TY - GEN
T1 - Study of the vegetation index-meteorological factor correlation adjusted by accumulated growing degree days
AU - Kang, Lingjun
AU - Di, Liping
AU - Yu, Eugene
AU - Lin, Li
AU - Shrestha, Ranjay
AU - Xu, Yang
AU - Rahman, Md Shahinoor
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/26
Y1 - 2016/9/26
N2 - In previous studies, the correlation between the vegetation index and meteorological factors were investigated with in intervals defined by the day-of-year. Compared with the day-of-year, the accumulated growing degree days (AGDD) more effectively reflect vegetation growing stage, which serves as important references in agricultural management and disaster prediction. From this end, it is also worth to investigate vegetation-meteorological factor correlation within intervals defined by the AGDD. In this paper, pixel-wise VCI-meteorological factor (i.e. precipitation and temperature) correlation was analyzed in grass/pasture land by different intervals adjusted by the AGDD. According to results, variances of VCI-meteorological factor correlation were unveiled across different intervals. Summarily, the temperature serves as the dominant factor on VCI dynamics before the heating accumulation necessary for grass growing is achieved. Within these intervals, the precipitation is weakly correlated with the VCI. As excessive heating is received after necessary heating condition is met, the precipitation replaces the temperature as the controlling factor and shows increasingly positive correlation with the VCI. Within the same intervals, VCI-temperature correlation coefficient decreases to negative level. The work in this paper is helpful to better understand intra-annual variances of VCI-meteorological factor correlation. Results from this paper will also serve as the reference for agricultural practices and management.
AB - In previous studies, the correlation between the vegetation index and meteorological factors were investigated with in intervals defined by the day-of-year. Compared with the day-of-year, the accumulated growing degree days (AGDD) more effectively reflect vegetation growing stage, which serves as important references in agricultural management and disaster prediction. From this end, it is also worth to investigate vegetation-meteorological factor correlation within intervals defined by the AGDD. In this paper, pixel-wise VCI-meteorological factor (i.e. precipitation and temperature) correlation was analyzed in grass/pasture land by different intervals adjusted by the AGDD. According to results, variances of VCI-meteorological factor correlation were unveiled across different intervals. Summarily, the temperature serves as the dominant factor on VCI dynamics before the heating accumulation necessary for grass growing is achieved. Within these intervals, the precipitation is weakly correlated with the VCI. As excessive heating is received after necessary heating condition is met, the precipitation replaces the temperature as the controlling factor and shows increasingly positive correlation with the VCI. Within the same intervals, VCI-temperature correlation coefficient decreases to negative level. The work in this paper is helpful to better understand intra-annual variances of VCI-meteorological factor correlation. Results from this paper will also serve as the reference for agricultural practices and management.
KW - accumulated growing degree days
KW - precipitation
KW - temperature
KW - vegetation condition index
UR - http://www.scopus.com/inward/record.url?scp=84994142341&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84994142341&partnerID=8YFLogxK
U2 - 10.1109/Agro-Geoinformatics.2016.7577672
DO - 10.1109/Agro-Geoinformatics.2016.7577672
M3 - Conference contribution
AN - SCOPUS:84994142341
T3 - 2016 5th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2016
BT - 2016 5th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2016
Y2 - 18 July 2016 through 20 July 2016
ER -