Methods and application of impervious surface information extraction in plain river network based on multi-temporal landsat imagery

doi:10.13474/j.cnki.11-2246.2020.0019

Abstract

Abstract: Impervious surface is recognized as the key indicator of the urban ecological environment. To improve the accuracy of the impervious surface information extraction in plain river network area, according to analysis of the seasonal spectral characteristics of the pixels in the rapid urbanization area of North Jiangsu derived from the multi-temporal Landsat imagery, this study proposes a new decision tree model based on the NDVI, NDWI and NDBI time-series datasets. Using the novel established decision tree model, the change of the impervious surface is also analyzed. The result shows that the Kappa coefficient and the overall accuracy of the impervious surface classify are both larger than 0.85, implying that the method is potentially useful for the detection of the impervious surface. With the process of the urbanization, the region has undergone a rapid expansion of the impervious surface with a increasing rate of 7.0 km²/year. In addition, a more rapid development trend towards the southeastern direction has been found during the period 2005-2016. Our investigations could provide scientific basis for the urban ecological environment research and provide a technical support for the impervious surface extraction in other plain river network area.

Key words: multi-temporal, Landsat, impervious surface, remote sensing information extraction, plain river network area

CLC Number:

P237

ZHOU Feng, LIAO Yubing, LI Na. Methods and application of impervious surface information extraction in plain river network based on multi-temporal landsat imagery[J]. Bulletin of Surveying and Mapping, 2020, 0(1): 94-97,106.

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