Temporal forest change detection and forest health assessment using remote sensing

• Main Authors: Azize, A.B.M (Author), Azmi, N.F (Author), Mahmon, N.A (Author), Mustafa, N. (Author), Ya'Acob, N. (Author), Yusof, A.L (Author)
• Format: Article
• Language: English
• Published: Institute of Physics Publishing 2014
• Subjects: Angsi Forest Reserve; Berembun Forest Reserve; Biodiversity; Carbon oxide; Climate change; deforestation; Deforestation; detection method; Earth sciences; Economic growths; Economics; Ecosystems; Forest change; forest dynamics; forest health; Forest health; Forest health assessment; forest management; Image Analysis; image processing; Image processing; Malaysia; nature reserve; NDVI; Negeri Sembilan; Normalized difference vegetation index; remote sensing; Remote sensing; Remote Sensing; Remote sensing applications; Satellite images; Seremban; Signal detection; temperate forest; West Malaysia
• Online Access: View Fulltext in Publisher; View in Scopus
• ISBN: 17551307 (ISSN)
• DOI: 10.1088/1755-1315/19/1/012017

This paper presents the detection of Angsi and Berembun Reserve Forest change for years 1996 and 2013. Forest is an important part of our ecosystem. The main function is to absorb carbon oxide and produce oxygen in their cycle of photosynthesis to maintain a balance and healthy atmosphere. However, forest changes as time changes. Some changes are necessary as to give way for economic growth. Nevertheless, it is important to monitor forest change so that deforestation and development can be planned and the balance of ecosystem is still preserved. It is important because there are number of unfavorable effects of deforestation that include environmental and economic such as erosion of soil, loss of biodiversity and climate change. The forest change detection can be studied with reference of several satellite images using remote sensing application. Forest change detection is best done with remote sensing due to large and remote study area. The objective of this project is to detect forest change over time and to compare forest health indicated by Normalized Difference Vegetation Index (NDVI) using remote sensing and image processing. The forest under study shows depletion of forest area by 12% and 100% increment of deforestation activities. The NDVI value which is associated with the forest health also shows 13% of reduction.