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Forest Land Analysis using Normalized Difference Vegetation Index (NDVI): A Case Study of Bangladesh

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Mohammed Shafiul Alam Khan, Md. Ismail Rahman

Mohammed Shafiul Alam Khan and Md. Ismail Rahman. Forest Land Analysis using Normalized Difference Vegetation Index (NDVI): A Case Study of Bangladesh. International Journal of Computer Applications 183(45):15-19, December 2021. BibTeX

	author = {Mohammed Shafiul Alam Khan and Md. Ismail Rahman},
	title = {Forest Land Analysis using Normalized Difference Vegetation Index (NDVI): A Case Study of Bangladesh},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2021},
	volume = {183},
	number = {45},
	month = {Dec},
	year = {2021},
	issn = {0975-8887},
	pages = {15-19},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2021921855},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


It is no longer a secret that Bangladesh is an innocent victim of climate change. Because of climate change, every year the inhabitants of Bangladesh are suffering a lot from the loss of life and property. Various researches, magazines and journals state that Bangladesh is one the most vulnerable nations to the impacts of climate change. Deforestation is the main reason for climate change and global warming. To address the issue, a detailed study of the country’s forestation changes and its impact to the prevention of climate change would be helpful. To do so, Landsat 8 dataset images, collected from USGS satellite image dataset, are analyzed, and a model is proposed to detect the changes of forestation between years. The proposed modelhelps to predict the forestation changes in near future and support to take necessary measures to reduce deforestation. Supervised classification and machine learning algorithm are used to implement the model.


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Supervised classification, Google Earth Engine, Bangladesh forest land change analysis, NDVI, CART, satellite image dataset