Estimation of Aboveground Forest Biomass and Carbon Storage of Bangladesh
Downloads
Forest biomass helps mitigate climate change impacts through sequestration of atmospheric carbon dioxide and potentially storing it for long periods of time. Deforestation and timber harvesting cause the reduction of forest biomass resulting in the reduced carbon sequestration capacity and alterednatural balance of forest ecosystems. We used remote sensing and GIS tools in the four important forest cover zones within five districts of Bangladesh to compare the aboveground forest biomass (AGB) changes between 2014 and 2020. We found an increased AGB in Sundarban mangrove forest from 89.73 Mg.h-1 in 2014 to 90.76 Mg.h-1 in 2020. Similarly, the AGB was found to be increased for Ukhiya hill forest from 7.89 Mg.h-1 in 2014 to 8.89 Mg.h-1 in 2020. Contrary, the average AGB content in Nijhum Dwip mangrove forest decreased from 44.36 Mg.h-1 in 2014 to 37.46 Mg.h-1 in 2020. The average AGB of Modhupur decidious forest also found to be decreased from 110.01 Mg.h-1 in 2014 to 107.22 Mg.h-1 in 2020. The decreased biomass contents could be attributed to anthropgenic factors as indicated by the presence of human activities and this informatin will be helpful for forest restoration and management in Bangladesh.
Downloads
Akhtar, N., Uddin, M. K., & Tan, Y. (2022). Remote sensing-based changes in the Ukhia Forest, Bangladesh. GeoJournal, 87(5), 4269-4287. https://doi.org/10.1007/s10708-021-10494-3 DOI: https://doi.org/10.1007/s10708-021-10494-3
Akhter, M., Mahmood, H., Birigazzi, B., & Matieu, H. (2013). Tree volume and biomass allometric equations of Bangladesh (Inventory No. 10.13140/ RG.2.2.29295.97445) (p. 33). Dhaka, Bangladesh: Bangladesh Forest Department and Food and Agriculture Organization of the United Nations. https://www.researchgate.net/publication/
_Tree_volume_and_biomass_allometric_equation_in_Bangladesh. Accessed 8 August 2023.
Al Faruq, M. A., Zaman, S., & Katoh, M. (2016). Analysis of forest cover changes using Landsat satellite imagery: a case study of the Madhupur Sal forest in Bangladesh. Journal of Forest Planning, 21(2), 29-38. DOI: https://doi.org/10.20659/jfp.21.2_29
Alamgir, M., & Al-Amin, M. (2007). Organic carbon storage in trees within different Geopositions of Chittagong (South) Forest Division, Bangladesh. Journal of Forestry Research, 18, 174-180. DOI: https://doi.org/10.1007/s11676-007-0036-6
Alamgir, M., & Turton, S. M. (2013). Climate change and organic carbon storage in Bangladesh forests. Climate change and plant abiotic stress tolerance, 881-902. DOI: https://doi.org/10.1002/9783527675265.ch33
Ali, I., Greifeneder, F., Stamenkovic, J., Neumann, M., & Notarnicola, C. (2015). Review of machine learning approaches for biomass and soil moisture retrievals from remote sensing data. Remote Sensing, 7(12), 16398-16421. DOI: https://doi.org/10.3390/rs71215841
Altrell, D., Saket, M., Lyckebäck, L., & Piazza, M. (2007). National forest and tree resources assessment 2005-2007, Bangladesh (Assessment) (p. 280). Dhaka, Bangladesh: Ministry of Environment and Forest (MoEF), Bangladesh and Food and Agriculture Organization of the United Nations (FAO). https://www.fao.org/forestry/15466-0af9a225183f27cf84c440a6a1bf90d6e.pdf. Accessed 2 August 2023.
Angelsen, A. (2009). Realising REDD+: National strategy and policy options. Bogor, Indonesia: Centre for International Forestry Research.
Aziz, A., & Paul, A. (2015). Bangladesh Sundarbans: Present Status of the Environment and Biota. Diversity, 7(3), 242-269. https://doi.org/10.3390/ d7030242 DOI: https://doi.org/10.3390/d7030242
BFD. (2017). Natural Mangrove Forest (Sundarbans). Bangladesh National Portal: Forest Department, Government of the People’s Republic of Bangladesh. Government Database. http:// www.bforest.gov.bd/site/page/19d63ffe-01e1-4351-b85b-3b60811b87f7/-. Accessed 3 August 2023.
BFD. (2020). Tree and Forest Resources of Bangladesh: Report on the Bangladesh Forest Inventory (Assessment No. GCP/BGD/058/USA) (p. 213). Dhaka, Bangladesh: Forest Department, Ministry of Environment, Forest and Climate Change, Government of the People’s Republic of Bangladesh. http://bfis.bforest.gov.bd/bfi/. Accessed 2 August 2023.
BMD. (2020). Bangladesh Climate Data Portal. BMD: Bangladesh Meteorological Department, Dhaka, Bangladesh. http://bmd.wowspace.org/team/ homex.php. Accessed 10 August 2023.
Brown, S. (1997). Estimating biomass and biomass change of tropical forests: a primer (Vol. 134). Food & Agriculture Org.
Brown, S., Iverson, L., & Prasad, A. (2001). Geographical Distribution of Biomass Carbon in Tropical Southeast Asian Forests: A Database (NPD-068). Environmental System Science Data Infrastructure for a Virtual Ecosystem; Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory, Oak Ridge, TN (USA). https://doi.org/10.3334/CDIAC/LUE.NDP068 DOI: https://doi.org/10.3334/CDIAC/lue.ndp068
Chowdhury, M. S. H., & Koike, M. (2010). An overview on the protected area system for forest conservation in Bangladesh. Journal of Forestry research, 21, 111-118. DOI: https://doi.org/10.1007/s11676-010-0019-x
Chowdhury, S. U., Foysal, M., Shahadat, O., Prince, N. U., Mohsanin, S., & Islam, M. T. (2020). Globally threatened shorebirds of Nijhum Dwip National Park and management implications. Wader Study Group Bulletin, 127, 244-251. DOI: https://doi.org/10.18194/ws.00202
Costello, L., Piazza, M., Iqbal, Z., Nur Siddiqui, B., Akhter, M., Siddiqui, R., & Henry, M. (2016). Experiences in Field Missions to Locate the Plots of the 2005 National Forest Assessment (NFA) of Bangladesh (Assessment No. GCP/GD/058/USAID) (p. 13). Dhaka, Bangladesh: Bangladesh Forest Department (BFD) and Food and Agriculture Organization of the United Nations (FAO). http://bfis.bforest.gov.bd/ library/wp-content/uploads/2018/12/38.pdf. Accessed 2 August 2023.
Deb, J., Phinn, S., Butt, N., & McAlpine, C. (2018). Climate change impacts on tropical forests: identifying risks for tropical Asia. Journal of Tropical Forest Science, 30(2), 182-194. DOI: https://doi.org/10.26525/jtfs2018.30.2.182194
DeFries, R. S., Houghton, R. A., Hansen, M. C., Field, C. B., Skole, D., & Townshend, J. (2002). Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 1990s. Proceedings of the National Academy of Sciences, 99(22), 14256-14261. DOI: https://doi.org/10.1073/pnas.182560099
Donato, D. C., Kauffman, J. B., Murdiyarso, D., Kurnianto, S., Stidham, M., & Kanninen, M. (2011). Mangroves among the most carbon-rich forests in the tropics. Nature geoscience, 4(5), 293-297. DOI: https://doi.org/10.1038/ngeo1123
Eggleston, H., Buendia, L., Miwa, K., Ngara, T., & Tanabe, K. (2006). 2006 IPCC guidelines for national greenhouse gas inventories.
FAO (Ed.). (2010). Global forest resources assessment 2010: main report. Rome: FAO. https://www.fao.org/3/ i1757e/i1757e.pdf. Accessed 10 August 2023.
Field, C. B., Randerson, J. T., & Malmström, C. M. (1995). Global net primary production: combining ecology and remote sensing. Remote sensing of Environment, 51(1), 74-88. DOI: https://doi.org/10.1016/0034-4257(94)00066-V
GFW. (2022). Forest Monitoring Designed for Action. Global Forest Watch. https:// www.globalforestwatch.org/. Accessed 10 August 2023.
Gibbs, H. K., Brown, S., Niles, J. O., & Foley, J. A. (2007). Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environmental research letters, 2(4), 045023. DOI: https://doi.org/10.1088/1748-9326/2/4/045023
Giri, C., Long, J., Abbas, S., Murali, R. M., Qamer, F. M., Pengra, B., & Thau, D. (2015). Distribution and dynamics of mangrove forests of South Asia. Journal of environmental management, 148, 101-111. DOI: https://doi.org/10.1016/j.jenvman.2014.01.020
Giri, C., Ochieng, E., Tieszen, L. L., Zhu, Z., Singh, A., Loveland, T., et al. (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography, 20(1), 154-159. DOI: https://doi.org/10.1111/j.1466-8238.2010.00584.x
Hale, R. P., Wilson, C., & Bomer, E. (2019). Seasonal variability of forces controlling sedimentation in the Sundarbans National Forest, Bangladesh. Frontiers in Earth Science, 211. DOI: https://doi.org/10.3389/feart.2019.00211
Harris, N., & Gibbs, D. (2021). Forests absorb twice as much carbon as they emit each year. World Resources Institute. Forests. https://www.wri.org/insights/ forests-absorb-twice-much-carbon-they-emit-each-year. Accessed 9 August 2023.
Hasan, M. E., Zhang, L., Mahmood, R., Guo, H., & Li, G. (2021). Modeling of Forest Ecosystem Degradation Due to Anthropogenic Stress: The Case of Rohingya Influx into the Cox’s Bazar–Teknaf Peninsula of Bangladesh. Environments, 8(11), 121. https://doi.org/10.3390/environments8110121 DOI: https://doi.org/10.3390/environments8110121
Henry, M., Iqbal, Z., Johnson, K., Akhter, M., Costello, L., Scott, C., et al. (2021). A multi-purpose National Forest Inventory in Bangladesh: design, operationalisation and key results. Forest Ecosystems, 8(1), 12. https://doi.org/10.1186/s40663-021-00284-1 DOI: https://doi.org/10.1186/s40663-021-00284-1
Hossain, F., & Moniruzzaman, Dr. Md. (2021). Environmental change detection through remote sensing technique: A study of Rohingya refugee camp area (Ukhia and Teknaf sub-district), Cox’s Bazar, Bangladesh. Environmental Challenges, 2, 100024. https://doi.org/10.1016/ j.envc.2021.100024 DOI: https://doi.org/10.1016/j.envc.2021.100024
Hossain, K. M., & Haider, R. M. (2020). Assessment Report on Plantation/Reforestation 2019 at Rohingya Camp, Cox’s Bazar, Final Draft.
Hossain, K. T., Tanim, I. A., & Salauddin, M. (2016). Change detection of forest cover: a study Nijhum Dwip National Park, Hatiya, Noakhali. Journal of Life and Earth Sciences, Jagannath University, 2(2), 54-90.
Hu, Z., Wu, G., Zhang, L., Li, S., Zhu, X., Zheng, H., et al. (2017). Modeling and Partitioning of Regional Evapotranspiration Using a Satellite-Driven Water-Carbon Coupling Model. Remote Sensing, 9(1), 54. https://doi.org/10.3390/rs9010054 DOI: https://doi.org/10.3390/rs9010054
Islam, M. M., & Mamun, M. M. I. (2015). Variations of NDVI and its association with rainfall and evapotranspiration over Bangladesh. Rajshahi University Journal of Science and Engineering, 43, 21-28. DOI: https://doi.org/10.3329/rujse.v43i0.26160
Islam, Md. R., Khan, Md. N. I., Khan, Md. Z., & Roy, B. (2021). A three decade assessment of forest cover changes in Nijhum dwip national park using remote sensing and GIS. Environmental Challenges, 4, 100162. https://doi.org/10.1016/j.envc.2021.100162 DOI: https://doi.org/10.1016/j.envc.2021.100162
Islam, Md. Y., Nasher, N. M. R., Karim, K. H. R., & Rashid, K. J. (2023). Quantifying forest land-use changes using remote-sensing and CA-ANN model of Madhupur Sal Forests, Bangladesh. Heliyon, 9(5), e15617. https://doi.org/10.1016/ j.heliyon.2023.e15617 DOI: https://doi.org/10.1016/j.heliyon.2023.e15617
Islam, S., & Alam, A. R. (2021). Performance evaluation of FAO Penman-Monteith and best alternative models for estimating reference evapotranspiration in Bangladesh. Heliyon, 7(7). DOI: https://doi.org/10.1016/j.heliyon.2021.e07487
Khan, Ms. N. (2022, February 9). Involving Rohingya refugees in reforestation in Bangladesh to reduce disaster risks. United Nations Office for Disaster Risk Reduction (UNDRR). Analysis. https:// www.undrr.org/news/involving-rohingya-refugees-reforestation-bangladesh-reduce-disaster-risks. Accessed 10 August 2023.
Khan, N. A., & Millate-e-Mustafa, M. (2001, September 16). The State Of Forestry In Bangladesh. The Bangladesh Observer, p. 6. Dhaka, Bangladesh. https://ruchichowdhury.tripod.com/state_of_forestry_in_bangladesh.htm. Accessed 16 August 2023.
Kibria, M. G., & Saha, N. (2011). Analysis of existing agroforestry practices in Madhupur Sal forest: an assessment based on ecological and economic perspectives. Journal of Forestry Research, 22, 533-542. DOI: https://doi.org/10.1007/s11676-011-0196-2
Köhl, M., Magnussen, S., & Marchetti, M. (2006). Sampling methods, remote sensing and GIS multiresource forest inventory (Vol. 2). Springer. DOI: https://doi.org/10.1007/978-3-540-32572-7
Li, Y., Li, M., Li, C., & Liu, Z. (2020). Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms. Scientific Reports, 10(1), 9952. https://doi.org/10.1038/ s41598-020-67024-3 DOI: https://doi.org/10.1038/s41598-020-67024-3
Littell, J. S., Oneil, E. E., McKenzie, D., Hicke, J. A., Lutz, J. A., Norheim, R. A., & Elsner, M. M. (2010). Forest ecosystems, disturbance, and climatic change in Washington State, USA. Climatic change, 102, 129-158. DOI: https://doi.org/10.1007/s10584-010-9858-x
Lu, D., Chen, Q., Wang, G., Moran, E., Batistella, M., Zhang, M., et al. (2012). Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates. International Journal of Forestry Research, 2012, 1-16. https://doi.org/10.1155/2012/436537 DOI: https://doi.org/10.1155/2012/436537
Macdicken, K. G., Fao, R. eng, Jonsson, Ö., Pina, L. C. de, Maulo, S., Adikari, Y., et al. (2015). Global Forest Resources Assessment 2015: how are the world’s forests changing? https://api.semanticscholar.org/ CorpusID:134207584 DOI: https://doi.org/10.1016/j.foreco.2015.02.006
Mahmood, H., Ahmed, M., Islam, T., Uddin, M. Z., Ahmed, Z. U., & Saha, C. (2021). Paradigm shift in the management of the Sundarbans mangrove forest of Bangladesh: Issues and challenges. Trees, Forests and People, 5, 100094. https://doi.org/ 10.1016/j.tfp.2021.100094 DOI: https://doi.org/10.1016/j.tfp.2021.100094
Mahmood, H., Saha, C., Paul, N., Deb, S., Abdullah, S. M. R., Tanvir, Md. S. S. I., et al. (2021). The soil quality of the world’s largest refugee campsites located in the Hill forest of Bangladesh and the way forward to improve the soil quality. Environmental Challenges, 3, 100048. https://doi.org/10.1016/ j.envc.2021.100048 DOI: https://doi.org/10.1016/j.envc.2021.100048
Masson-Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., & Shukla, P. R. (2022). Global Warming of 1.5 C: IPCC special report on impacts of global warming of 1.5 C above pre-industrial levels in context of strengthening response to climate change, sustainable development, and efforts to eradicate poverty. Cambridge University Press.
MoEFCC. (2021). Nationally Determined Contributions (NDCs) 2021 Bangladesh (p. 37). Dhaka, Bangladesh: Ministry of Environment, Forest and Climate Change (MoEFCC), Government of the People’s Republic of Bangladesh. https://unfccc.int/ sites/default/files/NDC/2022-06/ NDC_submission_20210826revised.pdf
Mollick, A. S., Rahman, M. K., Khan, M. N. I., & Sadath, M. N. (2018). Evaluation of good governance in a participatory forestry program: A case study in Madhupur Sal forests of Bangladesh. Forest Policy and Economics, 95, 123-137. DOI: https://doi.org/10.1016/j.forpol.2018.07.014
Mukul, Sharif A, Biswas, S. R., Rashid, A. M., Miah, D., Kabir, E., Uddin, M. B., et al. (2014). A new estimate of carbon for Bangladesh forest ecosystems with their spatial distribution and REDD+ implications. International Journal of Research on Land-use Sustainability, 1(1), 33-41.
Mukul, Sharif A, Herbohn, J., Rashid, A. M., & Uddin, M. B. (2014). Comparing the effectiveness of forest law enforcement and economic incentives to prevent illegal logging in Bangladesh. International Forestry Review, 16(3), 363-375. DOI: https://doi.org/10.1505/146554814812572485
Mukul, Sharif Ahmed, Rashid, A. Z. M. M., & Khan, N. A. (2016). Forest Protected Area Systems and Biodiversity Conservation in Bangladesh (preprint). EARTH SCIENCES. https://doi.org/10.20944/ preprints201611.0101.v1 DOI: https://doi.org/10.20944/preprints201611.0101.v1
Nishorgo Network. (2018). Nijhum Dwip National Park (Monitoring) (p. 2). Hatiya, Noakhali: USAID and Government of Bangladesh. https://nishorgo.org/ project/nijhum-dweep-national-park/. Accessed 3 August 2023.
Nur, A., Nandi, R., Jashimuddin, M., & Hossain, M. A. (2016). Tree Species Composition and Regeneration Status of Shitalpur Forest Beat under Chittagong North Forest Division, Bangladesh. Advances in Ecology, 2016, 1-7. https://doi.org/10.1155/2016/ 5947874 DOI: https://doi.org/10.1155/2016/5947874
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., et al. (2011). A large and persistent carbon sink in the world’s forests. Science, 333(6045), 988-993. DOI: https://doi.org/10.1126/science.1201609
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P. M., Mooney, H. A., & Klooster, S. A. (1993). Terrestrial ecosystem production: A process model based on global satellite and surface data. Global biogeochemical cycles, 7(4), 811-841. DOI: https://doi.org/10.1029/93GB02725
Rahman, L. M. (2021). Bangladesh National Convervation Strategy: Forest Resources (Inventory) (p. 43). Dhaka, Bangladesh: Ministry of Environment, Forest and Climate Change, Government of the People’s Republic of Bangladesh. http:// bforest.portal.gov.bd/. Accessed 8 August 2023.
Rahman, M. M., Khan, M. N. I., Hoque, A. F., & Ahmed, I. (2015). Carbon stock in the Sundarbans mangrove forest: spatial variations in vegetation types and salinity zones. Wetlands Ecology and Management, 23, 269-283. DOI: https://doi.org/10.1007/s11273-014-9379-x
Rahman, M., Nishat, A., & Vacik, H. (2009). Anthropogenic disturbances and plant diversity of the Madhupur Sal forests (Shorea robusta CF Gaertn) of Bangladesh. International Journal of Biodiversity Science & Management, 5(3), 162-173. DOI: https://doi.org/10.1080/17451590903236741
Rashid, A. (2017). Literature Review of Gender dimensions in forest use, management, governance, land tenure arrangements and safeguards in support of REDD+ in Bangladesh. UN-REDD Bangladesh National Program.
Reddy, C. S., Pasha, S. V., Jha, C., Diwakar, P., & Dadhwal, V. (2016). Development of national database on long-term deforestation (1930–2014) in Bangladesh. Global and Planetary Change, 139, 173-182. DOI: https://doi.org/10.1016/j.gloplacha.2016.02.003
Reza, A. A., & Hasan, M. K. (2019). Forest biodiversity and deforestation in Bangladesh: the latest update. Forest degradation around the world, 1-19.
Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T., Salas, W., et al. (2011). Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the national academy of sciences, 108(24), 9899-9904. DOI: https://doi.org/10.1073/pnas.1019576108
Salam, M. A., Noguchi, T., & Koike, M. (1999). The causes of forest cover loss in the hill forests in Bangladesh. GeoJournal, 47, 539-549. DOI: https://doi.org/10.1023/A:1006947203052
Sarkar, S. K., Saroar, M., & Chakraborty, T. (2023). Navigating nature’s toll: Assessing the ecological impact of the refugee crisis in Cox’s Bazar, Bangladesh. Heliyon, 9(7), e18255. https://doi.org/ 10.1016/j.heliyon.2023.e18255 DOI: https://doi.org/10.1016/j.heliyon.2023.e18255
Sellers, P., Meeson, B., Hall, F., Asrar, G., Murphy, R., Schiffer, R., et al. (1995). Remote sensing of the land surface for studies of global change: Models—algorithms—experiments. Remote Sensing of Environment, 51(1), 3-26. DOI: https://doi.org/10.1016/0034-4257(94)00061-Q
SER. (2022). Bangladesh: Mangrove Afforestation Programme of the National Forest Department. Society for Ecological Restoration (SER). Analysis. https://www.ser-rrc.org/project/bangladesh-mangrove-afforestation-programme-of-the-national-forest-department/. Accessed 10 August 2023.
Shin, M. Y., Miah, M. D., & Lee, K. H. (2007). Potential contribution of the forestry sector in Bangladesh to carbon sequestration. Journal of environmental management, 82(2), 260-276. DOI: https://doi.org/10.1016/j.jenvman.2005.12.025
Sims, D. A., Luo, H., Hastings, S., Oechel, W. C., Rahman, A. F., & Gamon, J. A. (2006). Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem. Remote Sensing of Environment, 103(3), 289-303. https://doi.org/ 10.1016/j.rse.2005.01.020 DOI: https://doi.org/10.1016/j.rse.2005.01.020
Sohel, Md. S. I., Islam, H. M. N., Newaz, K. Md. N., Khan, M. F. A., Sarker, G. C., & Bhuiyan, Md. S. R. (2023). Ecohydrological, climatic and tree architectural considerations for reforestation program using swamp vegetation of Bangladesh. Ecohydrology & Hydrobiology, 23(1), 127-140. https://doi.org/ 10.1016/j.ecohyd.2022.12.005 DOI: https://doi.org/10.1016/j.ecohyd.2022.12.005
Suri, M., Betak, J., Rosina, K., Chrkavy, D., Suriova, N., Cebecauer, T., et al. (2020). Global Solar Atlas (Assessment No. 149846) (p. 62). Washington DC: World Bank and Internation Finance Corporation. https://globalsolaratlas.info/map. Accessed 9 August 2023.
Tripathi, S., Soni, S. K., Maurya, A. K., & Soni, P. K. (2010). Calculating carbon sequestration using remote sensing and GIS. Geospatial world, 1-8.
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote sensing of Environment, 8(2), 127-150. DOI: https://doi.org/10.1016/0034-4257(79)90013-0
Uddin, M. M., Mahmud, M. A. A., & Jannat, M. (2019). Impacts of mangrove plantations on land stabilization along the coastline in Bangladesh. American Journal of Earth and Environmental Sciences, 2(1).
Ullah, M., & Al-Amin, M. (2012). Above-and below-ground carbon stock estimation in a natural forest of Bangladesh. Journal of forest science, 58(8), 372-379. DOI: https://doi.org/10.17221/103/2011-JFS
Ullah, S. A., Tsuchiya, J., Asahiro, K., & Tani, M. (2022). Exploring the socioeconomic drivers of deforestation in Bangladesh: The case of Teknaf Wildlife Sanctuary and its surrounding community. Trees, Forests and People, 7, 100167. DOI: https://doi.org/10.1016/j.tfp.2021.100167
UNHCR. (2023, July 23). Rohingya Crises: Bangladesh. The UN Refugee Agency. Monitoring. https:// data.unhcr.org/en/country/bgd. Accessed 4 August 2023.
Unni, N. M. (1983). Forest survey and management
using remote sensing. Proceedings of the Indian
Academy of Sciences Section C: Engineering Sciences, 6, 209-232.
Yasmin, R., Wadud, M., Mandol, M., & Sharif, M. (2010). Tree diversity in the homestead and cropland areas of Madhupur Upazila under Tangail District. J. Agrofor. Environ, 4(1), 89-92.
Copyright (c) 2023 Ajoy Mojumder, Md Sahadat Hossain, Timothy A Volk
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree with the following terms:
- Authors retain copyright and grant the journal right of first publication, with the work 1 year after publication simultaneously licensed under a Creative Commons attribution-noncommerical-noderivates 4.0 International License that allows others to share, copy and redistribute the work in any medium or format, but only where the use is for non-commercial purposes and an acknowledgement of the work's authorship and initial publication in this journal is mentioned.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
