Applied Ecology and Forestry Science
ISSN (Print): ISSN Pending ISSN (Online): ISSN Pending Website: https://www.sciepub.com/journal/aefs Editor-in-chief: Romeo Ekoungoulou
Open Access
Journal Browser
Go
Applied Ecology and Forestry Science. 2022, 5(1), 14-19
DOI: 10.12691/aefs-5-1-3
Open AccessArticle

Relationship Analysis between Rainfall and Vegetation Cover in Vaigai Dam Reserve Forest, Tamil Nadu, India Using GEE

Rajmohan Ramamoorthy1, Radhakrishnan Thulasi1 and Manimekalan Arunachalam1,

1Department of Environmental Sciences, Bharathiar University, India

Pub. Date: November 02, 2022

Cite this paper:
Rajmohan Ramamoorthy, Radhakrishnan Thulasi and Manimekalan Arunachalam. Relationship Analysis between Rainfall and Vegetation Cover in Vaigai Dam Reserve Forest, Tamil Nadu, India Using GEE. Applied Ecology and Forestry Science. 2022; 5(1):14-19. doi: 10.12691/aefs-5-1-3

Abstract

Climatic factors are the most important factor for vegetation changes on the earth's surface. The objective of the study is the application of modern scientific tools such as remote sensing to analyze the vegetation changes over a year concerning climatic changes (2005-2020). The Landsat 5, 7 and 8 satellite image was utilized which was obtained from the Google earth engine for studying vegetation changes. The main type of vegetation changes studied in the study area is high vegetation, moderate vegetation, low vegetation, and barren land. Earth engine was used for NDVI classification of the study area in periods of 2005-2020 and collected rainfall data of respective years from the meteorological lab. An ArcGIS software tool was used to acquire the shapefile from the Survey of India Topo sheet. Correlation analysis between the rainfall and vegetation changes will help to conserve nature and reclamation activities in the study area.

Keywords:
ArcGIS change detection correlation Google earth engine NDVI remote sensing

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  P. Yadav, P. K. Yadav, M. Kapoor, and K. Sarma, “Land Use Land Cover Mapping, Change Detection and Conflict Analysis of Nagzira-Navegaon Corridor, Central India... Land Use Land Cover Mapping, Change Detection and Conflict Analysis of Nagzira-Navegaon Corridor, Central India Using Geospatial Technology,” International Journal of Remote Sensing and GIS, vol. 1, no. 2, pp. 90-98, 2012, Accessed: Sep. 17, 2022. [Online]. Available: www.rpublishing.org.
 
[2]  P. S. Roy and A. Giriraj, “Land Use and Land Cover Analysis in Indian Context,” Journal of Applied Sciences, vol. 8, no. 8, pp. 1346-1353, Apr. 2008.
 
[3]  P. Dash, “Land surface temperature and emissivity retrieval from satellite measurements,” 2005.
 
[4]  M. Pfeifer, M. Disney, T. Quaife, and R. Marchant, “Terrestrial ecosystems from space: a review of earth observation products for macroecology applications,” Global Ecology and Biogeography, vol. 21, no. 6, pp. 603–624, Jun. 2012.
 
[5]  A. Shalaby and R. Tateishi, “Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt,” Applied Geography, vol. 27, no. 1, pp. 28-41, Jan. 2007.
 
[6]  P. Defourny et al., “Accuracy Assessment of a 300 m Global Land Cover Map: The GlobCover Experience CIRAD-Guyane-Université Laval”.
 
[7]  D. Potere and A. Schneider, “A critical look at representations of urban areas in global maps,” GeoJournal, vol. 69, no. 1-2, pp. 55-80, Jun. 2007.
 
[8]  A. M. Dewan and Y. Yamaguchi, “Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization,” Applied Geography, vol. 29, no. 3, pp. 390-401, Jul. 2009.
 
[9]  P. M. Mather and M. Koch, Computer Processing of Remotely-Sensed Images. Wiley, 2011.
 
[10]  M. Amiri and H. R. Pourghasemi, “Mapping the NDVI and monitoring of its changes using Google Earth Engine and Sentinel-2 images,” Computers in Earth and Environmental Sciences, pp. 127-136, Jan. 2022
 
[11]  S. Ezaidi et al., “Multi-temporal Landsat-derived NDVI for vegetation cover degradation for the period 1984-2018 in part of the Arganeraie Biosphere Reserve (Morocco),” Remote Sens Appl, vol. 27, p. 100800, Aug. 2022.
 
[12]  S. Garai et al., “Assessing correlation between Rainfall, normalized difference Vegetation Index (NDVI) and land surface temperature (LST) in Eastern India,” Safety in Extreme Environments, vol. 4, no. 2, pp. 119-127, Aug. 2022.
 
[13]  S. L. Savage et al., “Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager,” Forests 2018, Vol. 9, Page 157, vol. 9, no. 4, p. 157, Mar. 2018.