A High-Temperature Risk Assessment Model for Maize Based on MODIS LST

Xinlei Hu, Zuliang Zhao, Lin Zhang, Zhe Liu, Shaoming Li and Xiaodong Zhang
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Xinlei Hu: College of Land Science and Technology, China Agricultural University, Beijing 100083, China
Zuliang Zhao: College of Land Science and Technology, China Agricultural University, Beijing 100083, China
Lin Zhang: College of Land Science and Technology, China Agricultural University, Beijing 100083, China
Zhe Liu: College of Land Science and Technology, China Agricultural University, Beijing 100083, China
Shaoming Li: College of Land Science and Technology, China Agricultural University, Beijing 100083, China
Xiaodong Zhang: College of Land Science and Technology, China Agricultural University, Beijing 100083, China

Sustainability, 2019, vol. 11, issue 23, 1-15

Abstract: Currently, high-temperature risk assessments of crops at the regional scale are usually conducted by comparing the observed air temperature at ground stations or via the remote sensing inversion of canopy temperature (such as MODIS (moderate-resolution imaging spectroradiometer) land surface temperature (LST)) with the threshold temperature of the crop. Since this threshold is based on the absolute temperature value, it is difficult to account for changes in environmental conditions and crop canopy information between different regions and different years in the evaluation model. In this study, MODIS LST products were used to establish an evaluation model (spatiotemporal deviation mean (STDM)) and a classification method to determine maize-growing areas at risk of high temperatures at the regional scale. The study area was the Huang-Huai-Hai River plain of China where maize is grown and high temperatures occur frequently. The spatiotemporal distribution of the high-temperature risk of summer maize was determined in the study area from 2003 to 2018. The results demonstrate the applicability of the model at the regional scale. The distribution of high-temperature risk in the Huang-Huai-Hai region was consistent with the actual temperature measurements. The temperatures in the northwestern, southwestern, and southern parts were relatively high and the area was classified as a stable zone. Shijiazhuang, Jiaozuo, Weinan, Xi’an, and Xianyang city were located in a zone of increasing high temperatures. The regions with a stable high-temperature risk were Xiangfan, Yuncheng, and Luoyang city. Areas of decreasing high temperatures were Handan, Xingtai, Bozhou, Fuyang, Nanyang, Linfen, and Pingdingshan city. Areas that need to focus on preventing high-temperature risks include Luoyang, Yuncheng, Xianyang, Weinan, and Xi’an city. This study provides a new method for the detailed evaluation of regional high-temperature risk and data support.

Keywords: MODIS LST; spatiotemporal deviation; high-temperature risk; maize (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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