Cargando…

NDVI dynamics under changing meteorological factors in a shallow lake in future metropolitan, semiarid area in North China

Three meteorological parameters, including one parameter representing water conditions (i.e., precipitation) and two parameters representing energy conditions (i.e., net radiation and air temperature), were used to make an in-depth analysis of the response of Normalized Difference Vegetation Index (...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Yunlong, Wang, Xuan, Li, Chunhui, Cai, Yanpeng, Yang, Zhifeng, Yi, Yujun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206071/
https://www.ncbi.nlm.nih.gov/pubmed/30374106
http://dx.doi.org/10.1038/s41598-018-33968-w
Descripción
Sumario:Three meteorological parameters, including one parameter representing water conditions (i.e., precipitation) and two parameters representing energy conditions (i.e., net radiation and air temperature), were used to make an in-depth analysis of the response of Normalized Difference Vegetation Index (NDVI) dynamics to climate change in Lake Baiyangdian, a shallow lake located in Xiong’an New Area (XNA), a future metropolitan in North China. The results showed that the vegetation coverage of the entire area remained at a medium level with average NDVI being 0.46 during 2000–2015. At a yearly scale, water was the key factor controlling the reed growth in Lake Baiyangdian. NDVI variations in each season had different water/energy driving factors. In spring, summer and autumn, vegetation growth was mainly affected by net radiation, air temperature and air temperature, respectively. Time-lags between NDVI and the meteorological parameters varied from parameters and seasons. Taken together, this research broadened our cognition about response characteristics of NDVI dynamics to water and energy variations through adding an important meteorological parameter (i.e., net radiation). With the rapid construction of XNA, it could be helpful for accurately understanding impacts of climate change on vegetation growth and be beneficial for effective ecosystem management in water shortage areas.