The sustainable development of Madeira Island necessitates the implementation of more precise and targeted planning strategies to address its regional challenges. Given the urgency of this issue within the context of sustainability, planning approaches must be grounded in and reinforced by a comprehensive array of thematic studies to fully grasp the complexities involved. This research leverages Geographic Information Systems (GIS) to analyze land use and occupancy patterns and their evolution within the municipality of Machico on Madeira Island. The study provides a nuanced perspective on the urban structure’s stagnation in the region, while concurrently highlighting the dynamic shifts in agricultural practices. Furthermore, it elucidates the transformation of predominant native vegetation within the municipality from 1990 to 2018. Notably, the research underscores the alarming decline in native vegetation due to anthropogenic activities, emphasizing the need for more rigorous monitoring by regional authorities to safeguard and preserve these valuable landscapes, habitats, and ecosystems.

Alves, R., Lousada, S., Cabezas, J., et al. (2022). The Importance of the Strategic Urban Rehabilitation Plan in the Sustainable Development of the Municipality of Machico. Sustainability, 14(24), 16816. https://doi.org/10.3390/su142416816

Arévalo, J. R., Delgado, J. D., Otto, R., et al. (2005). Distribution of alien vs. native plant species in roadside communities along an altitudinal gradient in Tenerife and Gran Canaria (Canary Islands). Perspectives in Plant Ecology, Evolution and Systematics, 7(3), 185–202. https://doi.org/10.1016/j.ppees.2005.09.003

Baig, M. F., Mustafa, M. R. U., Baig, I., et al. (2022). Assessment of Land Use Land Cover Changes and Future Predictions Using CA-ANN Simulation for Selangor, Malaysia. Water, 14(3), 402. https://doi.org/10.3390/w14030402

Bakkestuen, V., Venter, Z., Ganerød, A. J., et al. (2023). Delineation of Wetland Areas in South Norway from Sentinel-2 Imagery and LiDAR Using TensorFlow, U-Net, and Google Earth Engine. Remote Sensing, 15(5), 1203. https://doi.org/10.3390/rs15051203

Bertrand, N., & Vanpeene-Bruhier, S. (2007). Periurban landscapes in mountain areas. Revue de Géographie Alpine, 95–4, 69–80. https://doi.org/10.4000/rga.363

Bildirici, M. E., Lousada, S., & Yılmaz Genç, S. (2022). Terrorism, Freshwater, and Environmental Pollution: Evidence of Afghanistan, Burkina Faso, Iraq, Arab Republic of Egypt, Cameroon, Mali, Mozambique, Niger, Nigeria, Somalia, Syrian Arab Republic, and Pakistan. Water, 14(17), 2684. https://doi.org/10.3390/w14172684

Boston, T., Van Dijk, A., & Thackway, R. (2023). Convolutional Neural Network Shows Greater Spatial and Temporal Stability in Multi-Annual Land Cover Mapping Than Pixel-Based Methods. Remote Sensing, 15(8), 2132. https://doi.org/10.3390/rs15082132

Cao, Y., Xu, C., Aziz, N. M., et al. (2023). BIM–GIS Integrated Utilization in Urban Disaster Management: The Contributions, Challenges, and Future Directions. Remote Sensing, 15(5), 1331. https://doi.org/10.3390/rs15051331

Chang, S., Zhao, J., Jia, M., et al. (2023). Land Use Change and Hotspot Identification in Harbin–Changchun Urban Agglomeration in China from 1990 to 2020. ISPRS International Journal of Geo-Information, 12(2), 80. https://doi.org/10.3390/ijgi12020080

Chen, H., Yang, L., & Wu, Q. (2023). Enhancing Land Cover Mapping and Monitoring: An Interactive and Explainable Machine Learning Approach Using Google Earth Engine. Remote Sensing, 15(18), 4585. https://doi.org/10.3390/rs15184585

Chen, J., Li, Y., Zhang, C., et al. (2023). Urban Flooding Prediction Method Based on the Combination of LSTM Neural Network and Numerical Model. International Journal of Environmental Research and Public Health, 20(2), 1043. https://doi.org/10.3390/ijerph20021043

Chen, T., Jiao, J., Wei, W., et al. (2023). Spatiotemporal Variation in the Land Use/Cover of Alluvial Fans in Lhasa River Basin, Qinghai–Tibet Plateau. Agriculture, 13(2), 312. https://doi.org/10.3390/agriculture13020312

Chen, Y., Liu, Y., Yang, S., et al. (2023). Impact of Land-Use Change on Ecosystem Services in the Wuling Mountains from a Transport Development Perspective. International Journal of Environmental Research and Public Health, 20(2), 1323. https://doi.org/10.3390/ijerph20021323

Clima, condições meteorológicas e temperatura média por mês de Machico (Portugal)—Weather Spark. (sem data). Obtido 10 de janeiro de 2024, de https://pt.weatherspark.com/y/31634/Clima-caracter%C3%ADstico-em-Machico-Portugal-durante-o-ano

Çolak, O., Özuyar, S. E. G., & Bölükbaşı, Ö. F. (2022). Asymmetric Effects of the Defense Burden on Environmental Degradation: Evidence from NATO Countries. Sustainability, 15(1), 573. https://doi.org/10.3390/su15010573

Commey, N. A., Magome, J., Ishidaira, H., et al. (2023). Catchment-Scale Land Use and Land Cover Change Analysis in Two Coastal Ramsar Sites in Ghana, Using Remote Sensing. Water, 15(20), 3568. https://doi.org/10.3390/w15203568

European Environment Agency. Corine Land Cover—European Environment Agency. Available online: https://www.eea.europa.eu/publications/COR0-landcover (accessed on 1 November 2024).

European Union. EUR-Lex—32007L0002—EN - EUR-Lex. Available online: https://eur-lex.europa.eu/legal-content/en/NIM/?uri=CELEX%3A32007L0002 (accessed on 1 November 2024).

Fagua, J. C., Rodríguez-Buriticá, S., & Jantz, P. (2023). Advancing High-Resolution Land Cover Mapping in Colombia: The Importance of a Locally Appropriate Legend. Remote Sensing, 15(10), 2522. https://doi.org/10.3390/rs15102522

Faria de Deus, R., Tenedório, J. A., Pumain, D., et al. (2023). 100 Years of Land-Use and Land-Cover Data: What Has Been the Effect of Spatial Planning in Coastal Land-Use and Land-Cover Change? Sustainability, 15(9), 7636. https://doi.org/10.3390/su15097636

Gao, P., Niu, X., Wang, B., et al. (2015). Land use changes and its driving forces in hilly ecological restoration area based on gis and rs of northern china. Scientific Reports, 5(1). https://doi.org/10.1038/srep11038

García-Ayllón, S., & Martínez, G. (2023). Analysis of Correlation between Anthropization Phenomena and Landscape Values of the Territory: A GIS Framework Based on Spatial Statistics. ISPRS International Journal of Geo-Information, 12(8), 323. https://doi.org/10.3390/ijgi12080323

Geng, J., Xu, L., Wang, Y., et al. (2023). Study of Land Cover Change in the City with the Fastest Economic Growth in China (Hefei) from 2000 to 2020 Based on Google Earth Engine Platform. Remote Sensing, 15(6), 1604. https://doi.org/10.3390/rs15061604

Gentilucci, M., Pelagagge, N., Rossi, A., et al. (2023). Landslide Susceptibility Using Climatic–Environmental Factors Using the Weight-of-Evidence Method—A Study Area in Central Italy. Applied Sciences, 13(15), 8617. https://doi.org/10.3390/app13158617

Geologia. (sem data). Visit Machico. Obtido 10 de janeiro de 2024, de https://www.visitmachico.com/pt/sobre-machico/turismo-tematico/geologia

GmbH (https://www.klokantech.com/), K. T. (sem data). Madeira 1936 / UTM zone 28N - EPSG:2191. Obtido 6 de fevereiro de 2024, de https://epsg.io

Haller, A. (2014). The “sowing of concrete”: Peri-urban smallholder perceptions of rural–urban land change in the Central Peruvian Andes. Land Use Policy, 38, 239–247. https://doi.org/10.1016/j.landusepol.2013.11.010

Hao, X., Qiu, Y., Jia, G., et al. (2023). Evaluation of Global Land Use–Land Cover Data Products in Guangxi, China. Remote Sensing, 15(5), 1291. https://doi.org/10.3390/rs15051291

Hasan, N. A., Yang, D., & Al-Shibli, F. (2023). A Historical–Projected Analysis in Land Use/Land Cover in Developing Arid Region Using Spatial Differences and Its Relation to the Climate. Sustainability, 15(3), 2821. https://doi.org/10.3390/su15032821

Hassan, M. M. (2017). Monitoring land use/land cover change, urban growth dynamics and landscape pattern analysis in five fastest urbanized cities in Bangladesh. Remote Sensing Applications: Society and Environment, 7, 69–83. https://doi.org/10.1016/j.rsase.2017.07.001

Home: Corine Land Cover classes. (sem data). Obtido 12 de janeiro de 2024, de https://land.copernicus.eu/content/corine-land-cover-nomenclature-guidelines/html/

Hu, J., Jiao, S., Xia, H., et al. (2023). Construction of Rural Multifunctional Landscape Corridor Based on MSPA and MCR Model—Taking Liukeng Cultural and Ecological Tourism Area as an Example. Sustainability, 15(16), 12262. https://doi.org/10.3390/su151612262

Ishikawa, T., & Akoh, R. (2023). Application of Running Water-Type Retarding Basin to Old Kinu River Floodplain, Japan. Hydrology, 10(4), 94. https://doi.org/10.3390/hydrology10040094

Janczewska, N., Matysik, M., Absalon, D., et al. (2023). Spatial Multi-Criteria Analysis of Water-Covered Areas: District City of Katowice—Case Study. Remote Sensing, 15(9), 2356. https://doi.org/10.3390/rs15092356

Jiang, G., Wang, J., Li, K., et al. (2023). Consistency Analysis and Accuracy Evaluation of Multi-Source Land Cover Data Products in the Eastern European Plain. Remote Sensing, 15(17), 4254. https://doi.org/10.3390/rs15174254

Kalfas, D., Kalogiannidis, S., Chatzitheodoridis, F., et al. (2023). Urbanization and Land Use Planning for Achieving the Sustainable Development Goals (SDGs): A Case Study of Greece. Urban Science, 7(2), 43. https://doi.org/10.3390/urbansci7020043

Kohno, M., & Higuchi, Y. (2023). Landslide Susceptibility Assessment in the Japanese Archipelago Based on a Landslide Distribution Map. ISPRS International Journal of Geo-Information, 12(2), 37. https://doi.org/10.3390/ijgi12020037

Li, C., Sun, N., Lu, Y., et al. (2023). Review on Urban Flood Risk Assessment. Sustainability, 15(1), 765. https://doi.org/10.3390/su15010765

Li, X., & Yang, L. (2023). Accelerated Restoration of Vegetation in Wuwei in the Arid Region of Northwestern China since 2000 Driven by the Interaction between Climate and Human Beings. Remote Sensing, 15(10), 2675. https://doi.org/10.3390/rs15102675

Liu, M., Chen, G., Li, G., et al. (2023). Landscape Evolution and Its Driving Forces in the Rapidly Urbanized Guangdong–Hong Kong–Macao Greater Bay Area, a Case Study in Zhuhai City, South China. Sustainability, 15(17), 13045. https://doi.org/10.3390/su151713045

Loures, L., Castanho, R. A., Gómez, J. M. N., et al. (2019). Impactos Socioculturais da Cooperação Transfronteiriça (CT) no Espaço Europeu. Fronteiras: Journal of Social, Technological and Environmental Science, 8(3), 292–312. https://doi.org/10.21664/2238-8869.2019v8i3.p292-312

Lousada, S. A. N. (2023). A Influência do Coeficiente de Rugosidade nos Fenómenos de Cheias – Bacia Hidrográfica da Ribeira de Machico, Ilha da Madeira, Portugal. Revista Brasileira de Geomorfologia, 24(3). https://doi.org/10.20502/rbg.v24i3.2307

Lousada, S., Cabezas, J., Castanho, R. A., et al. (2022). Hydraulic Planning in Insular Urban Territories: The Case of Madeira Island—Ribeira Brava. Water, 13(21), 2951. https://doi.org/10.3390/w13212951

Lousada, S., & Castanho, R. A. (2022). The Role of Ports in Tourism: Porto Santo Harbour. Water, 14(19), 3176. https://doi.org/10.3390/w14193176

Lousada, S., Gonçalves, L., & Atmaca, A. (2022). Hydraulic Planning in Insular Urban Territories: The Case of Madeira Island—São Vicente. Water, 14(1), 112. https://doi.org/10.3390/w14010112

Lousada, S., & Loures, L. (2020). Modelling Torrential Rain Flows in Urban Territories: Floods—Natural Channels (The Case Study of Madeira Island). American Journal of Water Science and Engineering, 6(1), 17. https://doi.org/10.11648/j.ajwse.20200601.13

Lousada, S., Silva, P. S. da, Castanho, R. A., & Naranjo-Gómez, J. M. (2019). Modelação de sistemas de abastecimento de água. O caso de Ilha da Madeira. Bitácora Urbano Territorial, 29(2), 89–98. https://doi.org/10.15446/bitacora.v29n2.69381

Lu, Z., & Zhang, Z. (2023). Dynamics of Territorial Spatial Pattern and Landscape Impact under Different Economic Gradients: A Case Study of the Beijing-Tianjin-Hebei (BTH) Region, China. Sustainability, 15(1), 259. https://doi.org/10.3390/su15010259

Lukas, P., Melesse, A. M., & Kenea, T. T. (2023). Prediction of Future Land Use/Land Cover Changes Using a Coupled CA-ANN Model in the Upper Omo–Gibe River Basin, Ethiopia. Remote Sensing, 15(4), 1148. https://doi.org/10.3390/rs15041148

Ma, D., Jiang, S., Tan, X., et al. (2023). Spatiotemporal Conflict Analysis and Prediction of Long Time Series Land Cover Changes in the Black Soil Region of Northeast China Using Remote Sensing and GIS. ISPRS International Journal of Geo-Information, 12(7), 271. https://doi.org/10.3390/ijgi12070271

Machico. (2023). Em Wikipédia, a enciclopédia livre. https://pt.wikipedia.org/w/index.php?title=Machico&oldid=65853677

Mansour, S., Ghoneim, E., El-Kersh, A., et al. (2023). Spatiotemporal Monitoring of Urban Sprawl in a Coastal City Using GIS-Based Markov Chain and Artificial Neural Network (ANN). Remote Sensing, 15(3), 601. https://doi.org/10.3390/rs15030601

Meier, J., & Mauser, W. (2023). Irrigation Mapping at Different Spatial Scales: Areal Change with Resolution Explained by Landscape Metrics. Remote Sensing, 15(2), 315. https://doi.org/10.3390/rs15020315

Melchiorri, M., Florczyk, A., Freire, S., et al. (2018). Unveiling 25 Years of Planetary Urbanization with Remote Sensing: Perspectives from the Global Human Settlement Layer. Remote Sensing, 10(5), 768. https://doi.org/10.3390/rs10050768

Merchán, L., Martínez-Graña, A., Nieto, C. E., et al. (2023). Geospatial Characterisation of Gravitational and Erosion Risks to Establish Conservation Practices in Vineyards in the Arribes del Duero Natural Park (Spain). Agronomy, 13(8), 2102. https://doi.org/10.3390/agronomy13082102

Miklósová, V., & Kozelová, I. (2023). Conflicts of the Land Use and Ecosystem Services in the Riverine Landscape of the Little Danube. Water, 15(24), 4221. https://doi.org/10.3390/w15244221

Naranjo Gómez, J. M., Lousada, S., Garrido Velarde, J. G., et al. (2020). Land-Use Changes in the Canary Archipelago Using the CORINE Data: A Retrospective Analysis. Land, 9(7), 232. https://doi.org/10.3390/land9070232

Neumann, K., Herold, M., Hartley, A., et al. (2007). Comparative assessment of CORINE2000 and GLC2000: Spatial analysis of land cover data for Europe. International Journal of Applied Earth Observation and Geoinformation, 9(4), 425–437. https://doi.org/10.1016/j.jag.2007.02.004

Orusa, T., Cammareri, D., & Borgogno Mondino, E. (2023a). A Possible Land Cover EAGLE Approach to Overcome Remote Sensing Limitations in the Alps Based on Sentinel-1 and Sentinel-2: The Case of Aosta Valley (NW Italy). Remote Sensing, 15(1), 178. https://doi.org/10.3390/rs15010178

Orusa, T., Cammareri, D., & Borgogno Mondino, E. (2023b). A Scalable Earth Observation Service to Map Land Cover in Geomorphological Complex Areas beyond the Dynamic World: An Application in Aosta Valley (NW Italy). Applied Sciences, 13(1), 390. https://doi.org/10.3390/app13010390

Papadopoulou, E., Mallinis, G., Siachalou, S., et al. (2023). Agricultural Land Cover Mapping through Two Deep Learning Models in the Framework of EU’s CAP Activities Using Sentinel-2 Multitemporal Imagery. Remote Sensing, 15(19), 4657. https://doi.org/10.3390/rs15194657

Parente, J., Tonini, M., Stamou, Z., et al. (2023). Quantitative Assessment of the Relationship between Land Use/Land Cover Changes and Wildfires in Southern Europe. Fire, 6(5), 198. https://doi.org/10.3390/fire6050198

Pereira, F. (2023). Demografia. Câmara Municipal de Machico (Original language). Available online: https://www.cm-machico.pt/territorial/o-territorio/demografia (accessed on 1 November 2024).

Author Name. PJ detém suspeito de atear incêndio florestal na Madeira—Portugal—Correio da Manhã (Original language). Available online: https://www.cmjornal.pt/portugal/detalhe/pj-detem-suspeito-de-atear-incendio-florestal-na-madeira (accessed on 1 November 2024).

Author Name. Portal do INE. (sem data). Available online: https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_publicacoes (accessed on 1 November 2024).

Puniach, E., Bieda, A., Ćwiąkała, P., et al. (2018). Use of Unmanned Aerial Vehicles (UAVs) for Updating Farmland Cadastral Data in Areas Subject to Landslides. ISPRS International Journal of Geo-Information, 7(8), 331. https://doi.org/10.3390/ijgi7080331

Rai, M. K., Paudel, B., Zhang, Y., et al. (2023). Appraisal of Empirical Studies on Land-Use and Land-Cover Changes and Their Impact on Ecosystem Services in Nepal Himalaya. Sustainability, 15(9), 7134. https://doi.org/10.3390/su15097134

Riera-Spiegelhalder, M., Campos-Rodrigues, L., Enseñado, E. M., et al. (2023). Socio-Economic Assessment of Ecosystem-Based and Other Adaptation Strategies in Coastal Areas: A Systematic Review. Journal of Marine Science and Engineering, 11(2), 319. https://doi.org/10.3390/jmse11020319

Rukhovich, D. I., Koroleva, P. V., Rukhovich, A. D., et al. (2023). Informativeness of the Long-Term Average Spectral Characteristics of the Bare Soil Surface for the Detection of Soil Cover Degradation with the Neural Network Filtering of Remote Sensing Data. Remote Sensing, 15(1), 124. https://doi.org/10.3390/rs15010124

Shimizu, K., Murakami, W., Furuichi, T., et al. (2023). Mapping Land Use/Land Cover Changes and Forest Disturbances in Vietnam Using a Landsat Temporal Segmentation Algorithm. Remote Sensing, 15(3), 851. https://doi.org/10.3390/rs15030851

Siangulube, F. S., Ros-Tonen, M. A. F., Reed, J., et al. (2023). Spatial Tools for Inclusive Landscape Governance: Negotiating Land Use, Land-Cover Change, and Future Landscape Scenarios in Two Multistakeholder Platforms in Zambia. Land, 12(4), 804. https://doi.org/10.3390/land12040804

Sieber, I. M., Hinsch, M., Vergílio, M., et al. (2021). Assessing the effects of different land-use/land-cover input datasets on modelling and mapping terrestrial ecosystem services—Case study Terceira Island (Azores, Portugal). One Ecosystem, 6. https://doi.org/10.3897/oneeco.6.e69119

Siewert, J., & Kroszczynski, K. (2023). Evaluation of High-Resolution Land Cover Geographical Data for the WRF Model Simulations. Remote Sensing, 15(9), 2389. https://doi.org/10.3390/rs15092389

Silva, A., Gonçalves, L., Moura, A., et al. (2021). Flood Hazard Assessment in Madeira (Portugal)—The Case Study of Machico. American Journal of Water Science and Engineering, 7(1), 1. https://doi.org/10.11648/j.ajwse.20210701.11

Solís, E., Ruiz-Apilánez, B., Moyano, A., et al. (2023). Towards Sustainable Regional Planning: Potential of Commuter Rail in the Madrid Urban Region. Applied Sciences, 13(6), 3953. https://doi.org/10.3390/app13063953

Statistics| FAO | Food and Agriculture Organization of the United Nations. (sem data). Statistics. Obtido 9 de janeiro de 2024, de https://www.fao.org/statistics/en

Synthesis—European Environment Agency. (sem data). [Collection]. Obtido 9 de janeiro de 2024, de https://www.eea.europa.eu/soer/2015/collections/synthesis

Tang, J., Fang, Y., Tian, Z., et al. (2023). Ecosystem Services Research in Green Sustainable Science and Technology Field: Trends, Issues, and Future Directions. Sustainability, 15(1), 658. https://doi.org/10.3390/su15010658

Tefera, G. W., Dile, Y. T., & Ray, R. L. (2023). Evaluating the Impact of Statistical Bias Correction on Climate Change Signal and Extreme Indices in the Jemma Sub-Basin of Blue Nile Basin. Sustainability, 15(13), 10513. https://doi.org/10.3390/su151310513

Union, P. O. of the E. (sem data). Https://op.europa.eu/en/publication-detail/-/publication/96743011-0b4f-11ea-8c1f-01aa75ed71a1 [Website]. Publications Office of the EU; Publications Office of the European Union. Obtido 10 de janeiro de 2024, de https://op.europa.eu/en/publication-detail/-/publication/96743011-0b4f-11ea-8c1f-01aa75ed71a1

Văculișteanu, G., Doru, S. C., Necula, N., et al. (2023). One Century of Pasture Dynamics in a Hilly Area of Eastern Europe, as Revealed by the Land-Use Change Approach. Sustainability, 15(1), 406. https://doi.org/10.3390/su15010406

Vizzari, M., Hilal, M., Sigura, M., et al. (2018). Urban-rural-natural gradient analysis with CORINE data: An application to the metropolitan France. Landscape and Urban Planning, 171, 18–29. https://doi.org/10.1016/j.landurbplan.2017.11.005

Vulevic, A., Castanho, R. A., Gómez, J. M. N., et al. (2021). Cross-Border Cooperation and Adaptation to Climate Change in Western Balkans Danube Area. In: Governing Territorial Development in the Western Balkans: Challenges and Prospects of Regional Cooperation. Springer International Publishing. pp. 289–308.

Wang, Y., Zhang, X., Huang, C., et al. (2023). Spatial-Convolution Spectral-Transformer Interactive Network for Large-Scale Fast Refined Land Cover Classification and Mapping Based on ZY1-02D Satellite Hyperspectral Imagery. Remote Sensing, 15(13), 3269. https://doi.org/10.3390/rs15133269

Wang, Z., Guo, M., Zhang, D., et al. (2023). Coupling the Calibrated GlobalLand30 Data and Modified PLUS Model for Multi-Scenario Land Use Simulation and Landscape Ecological Risk Assessment. Remote Sensing, 15(21), 5186. https://doi.org/10.3390/rs15215186

Wei, L., Cheng, H., & Dai, Z. (2023). Propagation Modeling of Rainfall-Induced Landslides: A Case Study of the Shaziba Landslide in Enshi, China. Water, 15(3), 424. https://doi.org/10.3390/w15030424

Wongthongtham, P., Abu-Salih, B., Huang, J., et al. (2023). A Multi-Criteria Analysis Approach to Identify Flood Risk Asset Damage Hotspots in Western Australia. Sustainability, 15(7), 5669. https://doi.org/10.3390/su15075669

Xing, H., Wang, H., Zhang, J., et al. (2023). Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model. Remote Sensing, 15(3), 736. https://doi.org/10.3390/rs15030736

Yaakub, N. F., Masron, T., Marzuki, A., et al. (2022). GIS-Based Spatial Correlation Analysis: Sustainable Development and Two Generations of Demographic Changes. Sustainability, 14(3), 1490. https://doi.org/10.3390/su14031490

Zhang, J., Fu, Z., Zhu, Y., et al. (2023). A High-Performance Automated Large-Area Land Cover Mapping Framework. Remote Sensing, 15(12), 3143. https://doi.org/10.3390/rs15123143

Zhao, J., Liu, S., Wang, Z., et al. (2023). The Impact of Land Use and Landscape Pattern on Ecosystem Services in the Dongting Lake Region, China. Remote Sensing, 15(9), 2228. https://doi.org/10.3390/rs15092228

Zimmermann, E., Bracalenti, L., Piacentini, R., et al. (2016). Urban Flood Risk Reduction by Increasing Green Areas for Adaptation to Climate Change. Procedia Engineering, 161, 2241–2246. https://doi.org/10.1016/j.proeng.2016.08.822