DocumentCode :
2575976
Title :
Extraction and application of impervious surface area in Yellow River Delta
Author :
Mingjie, Li ; Xiyong, Hou ; Mingming, Zhu ; Chunyan, Shen
Author_Institution :
Yantai Inst. of Coastal Zone Res., Chinese Acad. of Sci., Yantai, China
Volume :
2
fYear :
2010
fDate :
28-31 Aug. 2010
Firstpage :
634
Lastpage :
637
Abstract :
Impervious surfaces as a special factor mainly made by human not only can indicate changes of LUCC and the Urbanization, and is also a good indicator of environmental quality. In this paper, we took the TM image data of the Yellow River Delta (YRD) region especially the Dongying city in 2009 as study area, used the Normalized Mixing Spectral Analysis Model (NSMA) and aided the product of maximum likelihood classify to obtain the high accuracy map of percent impervious surface (PIS). In addition, the urban (town) were distinguished by setting appropriate threshold according to the PIS and the investigation data. The results indicated that, the combination of the NSMA and the maximum likelihood method was effective to differentiate alkaline land from build-up area; In the whole study area of YRD, the non-urban (non-town) area was an absolutely dominant type with the 92% percent area, while in the area with the PIS value of grater than 10%, the percents area of the urban (town) were 63%, specifically to the low, middle, high development levels area, each was 13%, 22%, 28% in sequence; The relationships between PIS and LST, ET revealed that the higher the PIS, the higher the LST while the lower the ET and there would be a clearly positive (negative) exponential relationships between the PIS and the LST (ET). And the study on impervious surface would be useful to further research on its sprawl and quantitative relationships between the PIS and the other land surface parameters.
Keywords :
geomorphology; geophysical techniques; remote sensing; rivers; AD 2009; Dongying city; LUCC; TM image data; Yellow River delta; alkaline land; build-up area; impervious surface area; land surface parameters; maximum likelihood classification; maximum likelihood method; normalized mixing spectral analysis model; percent impervious surface; remote sensing; Biological system modeling; Irrigation; Planning; Sensors; Impervious Surfaces; Land surface parameters; Maximum likelihood classify; Normalized Spectral Mixed Analysis Model; Relationship; Yellow River Delta;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-8514-7
Type :
conf
DOI :
10.1109/IITA-GRS.2010.5602323
Filename :
5602323
Link To Document :
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