Spatio-temporal patterns and dynamics of net primary productivity for Kazakhstan

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Eisfelder, C.^1 ; Klein, I.^1 ; Huth, J.^1 ; Niklaus, M.^1 ; Kuenzer, C.^1

German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Oberpfaffenhofen, 82234 Wessling, Germany^1

关键词: Arid and semi-arid regions;    Natural vegetation;    Net primary productivity;    Spatial and temporal patterns;    Spatiotemporal patterns;    Sustainable land managements;    Vegetation dynamics;    Vegetation productivity;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012028/pdf
DOI  :  10.1088/1755-1315/17/1/012028

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Monitoring of net primary productivity (NPP) is especially important for the fragile ecosystems in arid and semi-arid regions. Great interest exists in observing large-scale vegetation dynamics and understanding spatial and temporal patterns of NPP in these areas. In this study we present results of NPP obtained with the model BETHY/DLR for Kazakhstan for 2003-2011 and its spatial and temporal dynamics. The spatial distribution of vegetation productivity shows a gradient from North to South and clear differences between individual vegetation classes. The monthly NPP values show the highest productivity in June. Differences between rain-fed and irrigated areas indicate the dependency on water availability. Annual NPP variability was high for agricultural areas, but showed low values for natural vegetation. The analysis of different patterns in vegetation productivity provides valuable information for the identification of regions that are vulnerable to a possible climate change. This information may thus substantially support a sustainable land management.