Change detection of the Sundarban part of Bangladesh using remote sensing and GIS techniques with machine learning algorithms
- Paper number
IAC-18,B1,IP,26,x47723
- Author
Mr. Mitesh Chakma, Bangladesh, BRAC University
- Coauthor
Ms. Sadia Zannat, Bangladesh, BRAC University
- Coauthor
Mr. Abdulla Hil Kafi, Bangladesh, BRAC University
- Coauthor
Ms. Raihana Shams Islam Antara, Bangladesh, BRAC University
- Year
2018
- Abstract
Sundarbans, the world largest mangrove ecosystem is experiencing a multidimensional threat of degradation. The present study was aimed to understand these problems and search for proper remedies by applying suitable remote sensing technologies. This study aims to examine the landcover changes and quantifying the changes and present status of mangrove forest in the Bangladesh part of Sundarbans by using multitemporal Landsat data. The analysis shows the superabundant growth of the buildup areas near the reserve forest area where the classified maps have been assessed through different classification methods. Based on analyzed data, the result shows and predict the expected urban growth, deforestation rate and compare its performance based on different machine learning algorithms. The experimental result indicates and aims to provide an idea about the forest cover which is constantly evolving due to deforestation, aggradation, erosion, and forest restoration programs in the reserve forest of Sundarbans.
- Abstract document
- Manuscript document
IAC-18,B1,IP,26,x47723.pdf (🔒 authorized access only).
To get the manuscript, please contact IAF Secretariat.