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Remote Sens. 2017, 9(7), 751; doi:10.3390/rs9070751

Influence of Ecological Factors on Estimation of Impervious Surface Area Using Landsat 8 Imagery

1,2
,
1,* and 1,2
1
Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Received: 25 May 2017 / Revised: 16 July 2017 / Accepted: 18 July 2017 / Published: 21 July 2017
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
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Abstract

Estimation of impervious surface area is important to the study of urban environments and social development, but surface characteristics, as well as the temporal, spectral, and spatial resolutions of remote sensing images, influence the estimation accuracy. To investigate the effects of regional environmental characteristics on the estimation of impervious surface area, we divided China into seven sub-regions based on climate, soil type, feature complexity, and vegetation phenology: arid and semi-arid areas, Huang-Huai-Hai winter wheat production areas, typical temperate regions, the Pearl River Delta, the middle and lower reaches of the Yangtze River, typical tropical and subtropical regions, and the Qinghai Tibet Plateau. Impervious surface area was estimated from Landsat 8 images of five typical cities, including Yinchuan, Shijiazhuang, Shenyang, Ningbo, and Kunming. Using the linear spectral unmixing method, impervious and permeable surface areas were determined at the pixel-scale based on end-member proportions. We calculated the producer’s accuracy, user’s accuracy, and overall accuracy to assess the estimation accuracy, and compared the accuracies among images acquired from different seasons and locations. In tropical and subtropical regions, vegetation canopies can confound the identification of impervious surfaces and, thus, images acquired in winter, early spring, and autumn are most suitable; estimations in the Pearl River Delta, the middle and lower reaches of the Yangtze River are influenced by soil, vegetation phenology, vegetation canopy, and water, and images acquired in spring, summer, and autumn provide the best results; in typical temperate areas, images acquired from spring to autumn are most effective for estimations; in winter wheat-growing areas, images acquired throughout the year are suitable; and in arid and semi-arid areas, summer and early autumn, during which vegetation is abundant, are the optimal seasons for estimations. Knowledge of optimal time frames, multi-source data, and intelligent algorithms should be integrated to reduce spectral confusion and improve the estimation of impervious surface area from Landsat 8 OLI imagery. View Full-Text
Keywords: ecological regionalization; pixel unmixing; Landsat 8; China; impervious surfaces ecological regionalization; pixel unmixing; Landsat 8; China; impervious surfaces
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Jia, Y.; Tang, L.; Wang, L. Influence of Ecological Factors on Estimation of Impervious Surface Area Using Landsat 8 Imagery. Remote Sens. 2017, 9, 751.

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