Long Term Vegetation Health Monitoring in Dibru-Saikhowa National Park using Remote Sensing & Gis
Sujata Medhi1, Sourav Chetia2, Syeda Fahima Shahnaz Sultana3, Kasturi Borkotoky4, Ashok KumarBora5
1Sujata Medhi*, Department of Geography, Gauhati University, Guwahati, India.
2Sourav Chetia, Department of Geography, Gauhati University, Guwahati, India.
3Syeda Fahima Shahnaz Sultana*, Department of Geography, Gauhati University, Guwahati, India.
4Kasturi Borkotoky, Department of Geography, Gauhati University, Guwahati, India.
5Ashok Kumar Bora, Department of Geography, Gauhati University, Guwahati, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on April 10, 2020. | PP: 1901-1906 | Volume-9 Issue-6, April 2020. | Retrieval Number: F4747049620/2020©BEIESP | DOI: 10.35940/ijitee.F4747.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Remote sensing and GIS based vegetation monitoring offers lot of potential for ecosystem studies. This study utilized freely available moderate resolution Landsat images to quantify the changes in vegetation dynamics in Dibru-Saikhowa national park, India. A wide range of vegetation indices and temperature indices such as normalized difference vegetation index (NDVI), land surface temperature (LST), vegetation condition index (VCI), temperature condition index (TCI) and vegetation health index (VHI) was utilized for the purpose of the study. Results reveal that the study area has gone through changes in vegetation and temperature pattern affecting the land surface balances. The maximum NDVI value for the year 1996 was recorded between 0.5-0.8 whereas the maximum LST values ranged between 17.240C-34.850C. In 2019, the maximum NDVI values reduced to the range of 0.14-0.6 while LST increased to 18.950C-38.910C. Consequently, the VHI classes showed a negative trend. In 1996, healthy vegetation covered a total area of 14564.6 ha which reduced to 9872.1 ha in 2019. Conversely, the no vegetation class showed a significant positive trend from 951.3 ha to 3015.99. Such alteration in vegetation dynamics in the study area is affecting the local climate and regional ecosystem services and require instant attention of conservationist and policy makers.
Keywords: Lst, Ndvi , Tci , Vci, Vegetation Dynamics, Vhi.
Scope of the Article: Health Monitoring and Life Prediction of Structures