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Remote Sensing for Land & Resources    2020, Vol. 32 Issue (4) : 163-171     DOI: 10.6046/gtzyyg.2020.04.21
Using SVM classify Landsat image to analyze the spatial and temporal characteristics of main urban expansion analysis in Democratic People’s Republic of Korea
WANG Xiaolong1,2,3(), YAN Haowen1,2,3(), ZHOU Liang1,2,3, ZHANG Liming1,2,3, DANG Xuewei1,2,3
1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China
3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
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The study of the change of main urban construction land that is almost blank in the wide area space-time scale can make up for the blank in the wide area space-time scale in the study area. The construction land of six major cities was extracted by using SVM classification method based on the Landsat TM/ETM+/OLI data of long time series from 1990 to 2018 in the study area. The quantitative analysis was made on the landscape metric as well as annual increase and annual growth rate urban development mode. The results show that the SVM method can effectively extract the construction land, with the average of overall accuracy higher than 90% and Kappa more than 0.87. The area expansion of each urban area had reached 1.2~1.4 times and was growing continuously from 1990 to 2018. The annual growth that the largest among the six cities of Pyongyang has reached 1.15 km2, while the growth rate of Wosan has a small fluctuation range. And the growth rate that the largest among the six cities of Humhang has reached 2.74% in the recent period. The expansion of six cities in the study area is concentrated in the flat terrain,and the main urban area is distributed along the river or the coast, with the expansion mode of filling type and filling type. In general, its urbanization process is on the rise. This study lays the foundation for the ecological environment protection and the urban expansion and provides reference for the relevant scientific research in the study area.

Keywords SVM      urbanization      construction land      landscape metrics      Democratic People’s Republic of Korea     
:  TP79  
Corresponding Authors: YAN Haowen     E-mail:;
Issue Date: 23 December 2020
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Xiaolong WANG
Haowen YAN
Liang ZHOU
Liming ZHANG
Xuewei DANG
Cite this article:   
Xiaolong WANG,Haowen YAN,Liang ZHOU, et al. Using SVM classify Landsat image to analyze the spatial and temporal characteristics of main urban expansion analysis in Democratic People’s Republic of Korea[J]. Remote Sensing for Land & Resources, 2020, 32(4): 163-171.
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Fig.1  Location of study area
城市 1990年 2000年 2010年 2018年
清津 TM,1991 ETM+ TM OLI
咸兴 TM ETM+,2002 TM,2011 OLI
平壤 TM ETM+,2001 TM OLI
沙里院 TM ETM+,2001 TM OLI
Tab.1  Data sources employed in this study
指数 表达式 描述
NP NP=ni
PD PD=niA(1000)(100)
LPI LPI=max(aij)j=1nA(100)
PLAND PLAND=j=1naijA(100) 计算某一斑块类型占整个景观面积的相对比例
LSI LSI=0.25k=1meik*Aor=0.25E*A
Tab.2  Detailed information on the landscape indices implemented in Fragstats 4.2
城市 1990年 2000年 2010年 2018年
OA/% Kappa OA/% Kappa OA/% Kappa OA/% Kappa
清津 92.23 0.88 91.07 0.87 92.15 0.89 92.65 0.88
咸兴 90.20 0.88 92.80 0.89 92.58 0.91 92.88 0.90
江界 90.76 0.89 92.36 0.89 92.20 0.90 91.76 0.90
平壤 91.61 0.90 91.42 0.89 93.08 0.91 93.00 0.91
沙里院 93.46 0.88 91.48 0.88 91.08 0.87 92.99 0.91
元山 93.36 0.90 90.46 0.87 90.39 0.88 93.30 0.90
平均值 91.94 0.89 91.60 0.88 91.91 0.89 92.76 0.90
Tab.3  Classification accuracy of main cities in the study area
指标 城市 1990—
AI/km2 清津 0.02 0.63 0.04 0.17 0.22
咸兴 0.23 0.01 0.58 0.20 0.26
江界 0.07 0.09 0.05 0.51 0.18
平壤 0.01 0.86 1.15 0.03 0.51
沙里院 0.02 0.07 0.04 0.06 0.05
元山 0.08 0.04 0.10 0.06 0.07
AGR/% 清津 0.13 3.18 0.17 0.86 1.09
咸兴 1.30 0.04 2.74 1.02 1.28
江界 1.24 2.89 0.33 1.85 1.58
平壤 3.18 2.97 1.27 1.00 2.11
沙里院 0.03 1.89 2.08 1.08 1.27
元山 0.82 2.31 1.20 0.82 1.29
Tab.4  Annual increase and annual growth rate of construction land from 1990 to 2018
Fig.2  Relative spatial growth rate of the main cities in the study area
Fig.3  Spatial distribution of urban expansion in main cities in the study area from 1990 to 2018
Fig.4  Landscape metrics of construction land in Chongjin, Humhang, Kanggye, Pyongyang, Sariwon and Wosan from 1990 to 2018
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