Monitoring Land Use and Land Cover Change of Forest Ecosystems of Shendurney Wildlife Sanctuary, Western Ghats, India
Asian Journal of Environment & Ecology,
Understanding forest degradation due to human and natural phenomena is crucial to conserving and managing remnant forest resources. However, forest ecosystem assessment over a large and remote area is usually complex and arduous. The present study on land use and land cover change detection of the Shendurney Wildlife Sanctuary forest ecosystems was carried out to utilize the potential application of remote sensing (RS) and geographic information system (GIS). Moreover, to understand the trend in the forest ecosystem changes. The supervised classification with Maximum Likelihood Algorithm and change detection comparison approach was employed to study the land use and land cover changes, using the Landsat Enhanced Thematic Mapper (ETM±) and Landsat 8 OLI-TIRS using data captured on July 01, 2001, and January 14, 2018. The study indicated the rigorous land cover changes. It showed a significant increase in the proportion of degraded forest with negligible gain in the proportion of evergreen forest from 21.31% in 2001 to 22.97% in 2018. A substantial loss was also observed in moist deciduous from 27.11 % in 2001 to 17.23 % in 2018. The result of the current study indicated the degree of impacts on forests from the various activities of their surroundings. This study provides baseline information for planning and sustainable management decisions.
- Land use and land cover
- change detection
- forest ecosystem
- forest degradation
How to Cite
Benz UC, Hofmann P, Willhauck G, Lingenfelder I, Heynen M. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS J. Photogramm. Remote Sens. 2004;58(3-4):239- 258.
Ellenberg D, Mueller-Dombois D. Aims and methods of vegetation ecology. New York: Wiley; 1974.
Wallace J, Behn G, Furby S. Vegetation condition assessment and monitoring from sequences of satellite imagery. Ecol. Manag. Restor. 2006;7:31-S36.
Anderson JR. A land use and land cover classification system for use with remote sensor data. US Government Printing Office. 1976;964.
Richards JA, Richards JA. Remote sensing digital image analysis Berlin: Springer. 1999;3:10-38.
Congalton RG, Green K. Assessing the Accuracy of Remotely Sensed Data: Principles and Practicesboca Rotan. Lewis Publishers, Florida; 1999.
Jensen JR. "Digital Change Detection” Introductory digital image processing: a remote sensing perspective. Prentice-Hall, New Jersey; 2004.
Mallupattu PK, Sreenivasula Reddy JR. Analysis of land use/land cover changes using remote sensing data and GIS at an Urban Area, Tirupati, India. Sci. World J. 2013;6.
Roy PS, Kaul RN, Sharma Roy MR, Garbyal SS. Forest-type stratification and delineation of shifting cultivation areas in the eastern part of Arunachal Pradesh using LANDSAT MSS data. International Journal of Remote Sensing. 1985;6(3-4): 411-418.
Kushwaha SPS, Madhavan Unni NV. Hybrid interpretation for tropical forest classification. Asian-Pacific Remote Sensing J. 1989;1(2):69-75.
Panigrahy RK, Kale MP, Dutta U, Mishra A, Banerjee B, Singh S. Forest cover change detection of Western Ghats of Maharashtra using satellite remote sensing based visual interpretation technique. Current Science. 2010;98(5):657-664.
Dutta K, Reddy CS, Sharma S, Jha CS. Quantification and monitoring of forest cover changes in Agasthyamalai Biosphere Reserve, Western Ghats, India (1920–2012). Current Science. 2016; 110(4):508-520.
Kale MP, Chavan M, Pardeshi S, Joshi C, Verma PA, Roy PS, Srivastav SK, Srivastava VK, Jha AK, Chaudhari S, Giri Y. Land-use and land-cover change in Western Ghats of India. Environ. Monit. Assess. 2016;188(7):1-23.
Reddy CS, Jha CS, Dadhwal VK. Assessment and monitoring of long-term forest cover changes (1920–2013) in Western Ghats biodiversity hotspot. Journal of Earth System Science. 2016; 125(1):103-114.
Kushwaha SPS. Forest-type mapping and change detection from satellite imagery. ISPRS J. Photogramm. Remote Sens. 1990;45(3):175-181.
FAO. Global forest resources assessment 2000: main report. FAO forestry paper 140, Food and Agriculture Organization, Rome, Italy; 2001.
Kim M, Madden M, Warner TA. Forest type mapping using object-specific texture measures from multispectral Ikonos imagery. Photogramm. Eng. Remote Sensing. 2009;75(7):819-829.
Curran LM, Trigg SN, McDonald AK, Astiani D, Hardiono YM, Siregar P, Caniago I, Kasischke E. Lowland forest loss in protected areas of Indonesian Borneo. Science. 2004;303(5660):1000-1003.
Lira PK, Tambosi LR, Ewers RM, Metzger JP. Land-use and land-cover change in Atlantic Forest landscapes. For. Ecol. Manag. 2012;278:80-89.
Torahi AA, Rai SC. Land cover classification and forest change analysis, using satellite imagery-a case study in Dehdez area of Zagros Mountain in Iran. J. Geogr. Inf. Syst. 2011;3(01):1.
Ewers RM, Didham RK. Confounding factors in the detection of species responses to habitat fragmentation. Biol. Rev. 2006;81:117–142.
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