Monitoring responses of vegetation phenology and productivity to extreme climatic conditions using remote sensing across
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RESEARCH ARTICLE
Monitoring responses of vegetation phenology and productivity to extreme climatic conditions using remote sensing across different sub-regions of China Tehseen Javed 1,2 & Yi Li 1,2 & Kai Feng 1 & Olusola O. Ayantobo 3 & Shakeel Ahmad 2,4 & Xinguo Chen 1 & Sadaf Rashid 5 & Sovannaka Suon 1 Received: 9 May 2020 / Accepted: 7 September 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Drought is a major natural disaster that significantly impacts the susceptibility and flexibility of the ecosystem by changing vegetation phenology and productivity. This study aimed to investigate the impact of extreme climatic variation on vegetation phenology and productivity over the four sub-regions of China from 2000 to 2017. Daily rain gauge precipitation and air temperature datasets were used to estimate the trends, and to compute the standardized precipitation-evapotranspiration index (SPEI). Remote sensing–based Enhanced Vegetation Index (EVI) data from a moderate resolution imaging spectroradiometer (MODIS) was used to characterize vegetation phenology. The results revealed that (1) air temperature had significant increasing trends (P < 0.05) in all sub-regions. Precipitation showed a non-significant increasing trend in Northwest China (NWC) and insignificant decreasing trends in North China (NC), Qinghai Tibet area (QTA), and South China (SC). (2) Integrated enhanced vegetation index (iEVI) and SPEI variations depicted that 2011 and 2016 were the extremely driest and wettest years during 2000– 2017. (3) Rapid changes were observed in the vegetation phenology and productivity between 2011 and 2016. In 2011, changes in the vegetation phenology with the length of the growing season (ΔLGS) = was − 14 ± 36 days. In 2016, the overall net effect changed at the onset and end of the growing season with ΔLGS of 34 ± 71 days. The change in iEVI per SPEI increased rapidly with a changing rate of 0.16 from arid (NWC, and QTA) to semi-arid (NWC, QTA and NC) and declined with a rate of − 0.04 from semi-humid (QTA, NC, and SC) to humid (SC) region. A higher association was observed between iEVI and SPEI as compared to iEVI and precipitation. Our finding exposed that north China is more sensitive to climatic variation. Responsible editor: Philippe Garrigues * Yi Li [email protected] Tehseen Javed [email protected] 1
College of Water Resources and Architecture Engineering, Northwest A&F University, Yangling 712100, Shaanxi, People’s Republic of China
2
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, Shaanxi, People’s Republic of China
3
Department of Water Resources Management and Agricultural-Meteorology, Federal University of Agriculture, Abeokuta PMB 2240, Nigeria
4
College of Agronomy, Northwest Agriculture & Forestry University/ Key Laboratory of Physio-ecology, and Tillage in Loess Plateau, Ministry of Agriculture, Yangling 712100, China
5
Department of Physics, Islamia Coll
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