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Remote Sensing for Land & Resources    2020, Vol. 32 Issue (2) : 241-250     DOI: 10.6046/gtzyyg.2020.02.31
Remote sensing monitoring of impervious surface percentage in Hangzhou during 1990—2017
Yuting YANG1, Hailan CHEN2, Jiaqi ZUO2()
1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
2. Bazhong Bureau of Natural Resources and Planning,Bazhong 636000, China
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The impervious surface percentage is an important indicator of regional urbanization and ecological environment changes. The spatial and temporal distribution of impervious surface percentage can reveal the current and future development potential of the city, and provide a reference for urban environmental protection and green sustainable development. In this paper, Hangzhou was selected as the study area, and one Sentinel-2B satellite image was used to extract the impervious surface percentage as reference data. Based on the four-phase Landsat satellite imagery, the authors used the random forest algorithm to invert the 30 m spatial resolution impervious surface percentage datasets from 1990 to 2017 in Hangzhou. The accuracy verification results show that the mean absolute error is from 6.3% to 6.7%, and the root mean square error is from 13.40% to 14.25%, indicating that the inversion model has great accuracy and can accurately reflect the spatial distribution of the impervious surface. Based on the impervious surface weighted mean center, standard deviation ellipse and landscape pattern index, the authors analyzed the spatial and temporal patterns of impervious surface in Hangzhou. The results are as follows: The impervious surface percentage in Hangzhou was increasing from 1990 to 2017, and the annual average growing of impervious surface percentage was the fastest from 2010 to 2017, mainly concentrated in Yuhang and Xiaoshan; Due to the unbalanced development of Hangzhou between 1990 and 2017, the impervious surface weighting mean centre moved to northeast at first, then moved to south, and finally moved to north; The northwest-southeast profile was the main direction of urban growth and the gathering trend was relatively stable in Hangzhou; The change of landscape pattern shows that the impervious landscapes of all types were increasing, and were distributed in a balanced trend; The natural surface, medium density and super high density impervious landscapes became less aggregated and increasingly fragmented; The aggregation of the impervious landscapes of all types was relatively stable, the highest degree of aggregation was the natural surface, and the lowest was the medium density impervious landscape.

Keywords impervious surface      change detection      time series      Hangzhou      random forest     
:  TP79  
Corresponding Authors: Jiaqi ZUO     E-mail:
Issue Date: 18 June 2020
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Yuting YANG
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Jiaqi ZUO
Cite this article:   
Yuting YANG,Hailan CHEN,Jiaqi ZUO. Remote sensing monitoring of impervious surface percentage in Hangzhou during 1990—2017[J]. Remote Sensing for Land & Resources, 2020, 32(2): 241-250.
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Fig.1  Image of study area combined with Landsat 8 B5(R),B4(G),B3(B) in 2017
数据类型 采集时间 采用波段 轨道号
Landsat5 TM 2000-09-17; B1~B5 P119/R039
Landsat8 OLI 2017-11-03 B2~B6 P119/R039
Sentinel-2B 2017-10-31 B2~B4,B8 R089
Tab.1  The images used in the research
光谱指数 指数作用 表达式
NDBI 对于城镇用地信息有较好的检测效果 NDBI=MIR-NIRMIR+NIR
SAVI 考虑了土壤亮度背景,能够增强不透水面和植被的区分,对于城市内植被的提取具有良好的效果。 SAVI=1.5(NIR-RED)NIR+RED+0.5
IBI 增强了不透水面特征并且有效抑制了背景噪声 IBI=(NDBI-SAVI+MNDWI2)(NDBI+SAVI+MNDWI2)
Tab.2  The spectral index
Fig.2  Selection the pixels with constant impervious surface percentage from 1990 to 2017
类型 不透水面 其他 总和
不透水面 420 39 459
其他 37 435 472
总和 457 474 931
总体精度=91.84% Kappa=0.837
Tab.3  The classification of sentinel-2B image in 2017
Fig.3  ISP reference data extracted from Sentinel-2B image in 2017
误差 1990年 2000年 2010年 2017年
MBE -0.8 0.7 0.2 -0.7
MAE 6.7 6.6 6.4 6.3
RMSE 14.3 14.0 13.9 13.4
Tab.4  Errors of different years(%)
Fig.4  The impervious surface percentage in Hangzhou from 1990 to 2017
时期 增长总面积 年均增长面积
1990—2000年 607.72 60.772
2000—2010年 977.23 97.723
2010—2017年 725.91 103.702
Tab.5  Growth of impervious surface percentage in different periods(km2)
Fig.5  Impervious surface weighted mean centres in different years
年份 长轴/m 短轴/m 方位角/(°) 长短轴比
1990年 24 164.634 17 135.538 100.451 1.410
2000年 25 338.331 17 502.960 94.155 1.448
2010年 26 426.510 18 208.927 96.039 1.451
2017年 26 449.593 18 757.402 97.937 1.410
Tab.6  SDE parameters of impervious surface maps from 1990 to 2017
Fig.6  SDEs of impervious surface in different years
Fig.7  The landscape pattern changes of impervious surface in Hangzhou from 1990 to 2017
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