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NDVI An Indicator of Forest Cover Change Detection: A Geospatial Study on Chunati Forest Beat Areas, Chittagong, Bangladesh

Biswajit Nath

Abstract


Chunati Forest Beat Areas (CFBA) consisting of seven reserved forest (RF) blocks/beats of hill forests is located in the countries south-eastern region is facing deforestation problem due to extensive logging and encroachment. Geospatial technology in combination with Remote Sensing and Geographical Information System (GIS) can be used to assess the change of vegetation cover of Chunati Forest Areas. For this study, false color composite of band 4, 3, and 2 was applied for the Multispectral Landsat imageries (TM) of the year 1989, 2001, and 2010. NDVI was performed in the total forest beat areas (11567.79 hectare) to detect percentage areas of vegetation cover change. Three different time periods NDVI maps were generated and quantitative data were classified using ERDAS Imagine and ArcGIS 10v software respectively. Afterwards NDVI derived maps of 1989 and 2010 were crossed to generate the overall change detection map. This study reveals that vegetation cover of the CFBA has changed significantly during 1989–2010. The main change observed for the time period of 2001–2010 was that the hills with highly dense forest is in decrease state (48.62%) and moderate forest is some decrease (42.85%). The Forest Beat areas need special protection because forest cover is decreasing and some decreasing at the rate of 2.31% and 2.04% per year respectively.

 

Cite this Article
Nath B. NDVI. An Indicator of Forest Cover Change Detection: A Geospatial Study on Chunati Forest Beat Areas, Chittagong, Bangladesh. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(1): 5–18p.


Keywords


NDVI, forest cover change, Chunati forest beat, geospatial, Bangladesh

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References


Hoffer RM. Biological and Physical considerations in Applying Computer-aided analysis techniques to Remote sensor data, In Remote Sensing: The quantitative approach, edited by P. H. Swam and S.M. Davis Mc Graw-Hill.; U.S.A., 1978.

Singh A. Review Article: Digital Change Detection Techniques using Remotely Sensed Data. International Journal of Remote Sensing. 1989; 10: 989–1003p.

Sarma VVLN, Krishna GM, Malini, et al. Land Use/Land Cover Change detection through remote sensing and its climatic implications in the Godavari Delta region. J. Ind. Soc. Rem. Sensing. 2001; 29: 86–91p.

Demgiz, Orhan., Tugrul, et al. Soil erosion assessment using geographical information system (GIS) and remote sensing (RS) study from Ankara-Guvenc Basin, Turkey. J. Environ. Biol. 2009; 30: 339–44p.

Murali KS, Murthy IK, Ravundranath H. Joint Forest Management in India and its ecological impacts. Environment Management Health. 2002; 13: 512–28p.

Chuvieco E. El factor temporal enteledeteccio´n: evolutio´nfenomenolo´gica y ana´lisis de cambio. Revista de Teledeteccio´n. 1998; 10: 1–9p.

Tovar CLM. NDVI as indicator of Degradation. Unasylva. 2012; 62: 238p. Available at: www.fao.org/docrep/o 15/i2560e/i2560e07.pdf; accessed on 14–03–2014.

Campbell JB. Introduction to Remote Sensing. The Guilford Press, New York, 1987.

Lillesand TM, Keifer RW. Remote Sensing and Image Interpretation; John Wiley and Sons, New York, 1979, 1994 and 2000.

Reddy AM. Textbook of Remote Sensing and Geographical Information Systems; 3rd Edition, BS Publications, Hyderabad, India, 2006, 191–3p.

Morawaitz Dana F, Blewett, Tina M, et al. Using NDVI to Assess Vegetation Land Cover Change in Central Puget Sound. Environmental monitoring and Assessment. 2006; 114(1–3): 85–106p.

Tarpley JD, Schneider SR, Money RL. Global Vegetation Indices from the NOAA-7 Meteorological Satellite. J. Clim. Appl. Meteor. 1984; 23: 491–94p.


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