Mapping Long Term Changes in Mangrove Cover and Predictions of Future Change under Different Climate Change Scenarios in the Sundarbans, Bangladesh

• Other Authors: Ghosh Manoj (isManagedBy), Ghosh Manoj (isOwnedBy), Lalit Kumar (hasCollector), Manoj Kumer Ghosh (hasCollector)
• Format: Dataset
• Language: unknown
• Published: University of New England, Australia
• Subjects: Photogrammetry and Remote Sensing; ENGINEERING; GEOMATIC ENGINEERING; Environmental Monitoring; ENVIRONMENTAL SCIENCES; ENVIRONMENTAL SCIENCE AND MANAGEMENT; Natural Resource Management; Ecosystem Assessment and Management of Coastal and Estuarine Environments; ENVIRONMENT; ECOSYSTEM ASSESSMENT AND MANAGEMENT; Ecosystem Assessment and Management at Regional or Larger Scales; Ecosystem Assessment and Management of Forest and Woodlands Environments; Pollution and contamination not elsewhere classified; Pollution and contamination; Environmental management; Assessment and management of terrestrial ecosystems; Terrestrial systems and management; Assessment and management of Antarctic and Southern Ocean ecosystems; Management of Antarctic and Southern Ocean environments; Assessment and management of freshwater ecosystems; Fresh; ground and surface water systems and management; Antarctic; Eros; Southern Ocean; Antarc*
• Online Access: https://researchdata.edu.au/mapping-long-term-sundarbans-bangladesh/1594527; https://hdl.handle.net/1959.11/23067

Related Publications Climate Variability and Mangrove Cover Dynamics at Species Level in the Sundarbans, Bangladesh https://doi.org/10.3390/su9050805 Mapping Long-Term Changes in Mangrove Species Composition and Distribution in the Sundarbans https://doi.org/10.3390/f7120305 Ground-based readings of temperature and rainfall, satellite imagery, aerial photographs, ground verification data and Digital Elevation Model (DEM) were used in this study. Ground-based meteorological information was obtained from Bangladesh Meteorological Department (BMD) for the period 1977 to 2015 and was used to determine the trends of rainfall and temperature in this thesis. Satellite images obtained from the US Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) website (www.glovis.usgs.gov) in four time periods were analysed to assess the dynamics of mangrove population at species level. Remote sensing techniques, as a solution to lack of spatial data at a relevant scale and difficulty in accessing the mangroves for field survey and also as an alternative to the traditional methods were used in monitoring of the changes in mangrove species composition, . To identify mangrove forests, a number of satellite sensors have been used, including Landsat TM/ETM/OLI, SPOT, CBERS, SIR, ASTER, and IKONOS and Quick Bird. The use of conventional medium-resolution remote sensor data (e.g., Landsat TM, ASTER, SPOT) in the identification of different mangrove species remains a challenging task. In many developing countries, the high cost of acquiring high- resolution satellite imagery excludes its routine use. The free availability of archived images enables the development of useful techniques in its use and therefor Landsat imagery were used in this study for mangrove species classification. Satellite imagery used in this study includes: Landsat Multispectral Scanner (MSS) of 57 m resolution acquired on 1st February 1977, Landsat Thematic Mapper (TM) of 28.5 m resolution acquired on 5th February 1989, Landsat ...