Iranian Journal of Forest

Iranian Journal of Forest

Evaluating habitat changes and fragmentation in mangrove forests using Landsat satellite images (Case study: Hara Protected Area)

Document Type : Research Paper

Authors
1 Assistant Prof., Dept. of Environmental Science, Natural Resources Faculty, Lorestan University, Khorramabad, Iran
2 Prof., Dept. of Environmental Science, Natural Resources Faculty, University of Tehran, Karaj, Iran
10.22034/ijf.2025.515225.2049
Abstract
Introduction: Human-driven land-use/land-cover (LULC) changes represent one of the most recognized threats to mangrove forests. These changes reduce habitat integrity and animal biodiversity within these natural and distinctive ecosystems. Habitat fragmentation is the main cause of ecosystem destruction and reduces the habitat's capacity to provide many valuable ecosystem services. This study aimed to evaluate long-term trends (1989–2023) in habitat fragmentation and alteration within the mangrove forests of the Hara  Protected Area.
Materials and Methods: We assessed the spatial–temporal changes in LULC/mangrove forest cover using multispectral Landsat imagery across the 1989–2023 period. In addition, to evaluate habitat structural change, we analyzed landscape metrics and their effects on the protection zones (Zones 1 and 2) within the study area.
Results: Results indicate that the Hara Protected Area exhibits a decreasing trend in 2023 relative to 1989. Overall, the primary drivers of LULC changes and mangrove forest decline include infrastructure development (e.g., piers and commercial/recreational ports), population growth and urban expansion, excessive tourism, overexploitation of the area’s carrying capacity, aquaculture development, and deforestation. Landscape-structure metrics (specifically the SPLIT and Patch Density, PD) increased at the mangrove forest class and aquatic patches, indicating greater fragmentation and dispersion of patches. In contrast, these metrics showed a decreasing trend at tidal flat and barren land classes. Notably, SPLIT and PD also increased within the protected zones (Zone 1 and Zone 2), signaling rising fragmentation and patch dispersion, thus reflecting reduced habitat integrity, altered patch size, and increased patch numbers and spatial dispersion.
Conclusion: The findings can inform managers and planners aiming to regulate factors shaping LULC/cover changes in these natural mangrove systems. Accordingly, proposed projects and any infrastructure development in the area should be aligned with management plans (zoning) and environmental assessments. Moreover, LULC changes should be confined beyond the administrative boundaries of the area to minimize reductions in ecosystem integrity and fragmentation within the mangroves.
Keywords

Subjects


 
Adame, M.F., Connolly, R.M., Turschwell, M.P., Lovelock, C.E., Fatoyinbo, T., Lagomasino, D., Goldberg, L.A., ‌Holdorf, J., Friess, D.A., & Sasmito, S.D. (2021). Future carbon emissions from global mangrove forest loss. ‌Global Change Biology, 27, 2856–2866. https://doi.org/10.1111/gcb.15571 ‌
Ao, Y., Li, H., Zhu, L., Ali, S., & Yang, Z. (2018). The linear random forest algorithm and its advantages in ‌machine learning assisted logging regression modeling. Journal of Petroleum Science and Engineering, 174, ‌776-789. ‌ https://doi.org/10.1016/j.petrol.2018.11.067
Babí Almenar, J., Rugani, B., Geneletti, D., & Brewer, T. (2019). Integration of ecosystem services into a ‌conceptual spatial planning framework based on a landscape ecology perspective. Landscape ‌Ecology, 33, 2047–2059.‌ https://doi.org/10.1007/s10980-018-0727-8
Banks-Leite, C., Ewers, R.M., Folkard-Tapp, H., & Fraser, A. (2020). Countering the effects of habitat loss, fragmentation, and degradation through habitat restoration. One Earth, 3(6), 672-676. https://doi.org/10.1016/j.oneear.2020.11.016
Barati, B., Jahani, A., Zebardast, L., & Rayegani, B. (2017). Integration assessment of the protected areas using landscape ecological approach (Case Study: Kolah Ghazy National Park and Wildlife Refuge). Town and country planning, 9(1), 153-168. ‌(In Persian).‌ https://doi.org/10.22059/JTCP.2017.61412
Bryan-Brown, D.N., Connolly, R.M., Richards, D.R., Adame, F., Friess, D.A., & Brown, C.J. (2020). Global trends in mangrove forest fragmentation. Scientific reports, 10(1), 7117. https://doi.org/10.1038/s41598-020-63880-1
Carugati, L., Gatto, B., Rastelli, E., Lo Martire, M., Coral, C., Greco, S., & Danovaro, R. (2018). Impact of mangrove forests degradation on biodiversity and ecosystem functioning. Scientific reports, 8(1), 13298. https://doi.org/10.1038/s41598-018-31683-0
Castillo, E.M.D., Garcia-Martin, A., Aladren, L.A.L., & Luis, M.D. (2015). Evaluation of forest cover ‌change using remote sensing techniques and landscape metrics in Moncayo Natural Park (Spain). ‌ Applied Geography, 62, 247–255.‌ https://doi.org/10.1016/j.apgeog.2015.05.002
Erfanifard, Y., Lotfi Nasirabad, M., & Stereńczak, K. (2022). Assessment of Iran’s mangrove forest dynamics (1990–2020) using Landsat time series. Remote Sensing, 14(19), 4912. https://doi.org/10.3390/rs14194912 ‌
Fischer, J., Wirtz, S., & Scherer, V. (2023). Random forest classifier and neural network for fraction identification ‌of refuse-derived fuel images. Fuel, 341, 127712. https://doi.org/10.1016/j.fuel.2023.127712
Gouvêa, L.P., Serrão, E.A., Cavanaugh, K., Gurgel, C.F., Horta, P.A., & Assis, J. (2022). Global impacts of projected ‌climate changes on the extent and aboveground biomass of mangrove forests. Diversity and Distributions., 28, 2349–2360.‌ https://doi.org/10.1111/ddi.13631
Haqverdi, F., Jahani, A., Zavarat, L., Makhdoom, M., & Goshtasb, H. (2018). Quantification of wildlife habitat fragmentation using landscape ecology approach (case study: Lar National Park and Verjin Protected Area). Quarterly Journal of Animal Environment Research, 10(4), 23-34. ‌(In Persian)
Hermansen, T.D., Minchinton, T.E., & Ayre, D.J. (2017). Habitat fragmentation leads to reduced pollinator visitation, fruit production and recruitment in urban mangrove forests. Oecologia, 185(2), 221-231. https://link.springer.com/article/10.1007/s00442-017-3941-1
Hersperger, A.M., Grădinaru, S.R., Pierri Daunt, A.B., Imhof, C.S., & Fan, P. (2021). Landscape ecological concepts in planning: review of recent developments. Landscape ecology,  36, 2329–2345.
Islam, K., Rahman, M.F., & Jashimuddin, M. (2018). Modeling land use change using cellular automata and ‌artificial neural network: The case of Chunati Wildlife Sanctuary, Bangladesh. Ecological indicators, 88, 439-453. ‌ https://doi.org/10.1016/j.ecolind.2018.01.047
Jaeger, J.A.G., Bertiller, R., Schwick, C., Muller, K., Steinmeier, C., Ewald, K.C., & Ghazoul, J. (2008). Implementing landscape fragmentation as an indicator in the swiss monitoring system of ‌sustainable development. Journal of Environmental Management, 88, 737–751.‌ https://doi.org/10.1016/j.jenvman.2007.03.043
Jafarnia, S., Hojjati, S.M., & Kooch, Y. (2012). The effect of soil and water characteristics on the vegetative parameters of Hara trees in the Qeshm mangrove habitat, Hormozgan province. Environmental Sciences, 9(4), 134-148. ‌(In Persian).
Jaramillo, J. J., Rivas, C. A., Oteros, J., & Navarro-Cerrillo, R. M. (2023). Forest fragmentation and landscape connectivity changes in Ecuadorian mangroves: some hope for the future? Applied Sciences13(8), 5001. https://doi.org/10.3390/app13085001.
John, J., Nandhini, A., Velayudhaperumal Chellam, P., & Sillanpää, M. (2022). Microplastics in mangroves and coral ‌reef ecosystems: A review. Environmental Chemistry Letters, 20, 397–416. ‌
Khan, A.R., Khan, A., Masud, S., & Rahman, R.M. (2021). Analyzing the Land Cover Change and Degradation in ‌Sundarbans Mangrove Forest Using Machine Learning and Remote Sensing Technique. In Advances in ‌Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, ‌Virtual Event, June 16–18, 2021, Proceedings, Part II 16 Springer International Publishing, 429-438.
Lacaux, J.P., Tourre, Y.M., Vignolles, C., Ndione, J.A., & Lafaye, M. (2007). Classification of ponds from high-‌spatial ‌resolution remote sensing: application to Rift Valley Fever epidemics in Senegal. Remote Sensing of Environment, 106, 66–74.‌ https://doi.org/10.1016/j.rse.2006.07.012 ‌
Li, L., Fassnacht, F.E., & Burgi, M. (2021). Using a landscape ecological perspective to analyze regime ‌shifts in social–ecological systems: a case study on grassland degradation of the Tibetan Plateau. ‌Landscape Ecology, 36, 2277–2293.
‌Liu, J., Dietz, T., Stephen, R., Carpenter, S.R., & Taylor, W.W. (2007). Complexity of coupled human and natural ‌systems. Science, 317.
Mafi Gholami, D., Baharlouii, M., & Mahmoudi, B. (2018). Erosion and accretion monitoring in mangrove forests using remote sensing and Digital Shoreline Analysis System (DSAS)(Case study: Hara Biosphere reserve). Journal of Environmental Studies, 43(4), 633-646. ‌(In Persian).
Mafi-Gholami, D., Zenner, E.K., Jaafari, A., & Bui, D.T. (2020). Spatially explicit predictions of changes in the ‌extent of mangroves of Iran at the end of the 21st century. Estuarine, Coastal and Shelf Science, 237,106644.‌ https://doi.org/10.1016/j.ecss.2020.106644
McGarigal, K., & Marks B.J. (1995). FRAGSTATS: Spatial Pattern Analysis Program for Quantifying ‌Landscape Structure. Forest Science Department. Corvallis: Oregon State University‌.
Morshed, S.R., Fattah, Md.A., Haque, Md.N., & Morshed, S.Y. (2021). Future ecosystem service ‌value modeling ‌with land cover dynamics by using machine learning based Artificial Neural ‌Network model for Jashore ‌city, Bangladesh. Physics and Chemistry of the Earth, 126, 103021. ‌
Munthali, M., Mustak, Sk., Abiodun, A., & Davis, N. (2020). Modelling land use and land cover ‌dynamics of Dedza ‌district of Malawi using hybrid Cellular Automata and Markov model. ‌Remote Sensing Applications Society ‌and Environment, 17(4), 100276.‌
Peacock, M.M. (2025). Negotiating a Fragmented World: What Do We Know, How Do We Know It, and Where Do We Go from Here?. Diversity, 17(3), 200.
Rahimi, E., SALMAN, M.A., & Soltanian, S. (2016). A comparison of continuous and discrete indices in measuring Gorgan forest landscape fragmentation. Remote Sensing and Geographic Information Systems in Natural Resources, 7(3), 30-45. ‌(In Persian).‌
Roy, S.K., Mojumder, P., Chowdhury, M.A.A., & Hasan, M.M. (2025). Evaluating mangrove forest dynamics and fragmentation in Sundarbans, Bangladesh using high-resolution Sentinel-2 satellite images. Global Ecology and Conservation58, e03493. https://doi.org/10.1016/j.gecco.2025.e03493
Sadeghovgli, R., Jahani, A., Shabani, A.A., & Ghoshtasb, H. (2019). Quantification of landscape fragmentation as an indicator for assessing wildlife habitat (Case study: Jajrood Protected Area). Journal of Animal Environment, 11(1). ‌(In Persian)
Sagar, S., Roberts, D., Bala, B., & Lymburner, L. (2017). Extracting the intertidal extent and topography of the ‌Australian coastline from a 28-year time series of Landsat observations. Remote sensing of environment, 195, 153-169. https://doi.org/10.1016/j.rse.2017.04.009.
Sharifi, N. (2021). Developing Comprehensive Model for Zoning Protected Areas Based on ‌Multi Criteria Decision Methods‌ (Case Study: HARA Protected Area). Thesis for Environmental ‌Science, Science & Research Branch, Islamic Azad University, Faculty of Environmental ‌Science and Natural Resources, 261. (In Persian).
Sharifi, N., Danehkar, A., Robati, M., Khorasani, N.A., & Rajaee, T. (2021). Developing decision algorithm for determination of protection zones in protected areas (case study: Hara Protected Area). International Journal of Environmental Science and Technology, 18(8), 2237-2250.
Sharifi, N., Danehkar, A., Robati, M., Khorasani, N.A., & Rajaee, T. (2024). Developing a Model for Zoning Protected Areas Based on the Entropy Shannon Technique (Case Study: Mangrove Protected Area). International journal of environmental science and technology, 26(10), 93-109.
Shimu, S.A., Aktar, M., Afjal, M.I., Nitu, A.M., Uddin, M.P., & Al Mamun, M. (2019). NDVI based change ‌detection in Sundarban Mangrove Forest using remote sensing data. In 2019 4th international conference on ‌electrical information and communication technology (EICT) (1-5). IEEE.‌
Sobhani, P., & Danehkar, A. (2023b). Spatial-temporal changes in mangrove Forests for Analyzing habitat Integrity: A case of Hara Biosphere Reserve, Iran, Environmental and Sustainability Indicators, 20, 100293.
Sobhani, P., Esmaeilzadeh, H., Barghjelveh, S., Sadeghi, S.M.M., & Marcu, M.V. (2022). Habitat integrity in protected areas threatened by LULC changes and fragmentation: A case study in Tehran province, Iran. Land, 11(1), 6.
Sobhani, P., & Danehkar, A. (2023/a). Natural Features and Management Areas of Khamir and Gheshm Mangrove Forests. Iran Nature, 8(4), 97-112. ‌(In Persian).‌
Sobhani, P., & Danehkar, A. (2024). The trend of land use changes and the level of ecological risk in the Hara Protected Area. Sustainable Development of Geographical Environment, 5(9), 1-19. ‌(In Persian).‌
Sudhana, S.A., Sakti, A.D., Syahid, L.N., Prasetyo, L.B., Irawan, B., Kamal, M., & Wikantika, K. (2020). Detecting ‌mangrove deforestation using multi land use land cover change datasets: a comparative analysis in ‌Southeast Asia. In IOP Conference Series: Earth and Environmental Science, 500(1), 012014. IOP ‌Publishing.‌
Talukdar, S., Eibek, K.U., Akhter, S., Ziaul, S.K., Islam, A.R.M. T., & Mallick, J. (2021). Modeling fragmentation probability of land-use and land-cover using the bagging, random forest and random subspace in the Teesta River Basin, Bangladesh. Ecological indicators, 126, 107612.
Wang, Z., Wang, T., Zhang, X., Wang, J., Yang, Y., Sun, Y., & Kuca, K. (2024). Biodiversity conservation in the context of climate change: Facing challenges and management strategies. Science of The Total Environment, 937, 173377. https://doi.org/10.1016/j.scitotenv.2024.173377
Wiarta, R., Firdaus Silamon, R., Ishag Arbab, M., Badshah, M.T., Hayat, U., & Meng, J. (2025). Assessing of driving factors and change detection of mangrove forest in Kubu Raya District, Indonesia. Frontiers in Forests and Global Change, 8, 1511361. https://doi.org/10.3389/ffgc.2025.1511361
Wibowo, A., & Supriatna, S. (2011). Coastal Environmental Vulnerability on Coastal Cities in Indonesia. Jurnal Ilmu dan Teknologi Kelautan Tropis, 3(2), 1-20. https://doi.org/10.28930/jitkt.v3i2.7818.
Wolf, I.D., Sobhani, P., & Esmaeilzadeh, H. (2023). Assessing changes in land use/land cover and ecological risk to conserve protected areas in urban–rural contexts. Land, 12(1), 231.
Xia, Q., Qin, C.Z., Li, H., Huang, C., Su, F.Z., & Jia, M.M. (2020). Evaluation of submerged mangrove recognition index using multi-tidal remote sensing data. Ecological Indicators, 113, 106196. ‌
Yaghoubzadeh, M., Salmanmahiny, A., Moslehi, M., Danehkar, A., & Tabrizi, A.M. (2021). Investigation of port effects on vegetative and reproductive characteristics of grey mangrove (Avicennia marina (Forssk.) Vierh.) of Iran. Iranian Journal of Forest and Poplar Research, 28(3), 244-256. ‌(In Persian).‌
Zebardast, L., Yavare, A., Salehi, E., & Makhdoum, M. (2012). Using landscape ecological metrics to investigate impacts of road on structural changes in Golestan National Park during 1987 to 2010. Environmental Researches, 2(4), 11-20. ‌(In Persian).‌
Zhang, L., Huettmann, F., Liu, S., Sun, P., Yu, Z., Zhang, X., & Mi, C. (2019). Classification and regression with ‌random forests as a standard method for presence-only data SDMs: a future conservation example using ‌China tree species. Ecological Informatics, 52, 46-49.
Volume 17, Issue 3 - Serial Number 3
Autumn 2025
Pages 409-430

  • Receive Date 08 April 2025
  • Revise Date 04 September 2025
  • Accept Date 25 September 2025