Monitoring the Vegetation Condition of Gorumara National Park Using NDVI and NDMI Indices

Authors

  • Pritam Kumar Barman Dept. of Forest Biology, Tree Improvement and Wildlife Sciences, College of Forestry, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj, Uttar Pradesh (211 007), India https://orcid.org/0000-0002-5630-4965
  • Shivani Rawat Dept. of Forest Biology, Tree Improvement and Wildlife Sciences, College of Forestry, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj, Uttar Pradesh (211 007), India
  • Avni Kumari Dept. of Forest Biology, Tree Improvement and Wildlife Sciences, College of Forestry, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj, Uttar Pradesh (211 007), India
  • Afaq Majid Wani Dept. of Forest Biology, Tree Improvement and Wildlife Sciences, College of Forestry, Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj, Uttar Pradesh (211 007), India

DOI:

https://doi.org/10.23910/1.2024.5052

Keywords:

Landsat 8, NDVI, NDMI, remote sensing, vegetation condition

Abstract

The present study was conducted from November, 2022 to June, 2023 aims to analyze and detect changes in vegetation using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) in Gorumara National Park, Jalpaiguri district, West Bengal, India. To calculate NDVI and NDMI values, Landsat 8 level-1 images acquired between 2016 and 2021. Different band combinations of the remote sensing data are analyzed to classify the vegetation condition and cover. For this study, the 4 (Red), 5 (NIR), and 6 (SWIR) multi-spectral band combinations are used separately. The rising use of satellite remote sensing and Geographic Information System (GIS) for civilian purposes has shown itself to be the most cost-effective and time-effective method of mapping and monitoring vegetation conditions and changes. Open-source software such as QGIS and the Semi-Automatic Classification Plugin (SCP) was used for mapping and image pre-processing. According to the NDVI and NDMI classifications, the area under high vegetation and high moisture content has slightly increased by 0.15% and 0.23%, respectively. During the study period the high vegetation and very high moisture content areas covered most areas in 2020 and 2017, respectively. According to the findings, the NDVI and NDMI are very helpful in identifying the area’s surface features, which is very helpful for determining the vegetation’s general health, providing the required data for long-term conservation efforts, and developing efficient management plans.

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Published

2024-02-19

How to Cite

1.
Barman PK, Rawat S, Kumari A, Wani AM. Monitoring the Vegetation Condition of Gorumara National Park Using NDVI and NDMI Indices. IJBSM [Internet]. 2024 Feb. 19 [cited 2025 Sep. 20];15(Feb, 2):01-7. Available from: https://ojs.pphouse.org/index.php/IJBSM/article/view/5052

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Articles