Title :
Spatio-temporal variation trends of vegetation net primary productivity based on AVHRR
Author :
Ting Li ; Lin Wang
Author_Institution :
Coll. of Appl. Meteorol., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
Abstract :
Using NPP data from NOAA/AVHRR, this article analyzed spatio-temporal characteristics of vegetation net primary productivity (NPP) and discussed the impact of climate factors in the lower-middle reaches of Yangtze River. Results reported that the average value of annual NPP was 1147.1 gC/(m2·a) in the study area. And NPP in 1995 had the largest mean value (1310.5 gC/(m2·a)), while 1988 had the lowest one (1017.3 gC/(m2·a)). Annual NPP during 20 years increased overall. With respect to spatial distribution, NPP values in the northeastern part were higher than those in the southwest. And coastal NPP values were higher than those inland. NPP values showed a tendency of significant decrease in the south of Jiangsu province and Shanghai municipality because of economic development and urban expansion, while the ones in agriculture developed area with a significant increasing trend. The results revealed that NPP was influenced by climate factors. Temperature and sunshine duration time posed positive effect on NPP, while precipitation had little effect on it.
Keywords :
agriculture; atmospheric precipitation; atmospheric radiation; atmospheric temperature; ecology; geophysical techniques; radiometry; remote sensing; rivers; spatiotemporal phenomena; vegetation; AD 1988; AD 1995; Jiangsu province; NOAA/AVHRR; NPP data; Shanghai municipality; Yangtze River; agriculture; air temperature; climate factor; climate impact; coastal NPP values; economic development; lower-middle reaches; precipitation; spatiotemporal variation trends; sunshine duration time; urban expansion; vegetation net primary productivity; Economics; Image resolution; Monitoring; Rivers; Temperature measurement; Temperature sensors; US Government agencies; AVHRR; NPP; climate factors; spatio-temporal characteristics;
Conference_Titel :
Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4673-1272-1
DOI :
10.1109/CVRS.2012.6421290