Journal of Geo-information Science ›› 2021, Vol. 23 ›› Issue (1): 171-186.doi: 10.12082/dqxxkx.2021.200236

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Cascade Extraction of Impervious Surface Information based on the Signature of Temporal Spectrum

SHUAI Yanmin1,2,3(), MA Xianwei1,*(), QU Ge1, SHAO Congying1, LIU Tao2,3, LIU Shoumin4, HUANG Huabing5, GU Lingxiao1, LATIPA Tuerhanjiang2,3, LIANG Ji6, LI Ling1   

  1. 1. College of Surveying and Mapping and Geographic Science, Liaoning Technical University, Fuxin 123000, China
    2. Research Center of Green Silk Road, Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences, Urumqi 830011, China
    3. Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
    4. Science and Technology Bureau of Heze Shan County, Heze 274300, China
    5. School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China
    6. National-Local Joint Engineering Laboratory of Geo-Spatial Information Technology,Hunan University of Science and Technology, Xiangtan 411201, China
  • Received:2020-05-03 Revised:2020-07-03 Online:2021-01-25 Published:2021-03-25
  • Contact: MA Xianwei;
  • Supported by:
    Liaoning Revitalization Talents Program(XLYC1802027);One Hundred Talents Program of the Chinese Academy of Sciences(Y938091);One Hundred Talents Program of the Chinese Academy of Sciences(Y674141001);Hunan Natural Science Foundation Project(2018JJ2116);National Natural Science Foundation of China(42071351);National Key Research & Development Program of China(2020YFA0608501);Project supported discipline innovation team of Liaoning Technical University(LNTU20TD-23)


Impervious surface acts as an important technical indicator of urban characterization and regional urbanization dynamics. Its location, patch size, and spatial distribution are widely used by the communities of surface hydrothermal cycle and energy balance. However, traditional methods usually adopt a single time-phase image to retrieval the impervious surface information without considering the rich information implied in multiple time-phase images. Therefore, this paper presented a method to extract the impervious surface by integrating features in time-series images within a year. We generated the Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), and Normalized Difference Built-up Index (NDBI) from time-series Landsat-8 OLI surface reflectance images to analyze the intra-annual features of multi-temporal spectrum curves between typical objects and summarize principles in describing changes of impervious surface from multiple time phases. We also combined the prior knowledge of effective impervious surface information to improve the extraction accuracy. Finally, we used field survey data and the 30-m impervious map generated from the 2-m GF-1 image by screen digitalization to validate the accuracy of results using three combinations of images as input (i.e., single time-phase image, four images of seasons, and multi-temporal images). The results show that the impervious surface extracted from the single-phase image had the lowest accuracy, while the extraction accuracy using multi-temporal images was the highest with an overall accuracy of 93.66% and a Kappa coefficient of 0.81. The extraction accuracy using the four images of seasons was in the middle. Furthermore, the presented method showed potential advantages of effectively identifying impervious surfaces in rural areas. Our method provides a new idea for the impervious surface extraction through integrating temporal spectral features of impervious surface.

Key words: time-series features, impervious surface, prior knowledge, cascade retrieval, accuracy comparison, Landsat OLI, spectrum characteristic, remote sensing index