Correlating analysis on spatio-temporal variation of LUCC and water resources based on remote sensing data

Yi Lin; Bing Liu; Yuan Lu; Feng Xie

doi:10.1117/12.2063843

14 May 2014 Correlating analysis on spatio-temporal variation of LUCC and water resources based on remote sensing data

Yi Lin, Bing Liu, Yuan Lu, Feng Xie

Proceedings Volume 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China; 91580Q (2014) https://doi.org/10.1117/12.2063843
Event: Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 2012, Wuhan, China

Abstract

Accurate classification for land use/cover with remote sensing image is the premise of monitoring land use/cover change, as well as temporal and spatial change analysis, which can distinguish the number, location and type of changed land during monitoring years. This paper presents a decision tree classification method based on expert knowledge for temporal and spatial variation analysis of land use/cover, which takes advantage of new water index (NWI), normalization construction index (NDBI) and transformational vegetation index (TNDVI). It takes Qingpu District in Shanghai for example. Effective classification and information extraction are realized by using multi-temporal Landsat5 TM images from the year 1987 to 2007. It combines available ancillary geographical data, field survey data and statistical yearbook data to verify the analysis results, and then analyzes profoundly area variation trend of each classification and relative proportion during these years. Meanwhile, multi-temporal change monitoring results are used for the temporal and spatial variation analysis of water resources information, combining with existing relevant data of water quality. On the basis of buffer analysis for water quality and land use/cover in city-level water quality monitoring stations of Qingpu District, a correlation coefficient matrix has been calculated to analyze the relevance between land resources changes and water resources. In conclusion, the scale of urban area and water area are the primary driving force factors of LUCC, which also have an effect on water resource change of Qingpu District. This research represents the application of image recognition technology in the spatio-temporal changes of environment monitoring, and how to carry on deep analysis combined with various non-spatial data. It also provides objective reference about how to protect and improve water quality by controlling land use allocation in water source protection zones.

Citation Download Citation

Yi Lin, Bing Liu, Yuan Lu, and Feng Xie "Correlating analysis on spatio-temporal variation of LUCC and water resources based on remote sensing data", Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 91580Q (14 May 2014); https://doi.org/10.1117/12.2063843

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