{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T17:36:33Z","timestamp":1770226593630,"version":"3.49.0"},"reference-count":85,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T00:00:00Z","timestamp":1693267200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41702357"],"award-info":[{"award-number":["41702357"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41801283"],"award-info":[{"award-number":["41801283"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["DD20190340"],"award-info":[{"award-number":["DD20190340"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["20210203016SF"],"award-info":[{"award-number":["20210203016SF"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["20230101373JC"],"award-info":[{"award-number":["20230101373JC"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Geological Survey project of China Geological Survey","award":["41702357"],"award-info":[{"award-number":["41702357"]}]},{"name":"Geological Survey project of China Geological Survey","award":["41801283"],"award-info":[{"award-number":["41801283"]}]},{"name":"Geological Survey project of China Geological Survey","award":["DD20190340"],"award-info":[{"award-number":["DD20190340"]}]},{"name":"Geological Survey project of China Geological Survey","award":["20210203016SF"],"award-info":[{"award-number":["20210203016SF"]}]},{"name":"Geological Survey project of China Geological Survey","award":["20230101373JC"],"award-info":[{"award-number":["20230101373JC"]}]},{"name":"Science and Technology Development Project of Jilin Province","award":["41702357"],"award-info":[{"award-number":["41702357"]}]},{"name":"Science and Technology Development Project of Jilin Province","award":["41801283"],"award-info":[{"award-number":["41801283"]}]},{"name":"Science and Technology Development Project of Jilin Province","award":["DD20190340"],"award-info":[{"award-number":["DD20190340"]}]},{"name":"Science and Technology Development Project of Jilin Province","award":["20210203016SF"],"award-info":[{"award-number":["20210203016SF"]}]},{"name":"Science and Technology Development Project of Jilin Province","award":["20230101373JC"],"award-info":[{"award-number":["20230101373JC"]}]},{"name":"Natural Science Foundation of Jilin Province","award":["41702357"],"award-info":[{"award-number":["41702357"]}]},{"name":"Natural Science Foundation of Jilin Province","award":["41801283"],"award-info":[{"award-number":["41801283"]}]},{"name":"Natural Science Foundation of Jilin Province","award":["DD20190340"],"award-info":[{"award-number":["DD20190340"]}]},{"name":"Natural Science Foundation of Jilin Province","award":["20210203016SF"],"award-info":[{"award-number":["20210203016SF"]}]},{"name":"Natural Science Foundation of Jilin Province","award":["20230101373JC"],"award-info":[{"award-number":["20230101373JC"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Globally, natural wetlands have suffered severe ecological degradation (vegetation, soil, and biotic community) due to multiple factors. Understanding the spatiotemporal dynamics and driving forces of natural wetlands is the key to natural wetlands\u2019 protection and regional restoration. In this study, we first investigated the spatiotemporal evolutionary trends and shifting characteristics of natural wetlands in the Northeast Plain of China from 1990 to 2020. A dataset of driving-force evaluation indicators was constructed with nine indirect (elevation, temperature, road network, etc.) and four direct influencing factors (dryland, paddy field, woodland, grassland). Finally, we built the driving force analysis model of natural wetlands changes to quantitatively refine the contribution of different driving factors for natural wetlands\u2019 dynamic change by introducing the sparrow search algorithm (SSA) and extreme gradient boosting algorithm (XGBoost). The results showed that the total area of natural wetlands in the Northeast Plain of China increased by 32% from 1990 to 2020, mainly showing a first decline and then an increasing trend. Combined with the results of transfer intensity, we found that the substantial turn-out phenomenon of natural wetlands occurred in 2000\u20132005 and was mainly concentrated in the central and eastern parts of the Northeast Plain, while the substantial turn-in phenomenon of 2005\u20132010 was mainly located in the northeast of the study area. Compared with a traditional regression model, the SSA-XGBoost model not only weakened the multicollinearity of each driver but also significantly improved the generalization ability and interpretability of the model. The coefficient of determination (R2) of the SSA-XGBoost model exceeded 0.6 in both the natural wetland decline and rise cycles, which could effectively quantify the contribution of each driving factor. From the results of the model calculations, agricultural activities consisting of dryland and paddy fields during the entire cycle of natural wetland change were the main driving factors, with relative contributions of 18.59% and 15.40%, respectively. Both meteorological (temperature, precipitation) and topographic factors (elevation, slope) had a driving role in the spatiotemporal variation of natural wetlands. The gross domestic product (GDP) had the lowest contribution to natural wetlands\u2019 variation. This study provides a new method of quantitative analysis based on machine learning theory for determining the causes of natural wetland changes; it can be applied to large spatial scale areas, which is essential for a rapid monitoring of natural wetlands\u2019 resources and an accurate decision-making on the ecological environment\u2019s security.<\/jats:p>","DOI":"10.3390\/s23177513","type":"journal-article","created":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T10:30:52Z","timestamp":1693391452000},"page":"7513","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Driving Force Analysis of Natural Wetland in Northeast Plain Based on SSA-XGBoost Model"],"prefix":"10.3390","volume":"23","author":[{"given":"Hanlin","family":"Liu","sequence":"first","affiliation":[{"name":"College of Marine Engineering, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Nan","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Geomatics and Prospecting Engineering, Jilin Jianzhu University, Changchun 130018, China"},{"name":"School of Earth Science, Jilin University, Changchun 130026, China"}]},{"given":"Honghong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Geological Survey Institute of Jilin Province, Changchun 130102, China"}]},{"given":"Yongji","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geomatics and Prospecting Engineering, Jilin Jianzhu University, Changchun 130018, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8549-3382","authenticated-orcid":false,"given":"Chenzhao","family":"Bai","sequence":"additional","affiliation":[{"name":"College of Marine Engineering, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Duo","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Marine Engineering, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Jiali","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Marine Engineering, Dalian Maritime University, Dalian 116026, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.ocecoaman.2017.06.003","article-title":"Status of wetlands in China: A review of extent, degradation, issues and recommendations for improvement","volume":"146","author":"Meng","year":"2017","journal-title":"Ocean Coast. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1016\/j.ecolind.2015.07.003","article-title":"A review of methodologies and success indicators for coastal wetland restoration","volume":"60","author":"Zhao","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"879","DOI":"10.1007\/s11442-015-1208-5","article-title":"Recent changes in wetlands on the Tibetan Plateau: A review","volume":"25","author":"Zhao","year":"2015","journal-title":"J. Geogr. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s10584-010-0003-7","article-title":"The present and future role of coastal wetland vegetation in protecting shorelines: Answering recent challenges to the paradigm","volume":"106","author":"Gedan","year":"2011","journal-title":"Clim. Chang."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.scitotenv.2017.02.001","article-title":"Global wetlands: Potential distribution, wetland loss, and status","volume":"586","author":"Hu","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Li, X., Song, K., and Liu, G. (2020). Wetland Fire Scar Monitoring and Its Response to Changes of the Pantanal Wetland. Sensors, 20.","DOI":"10.3390\/s20154268"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mahdianpari, M., Salehi, B., Mohammadimanesh, F., Homayouni, S., and Gill, E. (2019). The First Wetland Inventory Map of Newfoundland at a Spatial Resolution of 10 m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform. Remote Sens., 11.","DOI":"10.3390\/rs11010043"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.landusepol.2018.09.036","article-title":"Urban development versus wetland loss in a coastal Latin American city: Lessons for sustainable land use planning","volume":"80","author":"Rojas","year":"2019","journal-title":"Land Use Policy"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"141778","DOI":"10.1016\/j.scitotenv.2020.141778","article-title":"Analysis of driving forces on wetland ecosystem services value change: A case in Northeast China","volume":"751","author":"Song","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e12954","DOI":"10.1111\/csp2.12954","article-title":"A wetland permanence classification tool to support prairie wetland conservation and policy implementation","volume":"5","author":"Paterson","year":"2023","journal-title":"Conserv. Sci. Pract."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wang, X., Jiang, W., Deng, Y., Yin, X., Peng, K., Rao, P., and Li, Z. (2023). Contribution of Land Cover Classification Results Based on Sentinel-1 and 2 to the Accreditation of Wetland Cities. Remote Sens., 15.","DOI":"10.3390\/rs15051275"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1007\/s12237-015-9993-8","article-title":"Mangrove Range Expansion Rapidly Increases Coastal Wetland Carbon Storage","volume":"39","author":"Doughty","year":"2016","journal-title":"Estuaries Coasts"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s00027-012-0278-z","article-title":"Current state of knowledge regarding the world\u2019s wetlands and their future under global climate change: A synthesis","volume":"75","author":"Junk","year":"2013","journal-title":"Aquat. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13717-020-00226-9","article-title":"The spatiotemporal changes of marshland and the driving forces in the Sanjiang Plain, Northeast China from 1980 to 2016","volume":"9","author":"Li","year":"2020","journal-title":"Ecol. Process."},{"key":"ref_15","first-page":"399","article-title":"High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm","volume":"18","author":"Mutanga","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1016\/j.jhydrol.2019.05.089","article-title":"Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles","volume":"575","author":"Chen","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.agwat.2019.03.035","article-title":"Spatially distributed crop model based on remote sensing","volume":"218","author":"Han","year":"2019","journal-title":"Agric. Water Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1002\/vnl.21799","article-title":"Investigation of silicone rubber composites reinforced with carbon nanotube, nanographite, their hybrid, and applications for flexible devices","volume":"27","author":"Kumar","year":"2021","journal-title":"J. Vinyl Addit. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Tran, T.V., Reef, R., and Zhu, X. (2022). A Review of Spectral Indices for Mangrove Remote Sensing. Remote Sens., 14.","DOI":"10.3390\/rs14194868"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.apgeog.2011.11.006","article-title":"Land use dynamics, built-up land expansion patterns, and driving forces analysis of the fast-growing Hangzhou metropolitan area, eastern China (1978\u20132008)","volume":"34","author":"Wu","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.rse.2018.12.034","article-title":"Individual mangrove tree measurement using UAV-based LiDAR data: Possibilities and challenges","volume":"223","author":"Yin","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"110355","DOI":"10.1016\/j.jenvman.2020.110355","article-title":"Remote sensing and GIS based analysis of temporal land use\/land cover and water quality changes in Harike wetland ecosystem, Punjab, India","volume":"262","author":"Singh","year":"2020","journal-title":"J. Environ. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12665-019-8149-8","article-title":"Integrated remote sensing-GIS analysis of urban wetland potential for crop farming: A case study of Nekemte district, western Ethiopia","volume":"78","author":"Feyissa","year":"2019","journal-title":"Environ. Earth Sci."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hao, B., Ma, M., Li, S., Li, Q., Hao, D., Huang, J., Ge, Z., Yang, H., and Han, X. (2019). Land Use Change and Climate Variation in the Three Gorges Reservoir Catchment from 2000 to 2015 Based on the Google Earth Engine. Sensors, 19.","DOI":"10.3390\/s19092118"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/s00027-012-0253-8","article-title":"Current state of knowledge regarding South America wetlands and their future under global climate change","volume":"75","author":"Junk","year":"2013","journal-title":"Aquat. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1038\/s41586-019-0951-7","article-title":"Wetland carbon storage controlled by millennial-scale variation in relative sea-level rise","volume":"567","author":"Rogers","year":"2019","journal-title":"Nature"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1123645","DOI":"10.3389\/fevo.2023.1123645","article-title":"A study of the effects of climate change and human activities on NPP of marsh wetland vegetation in the Yellow River source region between 2000 and 2020","volume":"11","author":"Feng","year":"2023","journal-title":"Front. Ecol. Evol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"163112","DOI":"10.1016\/j.scitotenv.2023.163112","article-title":"Influence of human activities and climate change on wetland landscape pattern\u2014A review","volume":"879","author":"Xiong","year":"2023","journal-title":"Sci. Total Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"980","DOI":"10.1016\/j.scitotenv.2019.01.399","article-title":"Product vs. process? The role of geomorphology in wetland characterization","volume":"663","author":"Lisenby","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1080\/03736245.2014.977812","article-title":"Using the landform tool to calculate landforms for hydrogeomorphic wetland classification at a country-wide scale","volume":"98","author":"Nel","year":"2016","journal-title":"S. Afr. Geogr. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.catena.2015.10.004","article-title":"Assessment of soil erosion change and its relationships with land use\/cover change in China from the end of the 1980s to 2010","volume":"137","author":"Wang","year":"2016","journal-title":"Catena"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s13157-019-01187-2","article-title":"Quantifying Topographic Characteristics of Wetlandscapes","volume":"40","author":"Branton","year":"2020","journal-title":"Wetlands"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1930587","DOI":"10.1080\/20964129.2021.1930587","article-title":"Wetland loss in Turkey over a hundred years: Implications for conservation and management","volume":"7","author":"Ataol","year":"2021","journal-title":"Ecosyst. Health Sustain."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Dang, Y., He, H., Zhao, D., Sunde, M., and Du, H. (2020). Quantifying the Relative Importance of Climate Change and Human Activities on Selected Wetland Ecosystems in China. Sustainability, 12.","DOI":"10.3390\/su12030912"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s10661-006-9232-7","article-title":"The landscape pattern characteristics of coastal wetlands in Jiaozhou Bay under the impact of human activities","volume":"124","author":"Gu","year":"2007","journal-title":"Environ. Monit. Assess."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Liu, K., Cao, J., Lu, M., Li, Q., and Deng, H. (2022). Spatial and Temporal Dynamics of Wetlands in Guangdong-Hong Kong-Macao Greater Bay Area from 1976 to 2019. Land, 11.","DOI":"10.3390\/land11122158"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"109735","DOI":"10.1016\/j.ecolind.2022.109735","article-title":"Prediction of the landscape pattern of the Yancheng Coastal Wetland, China, based on XGBoost and the MCE-CA-Markov model","volume":"145","author":"Hao","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"106535","DOI":"10.1016\/j.ocecoaman.2023.106535","article-title":"Analysis of the evolution and driving forces of tidal wetlands at the estuary of the Yellow River and Laizhou Bay based on remote sensing data cube","volume":"237","author":"Wang","year":"2023","journal-title":"Ocean Coast. Manag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"102995","DOI":"10.1016\/j.apgeog.2023.102995","article-title":"Tracking economic-driven coastal wetland change along the East China Sea","volume":"156","author":"Ai","year":"2023","journal-title":"Appl. Geogr."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"66514","DOI":"10.1007\/s11356-023-27123-w","article-title":"Economic and socioecological perspectives of urban wetland loss and processes: A study from literatures","volume":"30","author":"Ghosh","year":"2023","journal-title":"Environ. Sci. Pollut. Res. Int."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"21961","DOI":"10.1109\/JSEN.2022.3211021","article-title":"Fault Diagnosis Method Based on Two-Stage GAN for Data Imbalance","volume":"22","author":"Luo","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Khemiri, K., Jebari, S., Mahdhi, N., Saidi, I., Berndtsson, R., and Bacha, S. (2022). Drivers of Long-Term Land-Use Pressure in the Merguellil Wadi, Tunisia, Using DPSIR Approach and Remote Sensing. Land, 11.","DOI":"10.3390\/land11010138"},{"key":"ref_43","first-page":"217","article-title":"Decomposition processes in coastal wetlands: The importance of Suaeda salsa community for soil cellulose decomposition","volume":"66","author":"Ping","year":"2018","journal-title":"Pol. J. Ecol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"146615","DOI":"10.1016\/j.scitotenv.2021.146615","article-title":"Analyzing the spatiotemporal pattern and driving factors of wetland vegetation changes using 2000\u20132019 time-series Landsat data","volume":"780","author":"Zhang","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_45","first-page":"328","article-title":"Spatio-Temporal Changes and Driving Force Analysis of Wetlands in Jiaozhou Bay","volume":"38","author":"Tian","year":"2022","journal-title":"J. Coast. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1093\/jmammal\/gyv036","article-title":"Factors affecting acoustic detection and site occupancy of Indiana bats near a known maternity colony","volume":"96","author":"Kaiser","year":"2015","journal-title":"J. Mammal."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"107764","DOI":"10.1016\/j.ecolind.2021.107764","article-title":"Identification and scenario prediction of degree of wetland damage in Guangxi based on the CA-Markov model","volume":"127","author":"Zhang","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.jaridenv.2017.06.004","article-title":"Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression","volume":"146","author":"Georganos","year":"2017","journal-title":"J. Arid Environ."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Kopec, A., Trybala, P., Glabicki, D., Buczynska, A., Owczarz, K., Bugajska, N., Kozinska, P., Chojwa, M., and Gattner, A. (2020). Application of Remote Sensing, GIS and Machine Learning with Geographically Weighted Regression in Assessing the Impact of Hard Coal Mining on the Natural Environment. Sustainability, 12.","DOI":"10.3390\/su12229338"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00267-011-9738-9","article-title":"Spatial Variations in the Relationships between Land Use and Water Quality across an Urbanization Gradient in the Watersheds of Northern Georgia, USA","volume":"51","author":"Tu","year":"2013","journal-title":"Environ. Manag."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"7515","DOI":"10.1007\/s11356-019-07096-5","article-title":"Research on the influence of land use change to habitat of cranes in Shengjin Lake wetland","volume":"27","author":"Fang","year":"2020","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"van Asselen, S., Verburg, P.H., Vermaat, J.E., and Janse, J.H. (2013). Drivers of Wetland Conversion: A Global Meta-Analysis. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0081292"},{"key":"ref_53","first-page":"100854","article-title":"Quantifying the dynamics and driving forces of the coastal wetland landscape of the Yangtze River Estuary since the 1960s","volume":"32","author":"Wu","year":"2019","journal-title":"Reg. Stud. Mar. Sci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"105151","DOI":"10.1016\/j.engappai.2022.105151","article-title":"Ensemble deep learning: A review","volume":"115","author":"Ganaie","year":"2022","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"127762","DOI":"10.1016\/j.jhydrol.2022.127762","article-title":"Short-term runoff prediction using deep learning multi-dimensional ensemble method","volume":"609","author":"Liu","year":"2022","journal-title":"J. Hydrol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3727","DOI":"10.1007\/s00500-019-04141-w","article-title":"An ensemble learning framework for convolutional neural network based on multiple classifiers","volume":"24","author":"Guo","year":"2020","journal-title":"Soft Comput."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.inffus.2021.11.011","article-title":"Tabular data: Deep learning is not all you need","volume":"81","author":"Armon","year":"2022","journal-title":"Inf. Fusion"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1937","DOI":"10.1007\/s10462-020-09896-5","article-title":"A comparative analysis of gradient boosting algorithms","volume":"54","author":"Bentejac","year":"2021","journal-title":"Artif. Intell. Rev."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"108619","DOI":"10.1016\/j.ecolind.2022.108619","article-title":"Evaluation and analysis of ecosystem service value based on land use\/cover change in Dongting Lake wetland","volume":"136","author":"Long","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/j.jenvman.2016.06.034","article-title":"Modelling spatial association in pattern based land use simulation models","volume":"181","author":"Anputhas","year":"2016","journal-title":"J. Environ. Manag."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2923","DOI":"10.3390\/rs4102923","article-title":"Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes","volume":"4","author":"Reschke","year":"2012","journal-title":"Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Xie, H., Zhang, Y., Choi, Y., and Li, F. (2020). A Scientometrics Review on Land Ecosystem Service Research. Sustainability, 12.","DOI":"10.3390\/su12072959"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"04020051","DOI":"10.1061\/(ASCE)EM.1943-7889.0001790","article-title":"Symplectic Transfer-Matrix Method for Bending of Nonuniform Timoshenko Beams on Elastic Foundations","volume":"146","author":"Li","year":"2020","journal-title":"J. Eng. Mech."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1208","DOI":"10.1134\/S0037446622060179","article-title":"The transfer matrix of differential-algebraic equations","volume":"63","author":"Shcheglova","year":"2022","journal-title":"Sib. Math. J."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"7641","DOI":"10.1177\/09544062221078730","article-title":"An efficient technique in transfer matrix method for beam-like structures vibration analysis","volume":"236","author":"Feyzollahzadeh","year":"2022","journal-title":"Proc. Inst. Mech. Eng. Part C-J. Mech. Eng. Sci."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"96159","DOI":"10.1109\/ACCESS.2022.3204798","article-title":"An Improved Chaos Sparrow Search Optimization Algorithm Using Adaptive Weight Modification and Hybrid Strategies","volume":"10","author":"Zhang","year":"2022","journal-title":"IEEE Access"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Xiong, Q., Zhang, X., He, S., and Shen, J. (2021). A Fractional-Order Chaotic Sparrow Search Algorithm for Enhancement of Long Distance Iris Image. Mathematics, 9.","DOI":"10.3390\/math9212790"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.jmapro.2022.03.022","article-title":"Prediction and analysis of key parameters of head deformation of hot-rolled plates based on artificial neural networks","volume":"77","author":"Dong","year":"2022","journal-title":"J. Manuf. Process."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"127814","DOI":"10.1016\/j.jhydrol.2022.127814","article-title":"New method for diagnosing resilience of agricultural soil-water resource composite system: Projection pursuit model modified by sparrow search algorithm","volume":"610","author":"Xu","year":"2022","journal-title":"J. Hydrol."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Xiong, S., Liu, Z., Min, C., Shi, Y., Zhang, S., and Liu, W. (2023). Compressive Strength Prediction of Cemented Backfill Containing Phosphate Tailings Using Extreme Gradient Boosting Optimized by Whale Optimization Algorithm. Materials, 16.","DOI":"10.3390\/ma16010308"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"2340009","DOI":"10.1142\/S0218213023400092","article-title":"Prediction of Heart Disease Using a Hybrid XGBoost-GA Algorithm with Principal Component Analysis: A Real Case Study","volume":"32","author":"Ozcan","year":"2023","journal-title":"Int. J. Artif. Intell. Tools"},{"key":"ref_72","first-page":"1089","article-title":"No unbiased estimator of the variance of K-fold cross-validation","volume":"5","author":"Bengio","year":"2004","journal-title":"J. Mach. Learn. Res."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Zhao, D., He, H.S., Wang, W.J., Wang, L., Du, H., Liu, K., and Zong, S. (2018). PredictingWetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region. Sustainability, 10.","DOI":"10.3390\/su10030863"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"152021","DOI":"10.1016\/j.scitotenv.2021.152021","article-title":"Influence of meteorological conditions on the negative oxygen ion characteristics of well-known tourist resorts in China","volume":"819","author":"Wang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_75","unstructured":"Wang, O. (2023, July 01). Discussion System Reform of Water Conservancy Investment and Financing of Heilongjiang. Northeast Forestry University. Available online: https:\/\/kns.cnki.net\/kcms2\/article\/abstract?v=3uoqIhG8C475KOm_zrgu4lQARvep2SAkhskYGsHyiXlyV6jw0YcPLA_mpuQ9Ba-gfhoKpFBH9oIePGtFKgx8fYlk82Tymzyg&uniplatform=NZKPT."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.15666\/aeer\/2102_14711484","article-title":"Effect of cultivation and natural restoration on soil microbial functional structure in cold-region wetlands","volume":"21","author":"Ding","year":"2023","journal-title":"Appl. Ecol. Environ. Res."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Zheng, G., Bo, H., Wang, Y., Dong, J., Li, C., Wang, Y., Yan, S., Liu, K., and Wang, Z. (2023). Habitats generated by the restoration of coal mining subsidence land differentially alter the content and composition of soil organic carbon. PLoS ONE, 18.","DOI":"10.1371\/journal.pone.0282014"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.ecolmodel.2018.05.008","article-title":"Connectivity among wetlands matters for vulnerable amphibian populations in wetlandscapes","volume":"384","author":"Zamberletti","year":"2018","journal-title":"Ecol. Model."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s10498-022-09409-6","article-title":"Hydrogeochemical Processes of the Azigza Lake System (Middle Atlas, Morocco) Inferred from Monthly Monitoring","volume":"29","author":"Adallal","year":"2023","journal-title":"Aquat. Geochem."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Borgulat, J., Ponikiewska, K., Jalowiecki, L., Strugala-Wilczek, A., and Plaza, G. (2022). Are Wetlands as an Integrated Bioremediation System Applicable for the Treatment of Wastewater from Underground Coal Gasification Processes?. Energies, 15.","DOI":"10.3390\/en15124419"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Gil-Marquez, J.M., Andreo, B., and Mudarra, M. (2021). Comparative Analysis of Runoff and Evaporation Assessment Methods to Evaluate Wetland-Groundwater Interaction in Mediterranean Evaporitic-Karst Aquatic Ecosystem. Water, 13.","DOI":"10.3390\/w13111482"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10661-023-10928-0","article-title":"Estimation of evapotranspiration in constructed wetlands under diverse climatic conditions","volume":"195","author":"Harne","year":"2023","journal-title":"Environ. Monit. Assess."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"129748","DOI":"10.1016\/j.jhydrol.2023.129748","article-title":"High temporal and spatial resolution characteristics of evaporation, transpiration, and evapotranspiration from a subalpine wetland by an advanced UAV technology","volume":"623","author":"Yan","year":"2023","journal-title":"J. Hydrol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13157-023-01693-4","article-title":"Quantifying the Impact of Hydrological Connectivity on Salt Marsh Vegetation in the Liao River Delta Wetland","volume":"43","author":"Chen","year":"2023","journal-title":"Wetlands"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1080\/03736245.2022.2030247","article-title":"The geomorphic origin of large wetlands in Africa\u2019s elevated drylands: A Geographic Information System and Earth Observation approach","volume":"105","author":"Lidzhegu","year":"2023","journal-title":"S. Afr. Geogr. J."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/17\/7513\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:42:09Z","timestamp":1760128929000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/17\/7513"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,29]]},"references-count":85,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["s23177513"],"URL":"https:\/\/doi.org\/10.3390\/s23177513","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,29]]}}}