Estimation and Study of Forest Loss and Gain Using Spatial Dataset across Districts of Uttarakhand

Khan, Sameer and Joshi, Sanjay and Kumar, Ashok and Pandey, Binay K. (2022) Estimation and Study of Forest Loss and Gain Using Spatial Dataset across Districts of Uttarakhand. Asian Journal of Research in Computer Science, 14 (1). pp. 38-51. ISSN 2581-8260

[thumbnail of 275-Article Text-445-2-10-20220914.pdf] Text
275-Article Text-445-2-10-20220914.pdf - Published Version

Download (1MB)

Abstract

Aims: To study and estimate the forest cover loss and gain across the 13 districts of Uttarakhand.

Place and Duration of Study: Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, between September 2021 and December 2021.

Methodology: We extracted forest cover time-series data from the year 2001 to the year 2020 from Hensen Global Forest Change Dataset. This data was then mapped to the shapefile created in ARC-GIS containing all 13 districts as a Feature Collection, which was then used to individually classify each region and to estimate the size of the loss of tree cover precisely over the district boundary.

Results: Our study shows forest loss of about (21,05,71,646 square meters) and forest gain of (6,00,79,072 square meters) cumulatively in all the districts of Uttarakhand from the year 2001 to 2020 at a spatial resolution of 30 meters where trees were identified as canopies greater than 5 meters in height.

Conclusion: Among the districts of Uttarakhand Udham Singh Nagar, Nainital, and Champawat alone contribute to the total tree cover loss area of 15061.7513801 ha. which is about 71.5 % of Uttarakhand’s total tree cover loss. These regions require monitoring and controlling deforestation and more detailed studies like this are required to analyze and prevent the causes of such great-scale deforestation. Analyzing districts apart from those mentioned above, it is observed that the amount of tree cover loss is greater than the reforestation.

Item Type: Article
Subjects: Academic Digital Library > Computer Science
Depositing User: Unnamed user with email info@academicdigitallibrary.org
Date Deposited: 09 Jan 2023 07:04
Last Modified: 19 Jun 2024 11:46
URI: http://publications.article4sub.com/id/eprint/287

Actions (login required)

View Item
View Item