Research Article | Published: 15 January 2026

Spatiotemporal Monitoring and Simulations of the Land Use and Land Cover Changes in Chakaria Mangrove Forest of Bangladesh

^a , ^a , ^b,c , ^d

^aDepartment of Geography and Environmental Studies, University of Chittagong, Chattogram 4331, Bangladesh

^bChongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China

^cChongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China

^dBiomaterials Research Laboratory, Department of Applied Chemistry and Chemical Engineering, University of Chittagong, Chattogram 4331, Bangladesh

Download PDF

Abstract

The mangrove forests are growing woody plants susceptibly different for their physiochemical properties of soil, water and air quality. Besides, the mangrove forests land cover over the coastal areas has ecological and societal importance therefore, bearing different biodiversity, and different ecology, which have an aesthetic value for the live and, livelihoods. Moreover, mangrove forests play a crucial role in stabilizing shorelines and in helping reduce the devastating impact of natural disasters such as tsunamis, and hurricanes etc. The rapid growth of urbanization is the ultimate result of undergoing radical changes in its physical form, not only in its vast territorial expansion but also internal physical transformations over the last three decades. Physical characteristics of the Chakaria region is gradually changing, especially impacts over the mangrove forests. Therefore, this study attempted to figure out the root causes of this transformation, rate of transformation, consequences thereafter and strategic plan and policies to develop. As to fulfill the requirements, the temporal based spatial and areal changes of land use and land covers assessed for the yearly explorations using Landsat imagery for 1990, 2000, 2010, and 2020 were prepared individually and evaluated the land transformation and its annual changing rate. On Screen Digitization (visual interpretation) method has been applied to prepare the base maps with six land cover classes such as the water bodies, vegetation coverage, salt cultivation, shrimp cultivation area, mangrove forest, and settlement area. Further, the study evaluated that the settlement area, shrimp cultivation and salt cultivation land use types have been increasing at a high rate over the years. The principle driving these transformations were human settlements and forests coverage, which had conversely correlated each other. The significant land cover decline is found in water bodies (1562 ha), and mangrove forests (2426 ha) between 1990 and 2020, while settlement area, salt cultivation, and shrimp cultivation increased by an average of 13.72%. The study can be used as a baseline information for the conservation and master plan for the study area.

Keywords: Land use and land cover change; Mangrove forests; Landsat; Ecosystem sustainability; Bangladesh

CRediT authorship contribution statement

Mohammed Adil: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Shahidul Islam: Writing – review & editing, Visualization, Supervision, Funding acquisition, Formal analysis, Conceptualization.. Minggui Ma: Writing – review & editing, Software, Methodology. Sumon Ganguli: Writing – review & editing, Visualization, Data curation.

Declaration of competing interest

The authors would like to thank USGS for providing Landsat Imagery. Google for Google Earth engine API, and special thanks to the reviewers for their comments.

Acknowledgments

The authors would like to thank USGS for providing Landsat Imagery. Google for Google Earth engine API, and special thanks to the reviewers for their comments.

Abdullah-Al-Mamun, M. M., Masum, K. M., Raihan Sarker, A. H. M., &Mansor, A. (2017). Ecosystem services assessment using a valuation framework for the Bangladesh Sundarbans: livelihood contribution and degradation analysis. Journal of forestry research, 28(1), 1-13.

Google Scholar
Achard, F., Eva, H., Glinni, A., Mayaux, P. 1998. Identification of Deforestation not SPOT Areas in the Humid Tropics. TREES project. Joint Research Center, Ispra.

Google Scholar
Aheto DW, Kankam S, Okyere I, Mensah E, Osman A, Jonah FE, Mensah JC (2016) Community-based mangrove forest management: implications for local livelihoods and coastal resource conservation along the Volta estuary catchment area of Ghana. Ocean Coast Manag 127:43–54

Google Scholar
Alam, M. S., Shamsuddin, S. D., &Sikder, S. (1990, April). Application of remote sensing for monitoring shrimp culture development in a coastal mangrove ecosystem in Bangladesh. In Proceedings of the Twentythird International Symposium on Remote Sensing of Environment (pp. 18-25).

Google Scholar
Alauddin, M., Hossain M. N., Islam, M.B., Islam, S. and Islam, M.K. Management Strategies for Sustainable Forest Biodiversity Conservation in Protected Areas of Bangladesh: A Study of Bhawal National Park, Gazipur. Grassroots Journal of Natural Resources, 2020, 3 (3): 56-72. https://doi.org/10.33002/nr2581.6853.03035

Google Scholar
Bhattacharjee, S., Islam, M. T., Kabir, M. E., & Kabir, M. M. (2021). Land-use and land-cover change detection in a north-eastern wetland ecosystem of Bangladesh using remote sensing and GIS techniques. Earth Systems and Environment, 5(2), 319-340.

Google Scholar
Blasco, F., and Aizpuru, M. (2002). Mangroves along the coastal stretch of the Bay of Bengal: Present status.

Google Scholar
Blasco, F., Gauquelin, T., Rasolofoharinoro, M., Denis, J., Aizpuru, M. and Calderou, V. 1997. Recent advances in mangrove studies using remote sensing data. Aust. J. Marine & Fresh Water Res. 49: 287–296.

Google Scholar
Bomer, E. J., Wilson, C. A., Hale, R. P., Hossain, A. N. M., & Rahman, F. A. (2020). Surface elevation and sedimentation dynamics in the Ganges-Brahmaputra tidal delta plain, Bangladesh: Evidence for mangrove adaptation to human-induced tidal amplification. Catena, 187, 104312.

Google Scholar
Bonan, G. B. (2008). Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, pp. 1444–1449.

Google Scholar
Boring, L. R., Monk, C. D., and Swank, W. T. 1981. “Early regeneration of a clear-cut southern Appalachian forest.” Ecology, Vol. 62(No. 5): pp. 1244–1253. doi: 10.2307/1937289.

Google Scholar
Boyd, D. S. and Danson, F. M. (2005). Satellite remote sensing of forest resources: three decades of research development. Progress in Physical Geography 29, pp. 1–26.

Google Scholar
Brown, S. 1996. “Present and potential roles of forests in the global climate change debate.” Unasylva, Vol. 185: pp. 3–9.

Google Scholar
Canadell, J. G. and Raupach, M.R. (2008). Managing forests for climate change mitigation. Science 320, pp. 1456– 1457.

Google Scholar
Chowdhury, M. U. (1969). Working Plan of Cox's Bazaar Division 1968-69 to 1977-78. Forest Department: Government of East Pakistan.

Google Scholar
Das S, Vincent JR (2009) Mangroves protected villages and reduced death toll during Indian super cyclone. Proc Natl Acad Sci USA 106:7357.

Google Scholar
DeFries, R., Achard, F., Brown, S., Herold, M., Murdiyarso, D., Schlamadinger, B., et al. (2007). Earth observations for estimating greenhouse gas emissions from deforestation in developing countries. Environmental Science & Policy, 10, 385–394.

Google Scholar
Duke, N.C., Ball, M.C., Ellison, J.C. 1998. Factors influencing biodiversity and distributional gradients in mangroves. Global Ecol. Bio. Lett. 7: 27–47.

Google Scholar
EEA (2007). CLC2006 technical guidelines (technical report no 17). Copenhagen, Denmark: European Environment Agency (EEA).

Google Scholar
ESCAP. 1988. Coastal Environmental Management Plan for Bangladesh. Final Report, ESCAP, Bangkok, Thailand.

Google Scholar
FAO (Food and Agriculture Organization of the United Nations) (2007) The world’s mangroves 1980–2005. FAO Forestry Paper 153. FAO, Rome.

Google Scholar
Franklin, S.E. 2001: Remote sensing for sustainable forest management. Boca Raton, FL: Lewis.

Google Scholar
Ganguli, S., Islam, S., Garai, J. (2018). Physico-chemical assessment of water bodies and Socio-economic analysis from the coastal belt of Chittagong. Indonesian Journal of Environmental Management and Sustainability, 2(4): 107-117.

Google Scholar
Garred, P., Brygge, K., Sørensen, C. H., Madsen, H. O., Thiel, S., &Svejgaard, A. (1993). Mannan-binding protein—levels in plasma and upper-airways secretions and frequency of genotypes in children with recurrence of otitis media. Clinical & Experimental Immunology, 94(1), 99-104.

Google Scholar
Ghosh, D. K., Hossain, M.N., Sarker M.N.S., Islam, S. (2020). Effects of land-use changes pattern on tree plantation: Evidence from gher land in Bangladesh. International Journal of Agricultural Policy and Research, 8(3): 55-65.

Google Scholar
Giri, C., et al. (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography 20, pp. 154–159.

Google Scholar
Giri, C., Pengra, B., Zhu, Z., Singh, A. &Tieszen, L. (2007) Monitoring mangrove forest dynamics of the sundarbans in Bangladesh and India using multi-temporal satellite data from 1973–2000. Esturine, Coastal and Shelf Science, 73, 1–2, 91–100.

Google Scholar
Giri, C., Pengra, B., Zhu, Z., Singh, A., &Tieszen, L. L. (2007). Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000. Estuarine, coastal and shelf science, 73(1-2), 91-100.

Google Scholar
Herold, M., & Johns, T. (2007). Linking requirements with capabilities for deforestation monitoring in the context of the UNFCCC-REDD process. Environmental Research Letters, 2, 1–7

Google Scholar
Hill, R.A. 1999. Image segmentation for humid tropical forest classification in Landsat TM data. Int. J. Remote Sens. 20: 1039–1044.

Google Scholar
Homer, C., Huang, C., Yang, L., Wylie, B., &Coan, M. (2004). Development of a 2001 National Land-Cover Database for the United States. Photogrammetric Engineering & Remote Sensing, 70, 829–840. https://en.banglapedia.org/index.php/Chakaria_Sundarbans. Access 23 January 2023.

Google Scholar
Islam S, Zhang M, Yang H, Ma M. Assessing inconsistency in global land cover products and synthesis of studies on land use and land cover dynamics during 2001 to 2017 in the southeastern region of Bangladesh. Journal of Applied Remote Sensing, 2019, 13(4): 048501. https://doi.org/10.1117/1.JRS.13.048501

Google Scholar
Islam S., Ma M., Hossain M.N., Ganguli S., Sarker M.N.I. (2021) Temporal Evaluation of Climate Change on Land Use and Land Cover Changes in the Southeastern Region of Bangladesh from 2001 to 2016. In: Alam G.M.M., Erdiaw-Kwasie M.O., Nagy G.J., Leal Filho W. (eds) Climate Vulnerability and Resilience in the Global South. Climate Change Management. Springer, Cham. https://doi.org/10.1007/978-3-030-77259-8_26

Google Scholar
Islam, M. R., Khan, M. N. I., Khan, M. Z., & Roy, B. (2021). A three decade assessment of forest cover changes in Nijhumdwip national park using remote sensing and GIS. Environmental Challenges, 4, 100162.

Google Scholar
Islam, S. and Ma, M. (2018). Geospatial monitoring of land surface temperature effects on vegetation dynamics in the Southeastern Region of Bangladesh from 2001 to 2016.

Google Scholar
Islam, S., Rahman, M. M., Paul, A. Coping with Urban Coastal Disasters in Inadequate Urban Facilities: A case study at Chittagong city coastal belt, Bangladesh. Global Perspective on Geography (GPG), 2014, 2: 9-15

Google Scholar
Islam, S.; Ma, M.; Hossain, M.; Ganguli, S.; Song, Z. (2020). Climate Change and Food Security: A review of current and future perspective of China and Bangladesh. 4(4). 90-101. https://doi.org/10.26554/ijems.2020.4.4.90-101, ISPRS International Journal of Geo-Information, 7(12): 486.

Google Scholar
IUCN 1983. Global Status of Mangrove Ecosystems. Commission on Ecology Papers n◦3. IUCN, Commission on Ecology, Gland.

Google Scholar
Jiang, J., & Tian, G. (2010). Analysis of the impact of land use/land cover change on land surface temperature with remote sensing. Procedia environmental sciences, 2, 571-575.

Google Scholar
Kumar A, Ramanathan AL, Prasad MBK, Datta D, Kumar M, Sappal SM (2016) Distribution, enrichment, and potential toxicity of trace metals in the surface sediments of Sundarban mangrove ecosystem, Bangladesh: a baseline study before Sundarban oil spill of December, 2014. Environ Sci Pollut Res. https://doi. org/10.1007/s11356-016-6086-6.

Google Scholar
Lambin, E.F. and Ehrlich, D. 1997. The identification of tropical deforestation fronts at broad spatial scales. Int. J. Remote Sens. 18: 3551–3568.

Google Scholar
Malik A, Mertz O, Fensholt R (2017) Mangrove forest decline: consequences for livelihoods and environment in South Sulawesi. Reg Environ Change 17:157–169

Google Scholar
Malingreau, J.P., Achard, F., D’Souza, G., Stibig, H.J., D’Souza, J., Estréguil, C., Eva, H. 1995. AVHRR for global tropical forest monitoring: the lessons of the TREES project. Remote Sens. Rev. 12: 29–40.

Google Scholar
Mallupattu, P. K., &Sreenivasula Reddy, J. R. (2013). Analysis of land use/land cover changes using remote sensing data and GIS at an Urban Area, Tirupati, India. The Scientific World Journal, 2013.

Google Scholar
Mohiuddin M.S., Hossain M.N., Sarker M.N.I., Nayeem M.A.R., Islam S., Salehin F. (2021). Climate Change Vulnerability and its Impacts on Live and Livelihood Patterns in the South-Middle Coastal Areas of Bangladesh. In: Alam G.M.M., Erdiaw-Kwasie M.O., Nagy G.J., Leal Filho W. (eds) Climate Vulnerability and Resilience in the Global South. Climate Change Management. Springer, Cham. https://doi.org/10.1007/978-3-030-77259-8_25

Google Scholar
Mukhtar I, Hannan A (2012) Constrains on mangrove forests and conservation projects in Pakistan. J Coast Conserv 16:51–62.

Google Scholar
Mukul, S. A., Huq, S., Herbohn, J., Seddon, N., &Laurance, W. F. (2020). Saving the Sundarbans from development. Science, 368(6496), 1198-1198.

Google Scholar
Payo A, Mukhopadhyay A, Hazra S, Ghosh T, Ghosh S, Brown S, Nicholls RJ, Bricheno L, Wolf J, Kay S, Lázár AN, Haque A (2016) Projected changes in area of the Sundarban mangrove forest in Bangladesh due to SLR by 2100. Clim Change. https:// doi.org/10.1007/s10584-016-1769-z.

Google Scholar
Pomeroy, R. S. (1996). A handbook for rapid appraisal of fisheries management systems (version 1). ICLARM.

Google Scholar
Sandilyan S, Kathiresan K (2014) Decline of mangroves—a threat of heavy metal poisoning in Asia. Ocean Coast Manag 102:161–168

Google Scholar
Schmitt, C. B., et al. (2009). Global analysis of the protection status of the world’s forests. Biological Conservation 142, pp. 2122–2130.

Google Scholar
Siddiqi, N. A, M. Shahidullah and A. K. F. Hoque. 1994. Present status of ChakariaSunderbans-the oldest mangroves in the subcontinent. Bangladesh Journal of Forest Science. 23(1):26-34.

Google Scholar
Singh, S., Bhardwaj, A., & Verma, V. K. (2020). Remote sensing and GIS based analysis of temporal land use/land cover and water quality changes in Harike wetland ecosystem, Punjab, India. Journal of environmental Management, 262, 110355.

Google Scholar
Solomon, S., et al. (eds) (2007). Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. New York: Cambridge University Press.

Google Scholar
Spalding, M., Blasco, F. and Field, C. 1997. Word Mangrove Atlas. ISME, Okinawa.

Google Scholar
Strehlow, H. V., & Peters, K. J. (2004). Community action to protect fishery resources in NhaPhu Lagoon, Vietnam. Humboldt University of Berlin, Department for Animal Breeding in Tropics and Subtropics, Germany.

Google Scholar
Tewabe, D., &Fentahun, T. (2020). Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia. Cogent Environmental Science, 6(1), 1778998.

Google Scholar
Thakur, S., Maity, D., Mondal, I., Basumatary, G., Ghosh, P. B., Das, P., & De, T. K. (2021). Assessment of changes in land use, land cover, and land surface temperature in the mangrove forest of Sundarbans, northeast coast of India. Environment, Development and Sustainability, 23(2), 1917-1943.

Google Scholar
Townsley, P. (1996). Rapid rural appraisal, participatory rural appraisal and aquaculture (No. 358). Food & Agriculture Org.

Google Scholar
Tripp, R., & Woolley, J. (1989). The planning stage of on-farm research: Identifying factors for experimentation. CIMMYT.

Google Scholar
Uta B, Marion G, Boris K, Gesche K, Rubén L, Ulrich SP, Dirk S, Matthias W (1999) An integrated approach to mangrove dynamics and management. J Coast Conserv 5:125–134.

Google Scholar
Wilkie, M.L. & Fortune, S. (2003) Status and trends of mangrove area worldwide. Forest Resources Assessment Working Paper No. 63. Food and Agriculture Organization of the United Nations, Rome.

Google Scholar
Wulder, M. A. and Franklin, S. E. (2003). Remote sensing of forest environments: concepts and case studies. Massachusetts: Kluwer Academic Press.

Google Scholar
Zewdie, W., &Csaplovies, E. (2015). Remote sensing based multi-temporal land cover classification and change detection in northwestern Ethiopia. European Journal of Remote Sensing, 48(1), 121-139.

Google Scholar
Zhu K W, Chen Y C, Zhang S, Yang Z M, Huang L, Li L, Lei B, Zhou Z B, Xiong H L, Li X X, Li Y C, Islam S. (2020). Output risk evolution analysis of agricultural non-point source pollution under different scenarios based on multi-model. Global Ecology and Conservation, 23: e01144

Google Scholar

About the Article

DOI:

Received 8 July 2025 | Revised 17 December 2025 | Accepted 30 December 2025 | Published online: 15 January 2026

Article In Press Article number 10003

Corresponding Author: Shahidul Islam

Cite this article

M. Adil, S. Islam, M. Ma, S. Ganguli (2026). Spatiotemporal Monitoring and Simulations of the Land Use and Land Cover Changes in Chakaria Mangrove Forest of Bangladesh. Terra Geospatial, Article In Press.

Spatiotemporal Monitoring and Simulations of the Land Use and Land Cover Changes in Chakaria Mangrove Forest of Bangladesh

Abstract

CRediT authorship contribution statement

Declaration of competing interest

Acknowledgments

References (65)

About the Article

Cite this article

Author Name

Correspondence

Contribution