| Technology Application |
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NPP spatial and temporal pattern of vegetation in Beijing and its factor explanation based on CASA model |
| YIN Kai1, TIAN Yichen1, YUAN Chao1, ZHANG Feifei1, YUAN Quanzhi2, HUA Lizhong3 |
1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
2. Institure of Geography and Resources Science, Sichuan Normal University, Chengdu 610068, China;
3. Xiamen University of Technology, Xiamen 361024, China |
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Abstract Integrating remote sensing data, meteorological data and other multi-source auxiliary data, the vegetation net primary productivity (NPP) spatial and temporal pattern in Beijing and its main influence factors were analyzed based on carnegie-ames-stanford approach(CASA) model in 2010. The results showed that: 1 The total amount of NPP was 5.5 TgC, and the vegetation NPP spatial distribution pattern showed that the NPP in northern and western mountainous areas was higher, while the NPP in plain area was lower. 2 The seasonal vegetation NPP in Beijing changed significantly. The NPP in summer was the largest, accounting for 62% of the NPP in the whole year. The smallest was in winter, accounted for only 3%, and the NPP in spring and autumn respectively accounted for 18% and 17% of the total NPP. 3 The vegetation NPP was limited by water and heat conditions. However, the main limiting factor was different in different areas. The natural vegetation in the northern and western mountainous areas was more affected by the temperature, while the crops in plain area were more easily affected by the precipitation. And the vegetation in the transition area from mountains to the plain was more affected by the solar radiation.
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| Keywords
preconditioning
sparse matrix
preconditioned conjugate gradient(PCG)
aerial triangulation
bundle adjustment
structure from motion
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Issue Date: 08 December 2014
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