Measuring of Deforestation Rate Using Pixel Based Approach

  • Anand Malik Associate Professor, Geography, SSN College (University of Delhi), Delhi.
  • Surya Kant Pandey
  • Harish Kumar
Keywords: Deforestation, Land use and land cover change, Verified Carbon Standard (VCS), Pixel


Land use and land cover change is an essential part in understanding the interaction of the human exercises with the environmental Changes in the forest cover and the degradation of the forest has been seen as a result of the expanding populace weight and mechanical revolution. Deforestation has numerous natural, social and financial outcomes, for example, loss of organic assorted variety, decline in the carbon sequestration by the woods consequently expanded barometrical CO2 fixation and some more. The present study focuses on the calculating the deforestation rate in a selected landscape of Madhya Pradesh utilizing pixel based approach. Main objective of the study is analysis the deforestation rate in Hoshangabad and Harda area of Madhya Pradesh and test the significance of Verified Carbon Standard (VCS) Methodology utilizing pixel based approach. A pixel has been the essential unit of picture examination and change location procedures since the early utilization of remote detecting information. The paper present the overview of using landscape pixel based approach for investigation deforestation rate. The investigation has use remote detecting framework and GIS techniques to measure changes in forest cover and guide examples of deforestation in Madhya Pradesh for the period of 2003-2014.


Ceccarelli, T., Smiraglia, D., Bajocco, S., Rinaldo, S., De Angelis, A., Salvati, L. and Perini, L. (2013). Land cover data from Landsat single-date imagery: an approach integrating pixel-based and object-based classifiers. European Journal of Remote Sensing, 46(1), pp.699-717.
Chape, S., Harrison, J., Spalding, M. and Lysenko, I. (2005). Measuring the extent and effectiveness of protected areas as an indicator for meeting global biodiversity targets. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1454), pp.443-455.
Food and Agriculture Organization (1997). State of the world’s forests Report. Forestry department, Rome: United Nations.
Food and Agriculture Organization (2007). Manual on Deforestation, Degradation, and Fragmentation Using Remote Sensing. Forestry Department, Rome: United Nations.
Food and Agriculture Organization (2012). State of the world’s forests Report. Forestry department, Rome: United Nations.
Forest Survey of India (2009). India State of Forest Report. Ministry of Environment and Forests (MoEF), Government of India.
Gajbhiye, S. and Sharma, S. (2012). Land Use and Land Cover change detection of Indra river watershed through Remote Sensing using Multi-Temporal satellite data. International Journal of Geomatics and Geosciences, 3(1), ISSN: 0976 – 4380, pp.89-96.
Kumar, N., Gurugnanam, B. and Arulbalaji, K. (2015). Land Use and Land Cover Change Detection in Thirumanimuttar Sub Basin Cauvery River Tamilnadu. International Journal of Science, Engineering and Technology Research, 4(4), ISSN: 2278 – 7798 pp.680-683.
Hussain, M., Chen, D., Cheng, A., Wei, H. and Stanley, D. (2013). Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS Journal of Photogrammetry and Remote Sensing, 80, pp.91-106.
Lu, D., Chen, Q., Wang, G., Liu, L., Li, G. and Moran, E. (2014). A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems. International Journal of Digital Earth, [online] 9(1), pp.63-105. Available at:
Mishra, A. (2012). Land use / Land cover Mapping of Chhatarpur District, Madhya Pradesh, India Using Unsupervised Classification Technique. IOSR Journal of Engineering, 02(10), pp.51-56.
Murai, S. (Eds.). (1995). Development of global eco-engineering using remote sensing and geographic information systems. In Towards Global Planning of the Sustainable Use of the Earth Resources, Proceedings of 8th Toyota Conference.
Myers, N. (1993). Tropical Forests: The Main Deforestation Fronts. Environmental Conservation, 20(01), p.9.
NASA (1998). Tropical deforestation. NASA facts, FS-1998-11-120- GSFC, National Aeronautics and Space Administration, Goddard Space Flight Center.
Petrescu, A., Abad-Viñas, R., Janssens-Maenhout, G., Blujdea, V. and Grassi, G. (2012). Global estimates of carbon stock changes in living forest biomass: EDGARv4.3 – time series from 1990 to 2010. Biogeosciences, [online] 9(8), pp.3437-3447. Available at:
Skole, D. and Tucker, C. (1993). Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988. Science, 260(5116), pp.1905-1910.
Tagore, G., Bairagi, G., SHARMA, N., SHARMA, R., BHELAWE, S. and VERMA, P. (2012). Mapping of Degraded Lands Using Remote Sensing and GIS Techniques. Journal of Agricultural Physics, [online] 12(1), ISSN: 0973-032X, pp.29-36. Available at:
Thompson, I., Guariguata, M., Okabe, K., Bahamondez, C., Nasi, R., Heymell, V. and Sabogal, C. (2013). An Operational Framework for Defining and Monitoring Forest Degradation. Ecology and Society, 18(2).
Tiwari, J., Sharma, S. and Patil, R. (2017). An Integrated Approach of Remote Sensing and Gis for Land Use and Land Cover Change Detection: A Case Study of Banjar River Watershed Of Madhya Pradesh, India. Current World Environment, 12(1), pp.157-164.
Wu, C., Shen, H., Wang, K., Shen, A., Deng, J. and Gan, M. (2016). Landsat Imagery-Based Above Ground Biomass Estimation and Change Investigation Related to Human Activities. Sustainability, 8(2), p.159.