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| Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data |
| Li-wen Zhang, Jing-feng Huang, Rui-fang Guo, Xin-xing Li, Wen-bo Sun, Xiu-zhen Wang |
| Institute of Remote Sensing and Information Application, Zhejiang University, Hangzhou 310058, China; Key Laboratory of Polluted Environment Remediation and Ecological Health, Ministry of Education, College of Natural Resources and Environmental Science, Zhejiang University, Hangzhou 310058, China; Key Laboratory of Agricultural Remote Sensing and Information System of Zhejiang Province, Hangzhou 310058, China; Meteorological Information Technology Support Center of Jilin Province, Changchun 130062, China; Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121, China |
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Abstract The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (Ta) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for Ta estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed Ta based on MODIS land surface temperature (LST) data. The verification results of maximum Ta, minimum Ta, GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001–2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.
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Received: 14 June 2012
Published: 31 January 2013
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