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
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.
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.
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
1990-10-08;
Landsat5 TM
2000-09-17;
B1~B5
P119/R039
2010-10-31
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①
BAI
用于检测人工建筑面
BAI=
MNDWI
用于增强水体和其他地物的区别
MNDWI=
NDVI
用于增强植被和其他地物的区别
NDVI=
NDBI
对于城镇用地信息有较好的检测效果
NDBI=
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=
IBI
增强了不透水面特征并且有效抑制了背景噪声
IBI=
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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