A study of urban area extraction with the modified human settlement index

doi:10.6046/gtzyyg.2016.04.20

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Abstract

Urban areas extraction at regional and global scales remains a challenge. To map urban areas using DMSP-OLS nighttime light data is limited due to the saturation of data values, especially in urban cores. Different nighttime facula sizes lead to different degrees of light overflow, which causes difficulty for quantitative analysis. Vegetation-rich areas are selected to avoid the impact of bare soil when visible-near infrared image is used to map urban. To solve the problems above, this paper proposes modified human settlement index (MHSI) on the basis of human settlement index (HSI), which is composed of DMSP-OLS nighttime light data and visible-near infrared image. The MHSI has been tested in China and USA and testified by using the China city statistical data and USA NLCD land cover data. The results indicate that MHSI can overcome the overflow problem effectively and discriminate urban areas from other feature types such as bare soil, water and vegetable. MHSI can extract the regional or global city areas completely, and the accuracy is better than that of HSI and MODIS land cover data sets.

Keywords subalpine forest vegetation hyperspectral remote sensing spectral similarity upper reaches of the Minjiang River

TP751.1

Issue Date: 20 October 2016

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	DAI Xiaoai
	JIA Hujun
	ZHANG Xiaoxue
	WU Fenfang
	GUO Shouheng
	YANG Wunian
	YANG Ye

Cite this article:

DAI Xiaoai,JIA Hujun,ZHANG Xiaoxue, et al. A study of urban area extraction with the modified human settlement index[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(4): 127-134.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.04.20 OR https://www.gtzyyg.com/EN/Y2016/V28/I4/127

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