Journal of Environmental Biology

A multiscale analysis and classification of normalized

difference vegetation index value method in Kannad Taluka, Aurangabad District, using remote sensing and GIS

E.M. Garoon and M.B. Mule*

Department of Environmental Science, Dr. Babasaheb Ambedkar Marathawda University, Aurangabad-431 001, India

*Corresponding Author Email : mahadeo.mule@gmail.com                  *ORCiD: https://orcid.org/0000-0002-9028-8348

Received: 17.05.2022                                                                                         Revised: 05.07.2022                                                              Accepted: 04.10.2022

Abstract

Aim: The main objective of the present study is to quantify and assess the changes in vegetation cover by using NDVI values from the Kannad Taluka of Aurangabad district, Maharashtra, India. The changes were studied during the period 2013 to 2020 to identify the probable causes of change in NDVI.

Methodology: The present study utilized Landsat images to evaluate and track the changes in vegetation cover by using the NDVI index values and classified in eight classes during seven years period.

Results: Two of the major NDVI classifications of this area were agriculture and urban area which showed a significant decrease in the year 2020 while in the water bodies, dense forest, sparse forest, grass land mixed with shrubs, grass land and barren land were increased. Area covered by agriculture and urban area was found 36.40% and 4.47 % in 2013 and which was noted to reduce by 21.64% and 2.53 % in 2020. The water bodies, dense forest, sparse forest, grass land and shrubs, grass land and barren land were found to be 1.79%, 6.18%, 9.71%, 12.71%, 12.92%, and 15.82 % in the year 2013 and were increased up to 2.17%, 14.28%, 13.52%, 13.49%, 14.54% and 17.83 % in 2020, respectively.

Interpretation: Area covered by agriculture has decreased by 14.76% in seven year period while the barren land increased by 2.01% in seven year period in Kannad Taluka. The loss of forest cover might be due to increased human population in the study area.  

Key words: Agricultural land, GIS, Kannad Taluka, Remote Sensing, Vegetation cover

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