TY - GEN
T1 - Spatiotemporal vegetation dynamic patterns in a subtropical humid region of China
AU - Qiu, Bingwen
AU - Feng, Min
AU - Zhong, Ming
AU - Tang, Zhenghong
AU - Chen, Chongcheng
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (grant no. 41471362) and Foundation for the Returned Overseas Chinese Scholars by the Human Resources and Social Ministry of China.
Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/13
Y1 - 2015/10/13
N2 - This paper aims to improve our knowledge of the complex vegetation-climate relationship in subtropical humid region in the context of global warming, by taking into considerations of spatio-temporal variation of both vegetation and climate change. A multi-resolution analysis (MRA) based on the wavelet transform (WT) is applied to examine the vegetation growth and its relationship with climate factors based on 250m 16-day composites MODIS vegetation EVI dataset in subtropical humid region of China over the period 2001-2010. A general greening up (68%) was observed over the period 2001-2010, as well as rather local negative trends. A trend toward global warming was also observed for the whole study region, whereas no obvious trend of precipitation is examined in most areas. Temperature generally has a positive influence on vegetation; with only very few negative EVI-temperature coefficients observed on the south portion principally due to changes in land use, land degradation, and cloud noise. However, nearly equally positive and negative EVI-rainfall relationship is observed on the inter-annual level, with negative coefficients principally observed in the northwest portion with abundant precipitation. Very strong positive relationship is observed between both EVI-temperature and EVI-precipitation at seasonal level. It is revealed that spatio-temporal variation of both vegetation and climate should be taken into considerations when analyzing the long-term effects of global climate change. Interactions between vegetation dynamics and climate variability must be studied through spatially and temporally explicit multi-scale analysis to investigate the influence of long-term climate change on the vegetation growth.
AB - This paper aims to improve our knowledge of the complex vegetation-climate relationship in subtropical humid region in the context of global warming, by taking into considerations of spatio-temporal variation of both vegetation and climate change. A multi-resolution analysis (MRA) based on the wavelet transform (WT) is applied to examine the vegetation growth and its relationship with climate factors based on 250m 16-day composites MODIS vegetation EVI dataset in subtropical humid region of China over the period 2001-2010. A general greening up (68%) was observed over the period 2001-2010, as well as rather local negative trends. A trend toward global warming was also observed for the whole study region, whereas no obvious trend of precipitation is examined in most areas. Temperature generally has a positive influence on vegetation; with only very few negative EVI-temperature coefficients observed on the south portion principally due to changes in land use, land degradation, and cloud noise. However, nearly equally positive and negative EVI-rainfall relationship is observed on the inter-annual level, with negative coefficients principally observed in the northwest portion with abundant precipitation. Very strong positive relationship is observed between both EVI-temperature and EVI-precipitation at seasonal level. It is revealed that spatio-temporal variation of both vegetation and climate should be taken into considerations when analyzing the long-term effects of global climate change. Interactions between vegetation dynamics and climate variability must be studied through spatially and temporally explicit multi-scale analysis to investigate the influence of long-term climate change on the vegetation growth.
KW - Climate change
KW - Enhanced Vegetation Index (EVI)
KW - Non-stationary
KW - Subtropical humid region
KW - Vegetation dynamic
KW - Wavelet transform
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U2 - 10.1109/ICSDM.2015.7298032
DO - 10.1109/ICSDM.2015.7298032
M3 - Conference contribution
AN - SCOPUS:84956685205
T3 - ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services
SP - 93
EP - 98
BT - ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services
A2 - Chen, Chongcheng
A2 - Guo, Diansheng
A2 - Leung, Yee
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM 2015
Y2 - 8 July 2015 through 10 July 2015
ER -