{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T18:02:26Z","timestamp":1770141746226,"version":"3.49.0"},"reference-count":54,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T00:00:00Z","timestamp":1663977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["52109040"],"award-info":[{"award-number":["52109040"]}]},{"name":"National Natural Science Foundation of China","award":["51739009"],"award-info":[{"award-number":["51739009"]}]},{"name":"National Natural Science Foundation of China","award":["2021M702950"],"award-info":[{"award-number":["2021M702950"]}]},{"name":"National Natural Science Foundation of China","award":["222102320025"],"award-info":[{"award-number":["222102320025"]}]},{"name":"National Natural Science Foundation of China","award":["22B570003"],"award-info":[{"award-number":["22B570003"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["52109040"],"award-info":[{"award-number":["52109040"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["51739009"],"award-info":[{"award-number":["51739009"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2021M702950"],"award-info":[{"award-number":["2021M702950"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["222102320025"],"award-info":[{"award-number":["222102320025"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["22B570003"],"award-info":[{"award-number":["22B570003"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific and Technological Projects of Henan Province","award":["52109040"],"award-info":[{"award-number":["52109040"]}]},{"name":"Scientific and Technological Projects of Henan Province","award":["51739009"],"award-info":[{"award-number":["51739009"]}]},{"name":"Scientific and Technological Projects of Henan Province","award":["2021M702950"],"award-info":[{"award-number":["2021M702950"]}]},{"name":"Scientific and Technological Projects of Henan Province","award":["222102320025"],"award-info":[{"award-number":["222102320025"]}]},{"name":"Scientific and Technological Projects of Henan Province","award":["22B570003"],"award-info":[{"award-number":["22B570003"]}]},{"name":"Key Scientific Research Project in Colleges and Universities of Henan Province of China","award":["52109040"],"award-info":[{"award-number":["52109040"]}]},{"name":"Key Scientific Research Project in Colleges and Universities of Henan Province of China","award":["51739009"],"award-info":[{"award-number":["51739009"]}]},{"name":"Key Scientific Research Project in Colleges and Universities of Henan Province of China","award":["2021M702950"],"award-info":[{"award-number":["2021M702950"]}]},{"name":"Key Scientific Research Project in Colleges and Universities of Henan Province of China","award":["222102320025"],"award-info":[{"award-number":["222102320025"]}]},{"name":"Key Scientific Research Project in Colleges and Universities of Henan Province of China","award":["22B570003"],"award-info":[{"award-number":["22B570003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Flood risk assessment is an important tool for disaster warning and prevention. In this study, an integrated approach based on a D-number-improved analytic hierarchy process (D-AHP) and a self-organizing map (SOM) clustering algorithm are proposed for urban flooding risk assessment. The urban flood inundation model and geographic information system (GIS) technology were used to quantify the assessment indices of urban flood risk. The D-AHP approach was adopted to determine the weights of the indices, which effectively makes up for the shortcomings of the AHP in dealing with uncertain evaluation information (such as fuzzy and incomplete information). In addition, the SOM clustering algorithm was applied to determine the flood risk level. It is a data-driven approach that avoids the subjective determination of a flood risk classification threshold. The proposed approach for flood risk assessment was implemented in Zhengzhou, China. The flood risk was classified into five levels: highest risk, higher risk, medium risk, lower risk, and the lowest risk. The proportion of the highest risk areas was 9.86%; such areas were mainly distributed in the central and eastern parts of the Jinshui District, the eastern part of the Huiji District, and the northeastern part of the Guancheng District, where there were low terrain and serious waterlogging. The higher risk areas accounted for 24.26% of the study area, and were mainly distributed in the western and southern parts of the Jinshui District, the southern part of the Huiji District, the middle and eastern parts of the Zhongyuan District, the northeastern part of the Erqi District, and the northwestern part of the Guancheng District, which consisted of economically developed areas of dense population and buildings, matching well with historical flooding events. To verify the effectiveness of the proposed approach, traditional approaches for risk assessment were compared. The comparison indicated that the proposed approach is more reasonable and accurate than the traditional approaches. This study showed the potential of a novel approach to flood risk assessment. The results can provide a reference for urban flood management and disaster reduction in the study area.<\/jats:p>","DOI":"10.3390\/rs14194777","type":"journal-article","created":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T03:34:17Z","timestamp":1664163257000},"page":"4777","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Urban Flood Risk Assessment in Zhengzhou, China, Based on a D-Number-Improved Analytic Hierarchy Process and a Self-Organizing Map Algorithm"],"prefix":"10.3390","volume":"14","author":[{"given":"Zening","family":"Wu","sequence":"first","affiliation":[{"name":"Yellow River Laboratory, Zhengzhou University, Zhengzhou 450001, China"}]},{"given":"Wanjie","family":"Xue","sequence":"additional","affiliation":[{"name":"Yellow River Laboratory, Zhengzhou University, Zhengzhou 450001, China"}]},{"given":"Hongshi","family":"Xu","sequence":"additional","affiliation":[{"name":"Yellow River Laboratory, Zhengzhou University, Zhengzhou 450001, China"}]},{"given":"Denghua","family":"Yan","sequence":"additional","affiliation":[{"name":"China Institute of Water Resources and Hydropower Research, Beijing 100038, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0057-455X","authenticated-orcid":false,"given":"Huiliang","family":"Wang","sequence":"additional","affiliation":[{"name":"Yellow River Laboratory, Zhengzhou University, Zhengzhou 450001, China"}]},{"given":"Wenchao","family":"Qi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e2019EF001382","DOI":"10.1029\/2019EF001382","article-title":"The Role of Urban Growth in Resilience of Communities Under Flood Risk","volume":"8","author":"Hemmati","year":"2020","journal-title":"Earth Future"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Nguyen, H.D., Fox, D., Dang, D.K., Pham, L.T., Viet Du, Q.V., Nguyen, T.H.T., Dang, T.N., Tran, V.T., Vu, P.L., and Nguyen, Q. (2021). Predicting Future Urban Flood Risk Using Land Change and Hydraulic Modeling in a River Watershed in the Central Province of Vietnam. Remote Sens., 13.","DOI":"10.3390\/rs13020262"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"127121","DOI":"10.1016\/j.jhydrol.2021.127121","article-title":"The analysis of urban flood risk propagation based on the modified susceptible infected recovered model","volume":"603","author":"Wang","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.scitotenv.2017.11.358","article-title":"The changing pattern of urban flooding in Guangzhou, China","volume":"622","author":"Huang","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s13201-018-0881-9","article-title":"Flood risk and adaptation in Indian coastal cities: Recent scenarios","volume":"9","author":"Dhiman","year":"2019","journal-title":"Appl. Water"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zhao, L., Zhang, T., Fu, J., Li, J., Cao, Z., and Feng, P. (2021). Risk Assessment of Urban Floods Based on a SWMM-MIKE21-Coupled Model Using GF-2 Data. Remote Sens., 13.","DOI":"10.3390\/rs13214381"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1016\/j.scitotenv.2019.01.004","article-title":"Urban flood risk assessment using storm characteristic parameters sensitive to catchment-specific drainage system","volume":"659","author":"Zhou","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Manfreda, S., Samela, C., Refice, A., Tramutoli, V., and Nardi, F. (2018). Advances in Large-Scale Flood Monitoring and Detection. Hydrology, 5.","DOI":"10.3390\/hydrology5030049"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Albano, R., Samela, C., Cr\u0103ciun, I., Manfreda, S., Adamowski, J., Sole, A., Sivertun, \u00c5., and Ozunu, A. (2020). Large Scale Flood Risk Mapping in Data Scarce Environments: An Application for Romania. Water, 12.","DOI":"10.3390\/w12061834"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e12541","DOI":"10.1111\/jfr3.12541","article-title":"A digital elevation model based method for a rapid estimation of flood inundation depth","volume":"121","author":"Manfreda","year":"2019","journal-title":"J. Flood Risk Manag."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Kablan, M.K.A., Dongo, K., and Coulibaly, M. (2017). Assessment of Social Vulnerability to Flood in Urban Cote d\u2019Ivoire Using the MOVE Framework. Water, 9.","DOI":"10.3390\/w9040292"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.habitatint.2016.11.008","article-title":"Government support, social capital and adaptation to urban flooding by residents in the Pearl River Delta area, China","volume":"59","author":"Liang","year":"2017","journal-title":"Habitat Int."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.ijdrr.2016.09.006","article-title":"Social vulnerability indicators in disasters: Findings from a systematic review","volume":"22","author":"Fatemi","year":"2017","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.enggeo.2009.12.006","article-title":"Urban flood hazard zoning in Tucuman Province, Argentina, using GIS and multicriteria decision analysis","volume":"111","author":"Fernandez","year":"2010","journal-title":"Eng. Geol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11518-006-0151-5","article-title":"Decision making-the analytic hierarchy and network processes (AHP\/ANP)","volume":"13","author":"Saaty","year":"2004","journal-title":"J. Syst. Sci. Syst. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1007\/s12517-018-3933-4","article-title":"Geographic information system and AHP-based flood hazard zonation of Vaitarna basin, Maharashtra, India","volume":"11","author":"Das","year":"2018","journal-title":"Arab. J. Geosci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Karymbalis, E., Andreou, M., Batzakis, D.-V., Tsanakas, K., and Karalis, S. (2021). Integration of GIS-Based Multicriteria Decision Analysis and Analytic Hierarchy Process for Flood-Hazard Assessment in the Megalo Rema River Catchment (East Attica, Greece). Sustainability, 13.","DOI":"10.3390\/su131810232"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"125275","DOI":"10.1016\/j.jhydrol.2020.125275","article-title":"Flood susceptibility mapping with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory","volume":"590","author":"Nachappa","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Duan, C., Zhang, J., Chen, Y., Lang, Q., Zhang, Y., Wu, C., and Zhang, Z. (2022). Comprehensive Risk Assessment of Urban Waterlogging Disaster Based on MCDA-GIS Integration: The Case Study of Changchun, China. Remote Sens., 14.","DOI":"10.3390\/rs14133101"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"124696","DOI":"10.1016\/j.jhydrol.2020.124696","article-title":"Assessment of flash flood risk based on improved analytic hierarchy process method and integrated maximum likelihood clustering algorithm","volume":"584","author":"Lin","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"102103","DOI":"10.1016\/j.scs.2020.102103","article-title":"Inundation risk assessment of metro system using AHP and TFN-AHP in Shenzhen","volume":"56","author":"Lyu","year":"2020","journal-title":"Sust. Cities Soc."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"133936","DOI":"10.1016\/j.scitotenv.2019.133936","article-title":"Hydro-meteorological risk assessment methods and management by nature-based solutions","volume":"696","author":"Sahani","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.jhydrol.2014.03.064","article-title":"A comparative study of fuzzy logic systems approach for river discharge prediction","volume":"514","author":"Jayawardena","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1007\/s11069-019-03803-0","article-title":"Flood risk assessment in Quzhou City (China) using a coupled hydrodynamic model and fuzzy comprehensive evaluation (FCE)","volume":"100","author":"Geng","year":"2020","journal-title":"Nat. Hazards"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"127061","DOI":"10.1016\/j.jhydrol.2021.127061","article-title":"Flood prioritization of basins based on geomorphometric properties using principal component analysis, morphometric analysis and Redvan\u2019s priority methods: A case study of Hars, it River basin","volume":"603","author":"Ghasemlounia","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.5194\/nhess-17-1541-2017","article-title":"Construction of an integrated social vulnerability index in urban areas prone to flash flooding","volume":"17","year":"2017","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.wace.2017.10.002","article-title":"Flood vulnerability, local perception and gender role judgment using multivariate analysis: A problem-based \u201cparticipatory action to Future Skill Management\u201d to cope with flood impacts","volume":"18","author":"Rakib","year":"2017","journal-title":"Weather Clim. Extremes"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Gigovic, L., Pamucar, D., Bajic, Z., and Drobnjak, S. (2017). Application of GIS-Interval Rough AHP Methodology for Flood Hazard Mapping in Urban Areas. Water, 9.","DOI":"10.3390\/w9060360"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.1016\/j.scitotenv.2018.01.138","article-title":"Flood risk assessment in metro systems of mega-cities using a GIS-based modeling approach","volume":"626","author":"Lyu","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Cai, S., Fan, J., and Yang, W. (2021). Flooding Risk Assessment and Analysis Based on GIS and the TFN-AHP Method: A Case Study of Chongqing, China. Atmosphere, 12.","DOI":"10.3390\/atmos12050623"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.eswa.2013.07.018","article-title":"Supplier selection using AHP methodology extended by D numbers","volume":"41","author":"Deng","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1214\/aoms\/1177698950","article-title":"Upper and lower probabilities induced by a multivalued mapping","volume":"38","author":"Dempster","year":"1967","journal-title":"Ann. Math. Stat."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Shafer, G. (1976). A Mathematical Theory of Evidence, Princeton University Press.","DOI":"10.1515\/9780691214696"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"15547","DOI":"10.1109\/ACCESS.2019.2893884","article-title":"A New Method to Identify Incomplete Frame of Discernment in Evidence Theory","volume":"7","author":"Sun","year":"2019","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.inffus.2020.02.003","article-title":"Multi-classifier information fusion in risk analysis","volume":"60","author":"Pan","year":"2020","journal-title":"Inf. Fusion"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.eswa.2015.09.006","article-title":"A hybrid fuzzy evaluation method for curtain grouting efficiency assessment based on an AHP method extended by D numbers","volume":"44","author":"Fan","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1007\/s00500-017-2993-9","article-title":"D-AHP method with different credibility of information","volume":"23","author":"Deng","year":"2019","journal-title":"Soft Comput."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1016\/j.jhydrol.2018.06.060","article-title":"Urban flooding risk assessment based on an integrated k-means cluster algorithm and improved entropy weight method in the region of Haikou, China","volume":"563","author":"Xu","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_39","first-page":"7","article-title":"Survey on K-Means Clustering Algorithm","volume":"55","author":"Yang","year":"2019","journal-title":"Comput. Eng. Appl."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/BF00337288","article-title":"Self-organized formation of topologically correct feature maps","volume":"43","author":"Kohonen","year":"1982","journal-title":"Biol. Cybern."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"125581","DOI":"10.1016\/j.jhydrol.2020.125581","article-title":"Spatiotemporal variation of water pollution near landfill site: Application of clustering methods to assess the admissibility of LWPI","volume":"591","author":"Baghanam","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/j.jhydrol.2019.05.043","article-title":"Integrated urban flood vulnerability assessment using local spatial dependence-based probabilistic approach","volume":"575","author":"Chen","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Wu, Z., Shen, Y., and Wang, H. (2019). Assessing Urban Areas\u2019 Vulnerability to Flood Disaster Based on Text Data: A Case Study in Zhengzhou City. Sustainability, 11.","DOI":"10.3390\/su11174548"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1061\/(ASCE)HE.1943-5584.0000577","article-title":"Increasing Stream Geomorphic Stability Using Storm Water Control Measures in a Densely Urbanized Watershed","volume":"17","author":"Tillinghast","year":"2012","journal-title":"J. Hydrol. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.jenvman.2016.01.036","article-title":"Modeling flood reduction effects of low impact development at a watershed scale","volume":"171","author":"Ahiablame","year":"2016","journal-title":"J. Environ. Manag."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.scitotenv.2016.02.025","article-title":"Approach for evaluating inundation risks in urban drainage systems","volume":"553","author":"Zhu","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Akhter, M.S., and Hewa, G.A. (2016). The Use of PCSWMM for Assessing the Impacts of Land Use Changes on Hydrological Responses and Performance of WSUD in Managing the Impacts at Myponga Catchment, South Australia. Water, 8.","DOI":"10.3390\/w8110511"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Munir, B.A., Ahmad, S.R., and Hafeez, S. (2020). Integrated Hazard Modeling for Simulating Torrential Stream Response to Flash Flood Events. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9010001"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Duan, C., Zheng, X., Jin, L., Chen, Y., Li, R., and Yang, Y. (2022). Study on the Remote Sensing Spectral Method for Disaster Loss Inversion in Urban Flood Areas. Water, 14.","DOI":"10.3390\/w14142165"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3517104","DOI":"10.1155\/2020\/3517104","article-title":"Combination of D-AHP and Grey Theory for the Assessment of the Information Security Risks of Smart Grids","volume":"2020","author":"Dong","year":"2020","journal-title":"Math. Probl. Eng."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Kohonen, T., Schroeder, M.R., and Huang, T.S. (1997). Self-Organizing Maps, Springer.","DOI":"10.1007\/978-3-642-97966-8"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"127082","DOI":"10.1016\/j.jhydrol.2021.127082","article-title":"Using a linear discriminant analysis (LDA)-based nomenclature system and self-organizing maps (SOM) for spatiotemporal assessment of groundwater quality in a coastal aquifer","volume":"603","author":"Amiri","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"125655","DOI":"10.1016\/j.jhydrol.2020.125655","article-title":"Explore training self-organizing map methods for clustering high-dimensional flood inundation maps","volume":"595","author":"Chang","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Sidek, L.M., Chua, L.H.C., Azizi, A.S.M., Basri, H., Jaafar, A.S., and Moon, W.C. (2021). Application of PCSWMM for the 1-D and 1-D\u20132-D Modeling of Urban Flooding in Damansara Catchment, Malaysia. Appl. Sci., 11.","DOI":"10.3390\/app11199300"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/19\/4777\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:38:43Z","timestamp":1760143123000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/19\/4777"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,24]]},"references-count":54,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["rs14194777"],"URL":"https:\/\/doi.org\/10.3390\/rs14194777","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,24]]}}}