role of agriculture in global carbon cycles. However, it is still challenging to model crop yields based on remotely sensed data due to the variation in radiation use efficiency (RUE) across crop types and the effects of spatial heterogeneity. In this paper, we propose a production efficiency model-based method to estimate corn and soybean yields with MODerate Resolution Imaging Spectroradiometer (MODIS) data by explicitly handling the following two issues: (1) field-measured RUE values for corn and soybean are applied to relatively pure pixels instead of the biome-wide RUE value prescribed in the MODIS vegetation productivity product (MOD17); and (2) contributions to productivity from vegetation other than crops in mixed pixels are deducted at the level of MODIS resolution. Our estimated yields statistically correlate with the national survey data for rainfed counties in the Midwestern US with low errors for both corn (R2 = 0.77; RMSE = 0.89 MT/ha) and soybeans (R2 = 0.66; RMSE = 0.38 MT/ha). Because the proposed algorithm does not require any retrospective analysis that constructs empirical relationships between the reported yields and remotely sensed data, it could monitor crop yields over large areas.
Keywords: remote sensing; crop yield; MODIS GPP; radiation use efficiency; spatial heterogeneity remote sensing; crop yield; MODIS GPP; radiation use efficiency; spatial heterogeneity
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Xin, Q.; Gong, P.; Yu, C.; Yu, L.; Broich, M.; Suyker, A.E.; Myneni, R.B. A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US. Remote Sens. 2013, 5, 5926-5943.

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