Application of Sentinel-2 Satellite Data to Map Forest Cover in Southeast Sri Lanka through the Random Forest Classifier
Article
Article Title | Application of Sentinel-2 Satellite Data to Map Forest Cover in Southeast Sri Lanka through the Random Forest Classifier |
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Article Category | Article |
Authors | Gunawansa, Thakshila, Perera, Kithsiri, Apan, Armando and Hettiarachchi, Nandita |
Journal Title | Journal of Advances in Engineering and Technology |
Journal Citation | I (I), pp. 049-1 to 049-10 |
Number of Pages | 10 |
Year | 2022 |
Publisher | Sri Lanka Institute of Information Technology (SLIIT) |
Place of Publication | Sri Lanka |
Web Address (URL) | https://www.sliit.lk/blog/engineering-news/the-journal-of-advances-in-engineering-and-technology-jaet/ |
Abstract | Sentinel-2 satellite data has been used for forest cover monitoring for almost five years. Mapping with Sentinel data will be a cost-effective solution for Sri Lanka, where the lack of updated land cover maps with high spatial resolution is a significant challenge in the land resource management of the country. A study area of about 5,000 km2 located in southeast Sri Lanka was selected for this study. Agricultural lands, forests including Yala national park, and villages with perennial crops make up the region. A Level-2A Sentinel-2 image with less than 10 percent cloud cover was used in the European Space Agency's (ESA) SNAP software version 8.0.0 for image processing and the forest cover of the study area was mapped through the Random Forest classifier (RFC). Normalized Difference Vegetation Index (NDVI) is also calculated as a Sentinel product to support RFC output. For RFC, ground truth |
Keywords | Sentinel-2, Random Forest Classifier, Land cover classification, Land cover mapping, Normalized Difference Vegetation Index. |
Related Output | |
Is part of | Demarcating High-Risk Zones of Human-Elephant Conflict in Sri Lanka Utilizing GIS and a Satellite Data Fusion Approach |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 401304. Photogrammetry and remote sensing |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
This article is part of a UniSQ Thesis by publication. See Related Output. | |
Byline Affiliations | Uva Wellassa University of Sri Lanka, Sri Lanka |
School of Surveying and Built Environment | |
Centre for Sustainable Agricultural Systems | |
University of Ruhuna, Sri Lanka |
https://research.usq.edu.au/item/yzx56/application-of-sentinel-2-satellite-data-to-map-forest-cover-in-southeast-sri-lanka-through-the-random-forest-classifier
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