Analysis of Factors Affecting Urban Environmental Pollution in Coastal Areas (Bandar Anzali, Rezvanshahr and Astara) Using (AHP and RF) Models

جغرافیا و مخاطرات محیطی

Article 11, Volume 14, Issue 3 - Serial Number 55, September 2025, Pages 211-234   

Document Type: Research Article

DOI: 10.22067/geoeh.2025.92413.1554

Authors

Zahra Pourmoghadam¹; Mojtaba Yamani^{* 2}; Mansour Jafar Biglo³

¹Graduate of Environmental Hazards, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran

²Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran

³Associate Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran

Abstract

Urban environmental pollution in coastal areas significantly impacts water and soil quality, biodiversity, public health, and tourism activities. This study aims to identify and map pollution risk zones along the coasts of Anzali, Rezvanshahr, and Astara using a hybrid approach combining the Analytical Hierarchy Process (AHP) and the Random Forest (RF) machine learning algorithm. Fourteen critical criteria—including urban wastewater, population, human activity, coastal degradation, natural attractions, and tourism infrastructure—were selected from an initial set of 24 indicators through comparative analysis. Using expert judgment, the relative weights of each factor were calculated in Expert Choice software, and GIS-based spatial layers were generated in ArcGIS Pro. The pollution risk map was created by integrating the weighted layers. The RF model was trained using 70% of the high-risk zones as training data and 30% for testing. Model validation using ROC–AUC analysis showed excellent accuracy for the RF model (AUC = 0.97). The results revealed that Anzali County had the highest proportion of very high-risk zones, while Rezvanshahr and Astara also exhibited significant high-risk areas. The findings highlight the combined impact of human and natural drivers on coastal pollution and offer valuable insights for environmental management, spatial planning, and policy interventions to mitigate future risks.
Introduction
    Coastal areas require special attention due to the vulnerability of ecosystems and the dependence of human activities on them. Today, beaches have become one of the most popular destinations for tourists, and the presence of various coastal features creates diverse potentials for attracting visitors. Tourism, as a rapidly growing phenomenon, has become one of the largest industries in the world. The development of tourism and related recreational activities has a significant impact on the development patterns of regions and helps provide direct and indirect economic, social, cultural, and environmental benefits to host communities. However, at the same time, this development raises concerns and threats regarding environmental degradation and the destruction of the natural, historical, and cultural heritage of local residents. In fact, mass tourism does not equate to cleanliness or environmental sustainability. In this regard, some of the most significant impacts of tourism-related activities on the physical coastal environment include soil erosion, landslides, water quality degradation, shoreline alteration, and litter pollution. Litter pollution has become an undeniable threat to the sustainability of coastal ecosystems, and the threat posed by non-biodegradable plastic waste to coastal environments is increasingly evident. Pollution in the Caspian Sea poses a serious threat to aquatic life and human health. Unfortunately, coastal zones and estuaries are highly exposed to pollution, and this process endangers the survival of marine species. Urban environmental pollution in coastal areas can lead to a decline in water and soil quality, a reduction in biodiversity, health problems, and negative impacts on tourism and recreational activities.
Material and Methods
The main objective of this study is to identify and zone the coastal areas of the three counties of Anzali, Rezvanshahr, and Astara in terms of urban environmental pollution risk using the Analytic Hierarchy Process (AHP) and the Random Forest (RF) machine learning algorithm. In this regard, effective criteria were first identified. From an initial set of 24 criteria, 14 were selected: natural attractiveness, coastal degradation, river, road, human activity, urban drainage, population, urban waste, protection and management, facilities, security, natural landscapes, hotels, and the influence of tourism on population. Information layers for these were prepared in the ArcGIS Pro environment. Using the AHP method, the relative impact of each criterion was determined, and 70% of the high-risk areas were used as training data and 30% as test data for training the Random Forest algorithm. The predictive accuracy of the model results was evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC).
Results and Discussion
The results of validating the zoning maps using test data showed that the accuracy of the analytic hierarchy process and random forest models was 0.812 and 0.97, respectively. These results show that the random forest model has high accuracy in zoning coastal pollution. The results also show that the security criterion is the most significant in training the machine learning algorithm.
The results of coastal zone pollution zoning in the analytic hierarchy process and random forest model showed that in Anzali County, 0.82% and 10.10% were in the very low-risk class, 0.55% and 16.55% in the low-risk class, 0.6% and 0.36% in the medium-risk class, 73.89% and 27.35% in the high-risk class, and 20.6% and 24.9% in the very high-risk class. In Rezvanshahr County, 0.57% and 12.55% were in the very low-risk class, 7.09% and 28.71% in the low-risk class, 21.27% and 22.68% in the medium-risk class, 66.64% and 98% in the high-risk class, and 0.45% and 0% in the very high-risk class. In Astara County, 0.02% and 26.73% were in the very low-risk class, 6.30% and 23.21% in the low-risk class, 23.87% and 31.20% in the medium-risk class, and 6.44% and 16.51% in the high-risk class.
Conclusion
     Pollution from industrial and domestic wastewater entering the coastal waters is one of the major challenges on the northern coasts of Iran. In Bandar Anzali, this problem has been exacerbated due to the lack of adequate wastewater management infrastructure and poor enforcement of environmental laws. The general conclusion for the three cities of Astara, Bandar Anzali, and Rezvanshahr shows that all three regions face specific environmental pollution challenges caused by a combination of natural and human factors. Managers and planners can effectively reduce the risks of pollution in coastal areas by using the results of this research. Furthermore, these results will help facilitate the development and implementation of practical solutions.

Keywords

Caspian Sea Coastal Environmental Pollution; Random Forest Algorithm; Analytic Hierarchy Process (AHP); Pollution Risk Zoning

References

Abirami, A. (2024). Marine pollution and waste management, Law and legal research development. Journal of Law and Legal Research Development, 1(2), 20-24. https://doi.org/10.69662/jllrd.v1i2.10

Arabadzhyan, A., Figini, P., García, C., González, M. M., Lam-González, Y. E., & León, C. J. (2021). Climate change, coastal tourism, and impact chains–a literature review. Current Issues in Tourism, 24(16), 2233-2268. https://doi.org/10.1080/13683500.2020.1825351

Bancal, N. (2017). Industrial Development and Challenges of Water Pollution in Coastal Areas: The Case of Surat, India. OP conference series Earth and Environmental science, 120, (012001). http://dx.doi.org/10.1088/1755-1315/120/1/012001

Breiman, L. (2001). Random Forests. Machine Learning, 45(1), 5-32. http://dx.doi.org/10.1023/A:1010933404324

Chen, W., Li, y., Xue, W., Shahabi, H., Li, S., & Hong, H. (2020). Modelingflood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree and random forest methods. Science of the Total Environment. 701, 134979. https://doi.org/10.1016/j.scitotenv.2019.134979

Darvishi, R., Rezaei, M. R., & Shams-Aldini, A. (2018). Investigating the role of coastal tourism in economic development from the perspective of citizens. Quarterly Scientific-Research Journal of Geography (Regional Planning), 8(4), 411-426. [In Persian] https://dor.isc.ac/dor/20.1001.1.22286462.1397.8.4.24.7

Davar, L., Azizi Jalilian, M., Rafiei, R., & Danehkar, A. (2014). Vulnerability zoning of the coastal strip of Sistan and Baluchestan province based on threat foci. Journal of Natural Environment, 67(3), 289-300. [In Persian] https://doi.org/10.22059/jne.2014.52728

Ebrahimi, M., & Ramezanipour, M. (2018). Measuring the level of environmental responsibility of tourists. Geography and Human Relations, 1(2), 835-849. [In Persian] https://dor.isc.ac/dor/20.1001.1.26453851.1397.1.2.52.5

Fathalipour, M. (2023). Investigation of water polluting sources on the southern coast of the Caspian Sea in Gilan Province. Paper presented at the Proceedings of the 3^th International Conference on New Technologies in Science, Amol, 3-4. [In Persian] https://civilica.com/doc/1753787

Garcés-Ordóñez, O., Díaz, L. F. E., Cardoso, R. P., & Muniz, M. C. (2020). The impact of tourism on marine litter pollution on Santa Marta beaches, Colombian Caribbean. Marine Pollution Bulletin, 160, 111558. https://doi.org/10.1016/j.marpolbul.2020.111558

Ghosh, T. (2011). Coastal tourism: opportunity and sustainability. Journal of Sustainable Developmen, 4(6), 67. https://doi.org/10.5539/jsd.v4n6p67

Haji Amiri, R., Asghari, H., Amar‌, T., & Poursheykhian, A. (2023). Necessity of analysis of solid municipal wastes from origin to destination with emphasis on Astara city (West of Gilan province). Geographical Engineering of Territory, 7(2), 477-494. [In Persian] https://dor.isc.ac/dor/20.1001.1.25381490.1402.7.2.17.3

Hakimi, F., & Khanjani, F. (2014). Environmental impacts of tourism on the coastal strip of Gilan using software GIS. Paper presented at the Proceedings of the 2^th National Conference on Tourism, Geography and Sustainable Environment. [In Persian] https://civilica.com/doc/329164

Janparvar, M., Taghizadeh Sarokalaei, A., & Mazloom, Z. (2016). Politics, Technology and Environment (A Different Perspective on Environmental Issues in Guilan). Paper presented at the Proceedings of the Conference on Land Planning, the Position of the Caspian Sea and the Development Prospects of Gilan. [In Persian] https://civilica.com/doc/584777

Jorgensen, B., Krasny, M., & Baztan, J. (2021) Volunteer beach cleanups: civic Environmental stewardship combating global plastic pollution. Sustainability Science, 16(1), 153-167.  https://hal.science/hal-02919775v1

Kabil, M., Priatmoko, S., Magda, R., & Denes-david, L. (2021). Blue Economy and Coastal Tourism: A Comprehensive Visualization Bibliometric Analysis. Sustainability, 13(7), 3650. https://doi.org/10.3390/su13073650

Karnejadi, A., Ownegh, M., Pourghasemi, H., Bahremand, A., & Motamedi, M. (2019). Landslide susceptibility prediction using combined Mahalanobis distance and machine learning models (Case study: Oghan watershed, Golestan province). Earth Science Research, 11(42), 1-18. [In Persian] https://doi.org/10.52547/esrj.11.2.1

Lasaiba, M. (2024). Mitigation of Waste Pollution in Coastal Ecosystems and Mangrove Forests in Coastal Areas. Jurnal Pengabdian Arumbai, 2(1), 1-13. https://doi.org/10.30598/arumbai.vol2.iss1.pp1-13

Maghsoudi, M., Mohammad Khan, Sh., & Gholami, F. (2023). The role of natural factors in the settlement of ancient sites in the Payab basin of Seymareh 2 using the AHP model. Physical Geography, 16(62), 1-15. [In Persian] https://journals.iau.ir/article_709111.html

Movahedi, S., & Rostami, A. (2021). Investigating the potential for the development of cross-border cultural tourism in Guilan Province. Journal of Urban Studies on Space and Place, 4(14). [In Persian]https://dor.isc.ac/dor/20.1001.1.25386050.1399.1399.14.2.6

Pourshikhian, A., Amar, T., & Ebrahimi, S. A. (2012). Analysis on the topology criteria for hygienic curative centers in Anzali Port city. Journal of Studies of Human Settlements Planning, 21(7), 88-100. [In Persian] https://dorl.net/dor/20.1001.1.25385968.1391.7.21.8.8

Salari Sardari, F. A., Arabzadeh, S., Teymuri, S., & Jam, M. (2016). Analysis and Evaluation of the Role of Human Activities in the Persian Gulf. Persian Gulf Studies, 2(2), 65-77. [In Persian] https://persiangulf.iranology.ir/file/65_25_full.pdf

Salehi, S., Ghadami, M., & Hemmati Gouyomi, Z. (2012). A study of Environmental Behaviors among Coastal Tourists (A case Study of Coastal Tourists in Bushehr City during New Year Holiday). Journal of Tourism Planning and Development, 1(1), 35-58. [In Persian] https://tourismpd.journals.umz.ac.ir/article_295.html

Yaghoubzadeh, M., Danehkar, A., Haghighat, M., Mashhadi Rafiee, M., & Lotfikhah, S. (2022). Coastal Zoning of Sistan and Baluchestan Base on Environmental Sensitivity. Journal of Natural Environment, 75(1), 49-63. [In Persian] https://doi.org/10.22059/jne.2022.336323.2360

Zakeri Minabi, E., Zarei, M., & Derakhshan, A. (2024). Identification and leveling of pollution threat in sensitive coastal areas in the east of the Strait of Hormuz (Study area: Sirik County). Journal of Marine Medicine, 6(3), 185-193. [In Persian] http://dx.doi.org/10.30491/6.3.185

Ziari, K., Rezvani, M. R., & Ferdowsi, S. (2020). Determination of Physical-Ecological Carrying Capacity of Coastal Tourism and its Effectiveness of Satisfaction of Tourists (Case Study: Bandar Gaz). Journal of Environmental Science and Technology, 22(6), 189-202. [In Persian] http://dx.doi.org/10.22034/JEST.2019.24324.3332