Detection of vegetation cover change in the Southern region of Bangladesh using the Normalized Difference Vegetation Index (NDVI) and Climate Smart Agriculture (CSA) practices
Article Main
Abstract
Bangladesh is extremely vulnerable to climate change, and vegetation indices serve as sensitive indicators. Due to the impacts of climate change, the cropping intensity of Southern region of Bangladesh is very low. So, this study aimed to analyze the changes in vegetation cover over time using the Normalized Difference Vegetation Index (NDVI) and identify the use of Climate Smart Agriculture (CSA) technologies and the benefits of using such technologies. A questionnaire survey was carried out by purposive random sampling method to detect 120 farmers’ socioeconomic status, hazards faced by climate change, adopted climate smart agricultural practices and its benefits for assessing Adaptive Strategy Index (ASI) in Amtali upazila of Barguna district and Kalapara upazila of Patuakhali district. NDVI analysis of multi-spectral remote sensing data from 2012 and 2022 indicated the extent of sparse vegetation of Kalapara has increased. Western part of Amtali upazila, fallow areas have become lessened in 2022 (354.55 km2) compared to 2012 (368.78 km2) due to adopting different CSA practices. Saline-tolerant crop varieties, sunflowers, and watermelon cultivation were the highest ranked among the CSA practices, with 301, 300, and 296 ASI, respectively. Calculated weighted average of CSA practices indicated the reduction of production cost, increased family income (49.19%) and cropping intensity (51.67%), which impacts developed social bonding.
Article Details
Article Details
Keywords
Adaptation Strategy Index (ASI), Climate Change, Climate Smart Agricultural Practices, Normalized Difference Vegetation Index (NDVI), Satellite imagery, Sparse Vegetation
References
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Ali, M. Y. & Hossain, M. E. (2019). Profiling climate smart agriculture for southern coastal region of Bangladesh and its impact on productivity, adaptation and mitigation. EC Agriculture, 5(9), 530-544.
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Chowdhury, M. A., Hasan, M. K. & Islam, S. L. U. (2022). Climate change adaptation in Bangladesh: Current practices, challenges and the way forward. Journal of Climate Change and Health. 6, 981–985. https://doi.org/10.1016/j.joclim.2021.100108
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Gaznayee, A. Heman, A. Al-Quraishi A. M. F., Mahdi, K. & Ritsema, C. (2022). A Geospatial Approach for Analysis of Drought Impacts on Vegetation Cover and Land Surface Temperature in the Kurdistan Region of Iraq. Water, 14(6), 927. https:// doi.org/10.3390/w14060927
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Huyen, N. T., Tu, L. H., Liem, N. D., Tram, V. N. Q., Minh, D. N. & Loi, N. K. (2017). Assessing Impacts of Land Use and Climate Change on Soil and Water Resources in the Srepok Watershed, Central Highland of Vietnam (No. 2017–2; Agriculture and Development Discussion Paper Series). Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA). https://ideas.repec.org/p/sag/seadps/2017342.html.
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Laksono, A., Saputri, A.A., Pratiwi, C.I.B., Arkan, M.Z. & Putri, R.F. (2020). Vegetation covers change and its impact on Barchan dune morphology in parangtritis coast, Indonesia, the 1st geosciences and environmental sciences symposium (ICST), E3S Web Conf. https://doi.org/10.1051/e3sconf/ 202020002026
Leprieur, C., Verstraete, M. M. & Pinty, B. (1994). Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data. Remote Sensing Reviews, 10(4), 265–284. doi: https://doi.org/10.1080/02757259409532250
Lipper, L., Thornton, P., Campbell, B. M., Baedeker, T., Braimoh, A. & Bwalya, M. (2014). Climate-smart agriculture for food security, Nature Climate Change, 4, 1068–1072. doi:10.1038/nclimate2437
Liu, X., Zhu, X., Li, S., Liu, Y. & Pan, Y. (2015). Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012. Remote Sensing, 7(11), 15517–15535. doi: https://doi.org/10.3390/rs71115517
Mahashin, M. (2021). Impact of Climate Smart Agriculture on Farmers’ Livelihoods. A PhD dissertation of the Department of Agricultural Extension and Information System, Sher-e-Bangla Agricultural University, Dhaka -1207.
Mizik, T. (2021). Climate-Smart Agriculture on Small-Scale Farms: A Systematic Literature Review. Agronomy, 11(6), 1096.
Murshed, S.B., Rahman M.R. & Kaluarachchi, J.J. (2019). Changes in hydrology of the Ganges delta of Bangladesh and corresponding impacts on water Resources. Journal of the American Water Resources Association, 55 (4), 800–823. https://doi.org/10.1111/ 1752-1688.12775.
Orimoloye, I.R., Mazinyo, S.P., Kalumba, A., Nel, W., Adigun, A.I. & Ololade, O.O. (2019). Wetland shift monitoring using remote sensing and GIS techniques: landscape dynamics and its implications on Isimangaliso Wetland Park, South Africa. Earth Science Informatics, 12, 553–563. doi. https://doi.org/10.1007/s12145-019-00400-4.
Pantho, M. J., Ishmam, Z. S., Hafiz, A. M.I. & Rahman, M. M. (2022). NDVI: Detection of Vegetation Change Using Remote Sensing and GIS- A Study on Barishal City Corporation, Bangladesh. Proceedings of the 6th International Conference on Civil Engineering for Sustainable Development, 10~12 February 2022, KUET, Khulna, Bangladesh.
Piao, S., Wang, X., Ciais, P., Zhu, B., Wang, T. & Liu, J. (2011). Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006: Change in vegetation growth over Eurasia. Global Change Biology, 17(10), 3228–3239. doi: https://doi.org/10.1111/j.1365-2486.2011.02419.x
Potapov, P., Hansen, M. C., Laestadius, L., Turubanova, S., Yaroshenko, A., Thies, C., Smith, W., Zhuravleva, I., Komarova, A., Minnemeyer, S. & Esipova, E. (2017). The last frontiers of wilderness: Tracking loss of intact forest landscapes from 2000 to 2013. Science Advances, 3(1), e1600821. doi: https://doi.org/10.1126/sciadv.1600821.
Rashid, M. B., Sheik, M. R., Haque, A. J.M.E., Siddique, M. A. B., Habib, M. A. & Patwary, M. A. A. (2023). Salinity-induced change in green vegetation and land use patterns using remote sensing, NDVI, and GIS techniques: A case study on the southwestern coast of Bangladesh. Case Studies in Chemical and Environmental Engineering, 7, 100314. https://doi.org/10.1016/j.cscee.2023.100314
Rahman, M. M. (2013). Temporal Change Detection of Vegetation Coverage in Patuakhali Coastal Area of Bangladesh Using GIS & Remotely Sensed Data. International Journal of Geosciences, 4, 36–46.
Rousvel, S., Armand, N., Andre, L., Tengeleng, S., Alain, T. & Armel, K. (2013). Comparison between Vegetation and Rainfall of Bioclimatic Ecoregions in Central Africa. Atmosphere, 4(4), 411–427. doi:10.3390/atmos4040411
Rukaia, K., Haque, M. A., Khanam, S., Hoque, M. F., Akter, N., Sultana, N. & Mahmud, M. M. (2021). Spatial variability of some chemical properties of soil at Taltali Upazila of Barguna district, Bangladesh. Australian Journal of Science and Technology, 5(1), 2208- 6404.
Sain, G., Loboguerrero, A. M., Corner-Dolloff, C., Lizarazo, M., Nowak, A., Martínez-Barón, D. & Andrieu, N. (2017). Costs and benefits of climate-smart agriculture: The case of the dry corridor in Guatemala. Agricultural Systems, 151, 163–173. https://doi.org/10.1016/j.agsy.2016.05.004
Singh, A.N., Sinha, D.D., Bari, M.A., Ismail, A. & Singh, U.S. (2012). Site Suitability Analysis for Dissemination of Salt-tolerant Rice Varieties in Southern Bangladesh. International Rice Research Institute Bangladesh Office, Dhaka.
Sun, Y., Bricheno, L.M., Payo-Payo, M., Rahman, M.M. & Burns, N.M. (2022). Simulation of freshwater transport network and salt flux in the Bangladesh delta. Estuarine Coastal and Shelf Science, 270, 107839. https://doi.org/10.1016/j.ecss.2022.107839.
Thorat, S. S., Rajendra, Y. D., Kale, K. V. & Mehrotra, S. C. (2015). Estimation of Crop and Forest Areas using Expert System based Knowledge Classifier Approach for Aurangabad District. International Journal of Computers and Applications,121(23), 43-46. https://www.researchgate.net/publication/281953640
Uddin, M. N., Bokelmann, W. & Entsminger, J. S. (2014). Factors Affecting Farmers’ Adaptation Strategies to Environmental Degradation and Climate Change Effects: A Farm Level Study in Bangladesh. Climate. 2(4), 223-241. https://doi.org/10.3390/cli2040223
United States Geological Survey. (2018). NDVI, the Foundation for Remote Sensing Phenology. https://www.usgs.gov/special-topics/remote-sensing-phenology/science/ndvi-foundation-remote-sensing-phenology.
World Bank. (2022). Climate change. https://www.worldbank.org/en/topic/climatechange/overview
Yamane, Taro (1967). Statistics, An Introductory Analysis, 2nd Ed., New York: Harper and Row.
Zerssa, G., Feyssa, D. & Kim, D. (2021). Challenges of Smallholder Farming in Ethiopia and Opportunities by Adopting Climate-Smart Agriculture. Journal of Agri culture, 11(3), 192. https://doi.org/10.3390/agriculture11030192
Ajij, M., Haidar, M. L. & Rahman, M. M. (2014). Climate field school (CFS) training module. Dhaka: Disaster and Climate Risk Management Project in Agriculture Project, Department of Agricultural Extension, Dhaka. http://www.dae.gov.bd/site/page/168dad4b-851f-4669-9cd1-bb215e70c66f/Climate-Field-School-Training-Module.
Alex, C.A., Ramesh, K.V. & Hari, S. (2017). Quantification and understanding the observed changes in land cover patterns in Bangalore. International Journal of Civil Engineering and Technology, 8 (4), 597–603.
Ali, M.S. (2008). Adoption of selected ecological Agricultural practices by the farmers. A PhD dissertation of the Department of Agricultural Extension Education, Bangladesh Agriculture University Mymensingh.
Ali, M. Y. & Hossain, M. E. (2019). Profiling climate smart agriculture for southern coastal region of Bangladesh and its impact on productivity, adaptation and mitigation. EC Agriculture, 5(9), 530-544.
Bangladesh Bureau of Statistics (BBS) (2022). Population and Housing Census. Planning Division, Ministry of Planning, Government of the People’s Republic of Bangladesh, Dhaka.
Chowdhury, M. A., Hasan, M. K. & Islam, S. L. U. (2022). Climate change adaptation in Bangladesh: Current practices, challenges and the way forward. Journal of Climate Change and Health. 6, 981–985. https://doi.org/10.1016/j.joclim.2021.100108
FAO. (2013). Climate-smart agriculture sourcebook. Rome: Food and Agriculture Organization of the United Nations.
Gao, B.C. (1996). NDWI-a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257–266. https://doi.org/10.1016/S0034-4257(96)00067-3
Gaznayee, A. Heman, A. Al-Quraishi A. M. F., Mahdi, K. & Ritsema, C. (2022). A Geospatial Approach for Analysis of Drought Impacts on Vegetation Cover and Land Surface Temperature in the Kurdistan Region of Iraq. Water, 14(6), 927. https:// doi.org/10.3390/w14060927
Hasan, M. K., Desiere, S., D’Haese, M. & Kumar, L. (2018). Impact of climate-smart agriculture adoption on the food security of coastal farmers in Bangladesh. Food Science, 10, 1073–1088. doi: 10.1007/s12571-018-0824-1
Hasan, M.K. & Kumar, L. (2019). Comparison between meteorological data and farmer perceptions of climate change and vulnerability in relation to adaptation. Journal of Environmental Management, 237, 54–62. https://doi.org/10.1016/j.jenvman.2019.02.028
Huyen, N. T., Tu, L. H., Liem, N. D., Tram, V. N. Q., Minh, D. N. & Loi, N. K. (2017). Assessing Impacts of Land Use and Climate Change on Soil and Water Resources in the Srepok Watershed, Central Highland of Vietnam (No. 2017–2; Agriculture and Development Discussion Paper Series). Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA). https://ideas.repec.org/p/sag/seadps/2017342.html.
Islam, M. & Mamun, M.M.I. (2015). Variation of NDVI and Its association with rainfall and Evapotranspiration over Bangladesh. International Conference on Materials, Electronics and Information Engineering, ICMEIE, Faculty of Engineering, University of Rajshahi, Bangladesh. www.ru.ac.bd/icmeie2015/proceedings/
Islam, M.S., Yeasmin, T. Karmaker, S., Shakhawat, M.H. & Shi, L. (2023). Vegetation Cover Change Analysis during 1989-2020 of Coastal Barguna District, Bangladesh Using remote Sensing and Technology. International review for spatial planning and sustainable development D: Planning Assessment, 11(2), 259-277. https://creativecommons.org/licenses/by-nc-nd/4.0/
Jia, K., Liang, S., Zhang, N., Wei, X., Gu, X., Zhao. X., Yao, Y. & Xie, X. (2014). Land cover classification of finer resolution remote sensing data integrating temporal features from time series coarser resolution data, ISPRS. Journal of Photogrammetry and Remote Sensing, 93, 49–55. doi: 10.1016/j.isprsjprs.2014.04.004
Kabir, A., Hasan, M. M., Ahmed, B. & Islam, S. (2020). Climate Change Perception and Adaptation Strategies of Southwest Coastal Bangladesh. American Journal of Science, Engineering and Technology, 66 (1), 47-68.
Laksono, A., Saputri, A.A., Pratiwi, C.I.B., Arkan, M.Z. & Putri, R.F. (2020). Vegetation covers change and its impact on Barchan dune morphology in parangtritis coast, Indonesia, the 1st geosciences and environmental sciences symposium (ICST), E3S Web Conf. https://doi.org/10.1051/e3sconf/ 202020002026
Leprieur, C., Verstraete, M. M. & Pinty, B. (1994). Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data. Remote Sensing Reviews, 10(4), 265–284. doi: https://doi.org/10.1080/02757259409532250
Lipper, L., Thornton, P., Campbell, B. M., Baedeker, T., Braimoh, A. & Bwalya, M. (2014). Climate-smart agriculture for food security, Nature Climate Change, 4, 1068–1072. doi:10.1038/nclimate2437
Liu, X., Zhu, X., Li, S., Liu, Y. & Pan, Y. (2015). Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012. Remote Sensing, 7(11), 15517–15535. doi: https://doi.org/10.3390/rs71115517
Mahashin, M. (2021). Impact of Climate Smart Agriculture on Farmers’ Livelihoods. A PhD dissertation of the Department of Agricultural Extension and Information System, Sher-e-Bangla Agricultural University, Dhaka -1207.
Mizik, T. (2021). Climate-Smart Agriculture on Small-Scale Farms: A Systematic Literature Review. Agronomy, 11(6), 1096.
Murshed, S.B., Rahman M.R. & Kaluarachchi, J.J. (2019). Changes in hydrology of the Ganges delta of Bangladesh and corresponding impacts on water Resources. Journal of the American Water Resources Association, 55 (4), 800–823. https://doi.org/10.1111/ 1752-1688.12775.
Orimoloye, I.R., Mazinyo, S.P., Kalumba, A., Nel, W., Adigun, A.I. & Ololade, O.O. (2019). Wetland shift monitoring using remote sensing and GIS techniques: landscape dynamics and its implications on Isimangaliso Wetland Park, South Africa. Earth Science Informatics, 12, 553–563. doi. https://doi.org/10.1007/s12145-019-00400-4.
Pantho, M. J., Ishmam, Z. S., Hafiz, A. M.I. & Rahman, M. M. (2022). NDVI: Detection of Vegetation Change Using Remote Sensing and GIS- A Study on Barishal City Corporation, Bangladesh. Proceedings of the 6th International Conference on Civil Engineering for Sustainable Development, 10~12 February 2022, KUET, Khulna, Bangladesh.
Piao, S., Wang, X., Ciais, P., Zhu, B., Wang, T. & Liu, J. (2011). Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006: Change in vegetation growth over Eurasia. Global Change Biology, 17(10), 3228–3239. doi: https://doi.org/10.1111/j.1365-2486.2011.02419.x
Potapov, P., Hansen, M. C., Laestadius, L., Turubanova, S., Yaroshenko, A., Thies, C., Smith, W., Zhuravleva, I., Komarova, A., Minnemeyer, S. & Esipova, E. (2017). The last frontiers of wilderness: Tracking loss of intact forest landscapes from 2000 to 2013. Science Advances, 3(1), e1600821. doi: https://doi.org/10.1126/sciadv.1600821.
Rashid, M. B., Sheik, M. R., Haque, A. J.M.E., Siddique, M. A. B., Habib, M. A. & Patwary, M. A. A. (2023). Salinity-induced change in green vegetation and land use patterns using remote sensing, NDVI, and GIS techniques: A case study on the southwestern coast of Bangladesh. Case Studies in Chemical and Environmental Engineering, 7, 100314. https://doi.org/10.1016/j.cscee.2023.100314
Rahman, M. M. (2013). Temporal Change Detection of Vegetation Coverage in Patuakhali Coastal Area of Bangladesh Using GIS & Remotely Sensed Data. International Journal of Geosciences, 4, 36–46.
Rousvel, S., Armand, N., Andre, L., Tengeleng, S., Alain, T. & Armel, K. (2013). Comparison between Vegetation and Rainfall of Bioclimatic Ecoregions in Central Africa. Atmosphere, 4(4), 411–427. doi:10.3390/atmos4040411
Rukaia, K., Haque, M. A., Khanam, S., Hoque, M. F., Akter, N., Sultana, N. & Mahmud, M. M. (2021). Spatial variability of some chemical properties of soil at Taltali Upazila of Barguna district, Bangladesh. Australian Journal of Science and Technology, 5(1), 2208- 6404.
Sain, G., Loboguerrero, A. M., Corner-Dolloff, C., Lizarazo, M., Nowak, A., Martínez-Barón, D. & Andrieu, N. (2017). Costs and benefits of climate-smart agriculture: The case of the dry corridor in Guatemala. Agricultural Systems, 151, 163–173. https://doi.org/10.1016/j.agsy.2016.05.004
Singh, A.N., Sinha, D.D., Bari, M.A., Ismail, A. & Singh, U.S. (2012). Site Suitability Analysis for Dissemination of Salt-tolerant Rice Varieties in Southern Bangladesh. International Rice Research Institute Bangladesh Office, Dhaka.
Sun, Y., Bricheno, L.M., Payo-Payo, M., Rahman, M.M. & Burns, N.M. (2022). Simulation of freshwater transport network and salt flux in the Bangladesh delta. Estuarine Coastal and Shelf Science, 270, 107839. https://doi.org/10.1016/j.ecss.2022.107839.
Thorat, S. S., Rajendra, Y. D., Kale, K. V. & Mehrotra, S. C. (2015). Estimation of Crop and Forest Areas using Expert System based Knowledge Classifier Approach for Aurangabad District. International Journal of Computers and Applications,121(23), 43-46. https://www.researchgate.net/publication/281953640
Uddin, M. N., Bokelmann, W. & Entsminger, J. S. (2014). Factors Affecting Farmers’ Adaptation Strategies to Environmental Degradation and Climate Change Effects: A Farm Level Study in Bangladesh. Climate. 2(4), 223-241. https://doi.org/10.3390/cli2040223
United States Geological Survey. (2018). NDVI, the Foundation for Remote Sensing Phenology. https://www.usgs.gov/special-topics/remote-sensing-phenology/science/ndvi-foundation-remote-sensing-phenology.
World Bank. (2022). Climate change. https://www.worldbank.org/en/topic/climatechange/overview
Yamane, Taro (1967). Statistics, An Introductory Analysis, 2nd Ed., New York: Harper and Row.
Zerssa, G., Feyssa, D. & Kim, D. (2021). Challenges of Smallholder Farming in Ethiopia and Opportunities by Adopting Climate-Smart Agriculture. Journal of Agri culture, 11(3), 192. https://doi.org/10.3390/agriculture11030192
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Detection of vegetation cover change in the Southern region of Bangladesh using the Normalized Difference Vegetation Index (NDVI) and Climate Smart Agriculture (CSA) practices. (2024). Journal of Applied and Natural Science, 16(1), 435-444. https://doi.org/10.31018/jans.v16i1.5398
