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Spatio-temporal changes of forest and other land covers in the North-eastern Part (Jamalpur & Sherpur) of Bangladesh

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Research Paper 15/11/2022
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Spatio-temporal changes of forest and other land covers in the North-eastern Part (Jamalpur & Sherpur) of Bangladesh

Noor Shaila Sarmin
J. Bio. Env. Sci.21( 5), 120-128, November 2022.
Certificate: JBES 2022 [Generate Certificate]
Key: DeforestationLand use changeRemote sensingUrbanization

Abstract

Being a developing country Bangladesh is facing a rapid land use and land cover (LULC) change in recent few decades. The study was conducted to quantify the LULC change in the north-eastern part of Bangladesh for one decade. Landsat imageries of the study area for 2010 and 2020 were downloaded from the USGS earth explorer. The images were processed using QGIS and ArcGIS soft wares. A supervised semi-auto classification technique was applied to classify the study area into five land cover classes, i.e., forest, water, agri/homestead, fallow and built-up. Overall classification accuracies were 88% and 90% for the images of 2010 and 2020, respectively. During the studied decade, the coverage of built-up and agri/homestead showing an increasing trend in exchange of forest, water, and fallow lands which showed a decreasing trend. In one-decade period built-up area increased by 54.32% and agri/homestead area increased by 2.83%. On the other hand, fallow land decreased 50.6%. During the studied timeframe from 2010 to 2020, about 27033.75ha of forest area and 10799.19ha of fallow land area were converted to agri/homestead. However, about 3307.14ha and 5046.06ha of agri/homestead area was converted to fallow and built-up, respectively. About 312.92ha, 331.29ha and 278.1ha of forest area in 2010 was converted to water, fallow and built-up area, respectively in 2020. Different causes reported are mainly over-exploitation, illegal logging, making settlements and housing for increased population, urbanization etc.

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Abdullah HM, Mahboob MG, Rahman MM, Ahamed T. 2015. Monitoring Natural Sal forest cover in Madhupur, Bangladesh using temporal Landsat imagery during 1972-2015. International Journal of Environment 5(1), 1-7.

Abdullah HM, Muraduzzaman M, Islam I, Miah MG, Rahman MM, Rahman A, Ahmed N, Ahmed Z. 2019. Spatiotemporal dynamics of new land development in Bangladesh coast and its potential uses. Remote Sensing Applications: Society and Environment 14(2019), 191-199.

Bangladesh Bureau of Statistics (BBS), District Statistics. 2011. Jamalpur and Sherpur district. Statistics and Informatics Division (SID), Ministry of Planning, Government of the People’s Republic of Bangladesh 2013.

Chowdhury QI. 1999. Bangladesh: country overview. In: Q. I. Chowdhury (ed.), Bangladesh State of Environment report 1998. Forum of Environmental Journalists of Bangladesh (FEJB), Dhaka pp. 3-14.

FAO/UNDP. 1988. Land Resources Appraisal of Bangladesh for Agricultural Development Report 2: Agroecological Regions of Bangladesh, FAO/UNDP.

Food and Agriculture Organization (FAO). 2016. State of the World’s Forests 2016. Forest and Agriculture: land-use challenges and opportunities. Rome.

Gómez C, White JC, Wulder MA. 2016. Optical remotely sensed time series data for land cover classification: a review. ISPRS J. Photogrammetry Remote Sens 116, 55-72.

Haiming Y, Jinyan Z, Qunou J. 2010. Scenario simulation of changes of forest land in Poyang Lake watershed, Procedia Environ. Scinica 2, 1469-1478.

Hasan SS, Sarmin NS, Miah MG. 2020. Assessment of scenario-based land use changes in the Chittagong Hill Tracts of Bangladesh. Environmental Development 34, 100463.

Holdgate MW. 1993. The sustainable use of tropical coastal resources- a key conservation issue. Ambio 22(7), 481-482.

Islam KK, Sato N. 2012. Deforestation, land conversion and illegal logging in Bangladesh: the case of the Sal (Shorea robusta) forests”, iForest 5, 171-178.

Ismail MH, Zaki PH, Khairunnesa N. 2011. Remote Sensing for Mapping RAMSAR Heritage Site at Sungai Pulai Mangrove Forest Reserve, Johore, Malaysia. J. Sains Malaysiana 40(2), 83-88.

Liang S, Fang H, Chen M. 2001. Atmospheric correction of Landsat ETM+ land surface imagery. I. Methods. IEEE Transactions on geoscience and remote sensing 39(11), 2490-2498.

Mallick SK. 2021. Prediction-Adaptation-Resilience (PAR) approach- A new pathway towards future resilience and sustainable development of urban landscape. Geography and Sustainability 2, 127-133.

NASA. 2008. Landsat data continuing mission [online]. URL: http://Idem.nasa.gov/index.htm [Accessed 05 Jan 2009].

Peijun DU, Xingli LI, Wen CAO, Yan LUO, Zhang H. 2010. Monitoring urban land cover and vegetation change by multi-temporal remote sensing information. Mining Science and Technology (China) 20(6), 922-932.

Rahman MM, Motiur MR, Guogang Z, Islam KS. 2010. A review of the present threats to tropical moist deciduous Sal (Shorea robusta) forest ecosystem of central Bangladesh”, Tropical Conserv. Sci 3(1), 90-102.

Rahman MM. 2003. Sal Forest, In: Islam S, Miah S (eds.) Banglapedia: National Encyclopedia of Bangladesh, Vol. 9. Asiatic Society of Bangladesh, Dhaka pp. 28-29.

Sarmin NS, Ismail MH, Pakhriazad HZ, Khairil WA, Mohamad Roslan MK. 2017b. Deforestation awareness among the community living near mangroves in mukim Tanjung Kupang, Johor, Malaysia. Science International, ISSN: 1013-5316, 29(2), 115-119.

Sarmin NS, Ismail MH, Pakhriazad HZ, Khairil WA. 2017a. Change detection of Sungai Pulai mangroves and other land cover at mukim level by Landsat imageries in Sungai Pulai, Johor, Malaysia. The Malaysian Forester, ISSN: 0302-2935, 80(1), 31-42.

Sarmin NS, Ismail MH, Zaki PH, Khairil WA, Ash Shidiq IP. 2016b. Land cover dynamics of Sungai Pulai mangrove forest using remote sensing and GIS- preliminary results. Journal of Engineering and Applied Sciences 11(3), 441-445.

Sarmin NS, Ismail MH. 2016a. A review of potentialities and challenges of integrating remote sensing and GIS with socio-economic data. Pertanika Journal of Scholarly Research Reviews 2(1), 129-141.

Turner BL, Skole B, Sanderson S, Fischer G, Fresco L, Leemans R. 1995. Land-Use and Land-Cover Change: Science Research Plan. IGBP Report, 35. IGBP, Stockholm 132.

Wang J, Ji W. 2012. Spatial-temporal pattern analysis of land use change in Dehua county of China from remote sensing images. National Natural Science Foundation of China (Grant no. 41101543/D011103), 987-1-4673-0875-5/12/$31.00©2012 IEEE.

Weng Q. 2002. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. Journal of Environmental Management 64, 273-284.

Zafar TB, Ding W, Din SU, Khan GM, Hao C. Forest cover and land use map of the Chunati Wildlife Sacntuary based on participatory mapping and satellite images: Insight into Chunati beat. Land Use Policy 103(2021), 105193.

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