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Estimating 2009-2017 Impervious Surface Change in Gwadar, Pakistan Using the HJ-1A/B Constellation, GF-1/2 Data, and the Random Forest Algorithm
Bian Jinhu; Li Ainong; Zuo Jiaqi; Lei Guangbin; Zhang Zhengjian; Nan Xi
Corresponding AuthorLi, Ainong(ainongli@imde.ac.cn)
2019
Source PublicationISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
EISSN2220-9964
Volume8Issue:10Pages:443
SubtypeArticle
Contribution Rank1
AbstractThe China-Pakistan Economic Corridor (CPEC) is the flagship project of the Belt and Road Initiative. At the end of the CPEC, the Gwadar port on the Arabian Sea is being built quickly, providing an important economical route for the flow of Central Asia's natural resources to the world. Gwadar city is in a rapid urbanization process and will be developed as a modern, world-class port city in the near future. Therefore, monitoring the urbanization process of Gwadar at both high spatial and temporal resolution is vital for its urban planning, city ecosystem management, and the sustainable development of CPEC. The impervious surface percentage (ISP) is an essential quantitative indicator for the assessment of urban development. Through the integration of remote sensing images and ISP estimation models, ISP can be routinely and periodically estimated. However, due to clouds' influence and spatial-temporal resolution trade-offs in sensor design, it is difficult to estimate the ISP with both high spatial resolution and dense temporal frequency from only one satellite sensor. In recent years, China has launched a series of Earth resource satellites, such as the HJ (Huangjing, which means environment in Chinese)-1A/B constellation, showing great application potential for rapid Earth surface mapping. This study employs the Random Forest (RF) method for a long-term and fine-scale ISP estimation and analysis of the city of Gwadar, based on the density in temporal and multi-source Chinese satellite images. In the method, high spatial resolution ISP reference data partially covering Gwadar city was first extracted from the 1-2 meter (m) GF (GaoFen, which means high spatial resolution in Chinese)-1/2 fused images. An RF retrieval model was then built based on the training samples extracted from ISP reference data and multi-temporal 30-m HJ-1A/B satellite images. Lastly, the model was used to generate the 30-m time series ISP from 2009 to 2017 for the whole city area based on the HJ-1A/B images. Results showed that the mean absolute error of the estimated ISP was 6.1-8.1% and that the root mean square error (RMSE) of the estimation results was 12.82-15.03%, indicating the consistently high performance of the model. This study highlights the feasibility and potential of using multi-source Chinese satellite images and an RF model to generate long-term ISP estimations for monitoring the urbanization process of the key node city in the CPEC.
Keywordimpervious surface HJ-1A/B constellation GF-1/2 time series random forest China-Pakistan Economic Corridor (CPEC)
DOI10.3390/ijgi8100443
Indexed BySCI
WOS KeywordLAND-COVER CLASSIFICATION ; MAPPING URBAN AREAS ; TIME-SERIES ; SCALE ; INDEX ; IMPACT ; REGION ; MODIS ; CITY
Language英语
Funding Projectkey program of CAS[KFZD-SW-319-04] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDA19030303] ; National Natural Science Foundation of China[41701432] ; National Natural Science Foundation of China[41631180] ; National Natural Science Foundation of China[41571373] ; National Key Research and Development Program of China[2016YFA0600103] ; National Key Research and Development Program of China[2016YFC0500201-06] ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS[SDS-135-1708] ; CAS Light of West China Program ; Youth Innovation Promotion Association CAS[2019365]
WOS Research AreaPhysical Geography ; Remote Sensing
WOS SubjectGeography, Physical ; Remote Sensing
WOS IDWOS:000498398300018
Funding Organizationkey program of CAS ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS ; CAS Light of West China Program ; Youth Innovation Promotion Association CAS
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/33572
Collection数字山地与遥感应用中心
Corresponding AuthorLi Ainong
AffiliationChinese Acad Sci, Res Ctr Digital Mt & Remote Sensing Applicat, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Corresponding Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
Bian Jinhu,Li Ainong,Zuo Jiaqi,et al. Estimating 2009-2017 Impervious Surface Change in Gwadar, Pakistan Using the HJ-1A/B Constellation, GF-1/2 Data, and the Random Forest Algorithm[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(10):443.
APA Bian Jinhu,Li Ainong,Zuo Jiaqi,Lei Guangbin,Zhang Zhengjian,&Nan Xi.(2019).Estimating 2009-2017 Impervious Surface Change in Gwadar, Pakistan Using the HJ-1A/B Constellation, GF-1/2 Data, and the Random Forest Algorithm.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(10),443.
MLA Bian Jinhu,et al."Estimating 2009-2017 Impervious Surface Change in Gwadar, Pakistan Using the HJ-1A/B Constellation, GF-1/2 Data, and the Random Forest Algorithm".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.10(2019):443.
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