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On-line Access: 2013-01-31

Received: 2012-06-14

Revision Accepted: 2012-10-15

Crosschecked: 2013-01-13

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Journal of Zhejiang University SCIENCE B 2013 Vol.14 No.2 P.144-161

http://doi.org/10.1631/jzus.B1200169


Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data


Author(s):  Li-wen Zhang, Jing-feng Huang, Rui-fang Guo, Xin-xing Li, Wen-bo Sun, Xiu-zhen Wang

Affiliation(s):  Institute of Remote Sensing and Information Application, Zhejiang University, Hangzhou 310058, China; more

Corresponding email(s):   flowerpapa@hotmail.com, hjf@zju.edu.cn

Key Words:  MODIS land surface temperature, Air temperature estimation, Reconstruction, Heat accumulation, Rice growing season, Growing degree day (GDD)


Li-wen Zhang, Jing-feng Huang, Rui-fang Guo, Xin-xing Li, Wen-bo Sun, Xiu-zhen Wang. Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data[J]. Journal of Zhejiang University Science B, 2013, 14(2): 144-161.

@article{title="Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data",
author="Li-wen Zhang, Jing-feng Huang, Rui-fang Guo, Xin-xing Li, Wen-bo Sun, Xiu-zhen Wang",
journal="Journal of Zhejiang University Science B",
volume="14",
number="2",
pages="144-161",
year="2013",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1200169"
}

%0 Journal Article
%T Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data
%A Li-wen Zhang
%A Jing-feng Huang
%A Rui-fang Guo
%A Xin-xing Li
%A Wen-bo Sun
%A Xiu-zhen Wang
%J Journal of Zhejiang University SCIENCE B
%V 14
%N 2
%P 144-161
%@ 1673-1581
%D 2013
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1200169

TY - JOUR
T1 - Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data
A1 - Li-wen Zhang
A1 - Jing-feng Huang
A1 - Rui-fang Guo
A1 - Xin-xing Li
A1 - Wen-bo Sun
A1 - Xiu-zhen Wang
J0 - Journal of Zhejiang University Science B
VL - 14
IS - 2
SP - 144
EP - 161
%@ 1673-1581
Y1 - 2013
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1200169


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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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