Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations
AbstractThe rapid and accurate estimation of wheat production at a regional scale is crucial for national food security and sustainable agricultural development. This study developed a new gross primary productivity (GPP) estimation model (denoted as the [ACPM]), based on the effects of light, heat, soil moisture, and nitrogen content (N) on the light-use efficiency of winter wheat. The ACPM model used the quantic additivity of the environmental factors to improve the minimum form or multiple multiplication form in the previous model and thus characterized the joint effects of heat, soil moisture, and N on crop photosynthesis performance. The key parameters (i.e., light) were determined from the photosynthetically active radiation product of the Himawari-8 sensor and the fraction of photosynthetically active radiation product of Moderate Resolution Imaging Spectroradiometer (MODIS). The heat was determined from the land temperature products of MODIS. The soil moisture was obtained from the inversion using a visible and shortwave infrared drought index (VSDI), whereas the N stress of winter wheat was detected using the newly developed modified ratio vegetation index (MRVI), which could accurately obtain the spatiotemporal distribution of the leaf chlorophyll content of winter wheat. The ACPM and two other previous models (named the GPP1 and GPP2 models) were applied on the Himawari-8 and MODIS images in Hengshui City. The evaluation results, based on the ground measurement, indicated that the ACPM models exhibited the best estimate of dry aboveground biomass (DAM) and the wheat yield in Hengshui City, with errors of <10% and <12% for the DAM and yield, respectively. Considering the easy operation of the ACPM model and the accessibility of the corresponding satellite images, the Agriculture Crop Photosynthesis Model (ACPM) can be expected to provide information on the winter wheat shortfalls and surplus ahead of the availability of official statistical data. View Full-Text
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Sui, J.; Qin, Q.; Ren, H.; Sun, Y.; Zhang, T.; Wang, J.; Gong, S. Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations. Remote Sens. 2018, 10, 962.
Sui J, Qin Q, Ren H, Sun Y, Zhang T, Wang J, Gong S. Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations. Remote Sensing. 2018; 10(6):962.Chicago/Turabian Style
Sui, Juan; Qin, Qiming; Ren, Huazhong; Sun, Yuanheng; Zhang, Tianyuan; Wang, Jiandong; Gong, Shihong. 2018. "Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations." Remote Sens. 10, no. 6: 962.
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