| Technology Application |
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A temporal-spatial variation analysis of land surface temperature in Beijing |
| WANG Yanhui, XIAO Yao |
| Key Laboratory of 3-Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China |
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Abstract Land surface temperature (LST) is an important parameter in such fields as meteorology, hydrology and ecology, and the inversion of land surface temperature by use of remote sensing data is a simple and effective method. In this paper, with the support of the 3S technology, the authors took Beijing City as the study area to study the land surface temperature inversion and analyze spatial and temporal characteristics. Using TM data obtained from 1989 to 2010 within the 5th Ring Rroad of Beijing, the authors adapted the single-window algorithm in 20a to the inversion of land surface temperature, with a comparative study of the verification of synchronous MODIS temperature products. On such a basis, the anomaly analysis and hatches analysis were conducted to reveal the overall characteristics of temporal and spatial variation of Beijing surface temperature in more than 20 a. The characteristics of temporal and spatial variation of NDMI and NDBI index were analyzed based on 20 years' land surface temperature of the study area, and the relationship between land surface temperature and NDMI as well as between land surface temperature and NDBI was quantitatively revealed and expounded. Research results show that the single-window algorithm method can obtain the reasonable land surface temperature and can reflect the spatial difference of surface heat condition. Beijing land surface temperature variation characteristics are obvious, surface temperature difference of different land cover types in the same period is evident, and heat island effect is also significant. A significant positive correlation between surface temperature and NDBI exists, and there is a significant negative correlation with NDMI, which means that both NDMI and NDBI are good indicators for marking surface thermal characteristics, and they can be used to provide an effective basis for monitoring surface temperature changes and its spatial and temporal characteristics.
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| Keywords
multimodal remote sensing images
image registration
point-feature detecting and matching algorithm
curve-feature matching algorithm
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Issue Date: 01 July 2014
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2014,
Vol. 26
