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Tracing mangrove forest dynamics of Bangladesh using historical Landsat data

Islam, Md Monirul LU (2017) In Student thesis series INES NGEM01 20171
Dept of Physical Geography and Ecosystem Science
Abstract
Present, accurate, and reliable estimation of mangrove forests in Bangladesh is limited. Former estimation of mangroves extent and density has been more or less restricted to Sundarbans and do not represent the whole country. In this study, a time series analysis was performed using Landsat images from four epochs, namely: 1976 (Landsat MSS), 1989 (Landsat TM), 2000 (Landsat ETM+) and 2015 (Landsat L8 OLI) to accurately quantify mangroves extent and density change/variation in the study area. An atmospheric correction using the Dark Object Subtraction method and a radiometric normalization using pseudo-invariant features was performed to reduce haze and sedimentation effects of the images. A standard approach to study changes in forest... (More)
Present, accurate, and reliable estimation of mangrove forests in Bangladesh is limited. Former estimation of mangroves extent and density has been more or less restricted to Sundarbans and do not represent the whole country. In this study, a time series analysis was performed using Landsat images from four epochs, namely: 1976 (Landsat MSS), 1989 (Landsat TM), 2000 (Landsat ETM+) and 2015 (Landsat L8 OLI) to accurately quantify mangroves extent and density change/variation in the study area. An atmospheric correction using the Dark Object Subtraction method and a radiometric normalization using pseudo-invariant features was performed to reduce haze and sedimentation effects of the images. A standard approach to study changes in forest characteristics is to perform a time series analysis using images that have undergone a supervised classification. Results are indicating a gradual increase of forest area in most parts of the study area. Overall, the areal coverage increased by 3.10% (58140 ha) from 1976 to 2015, where 1.79% (58140 ha) of this increase took place from 2000 to 2015. The Sundarbans area turned out to be an exception. There, the mangrove forest area remained almost unchanged, although a little change (decrease by 1.03%) was found between 2000 and 2015. The study also claimed that one of the oldest mangrove forests in Bangladesh (Chakaria Sundarbans) had lost 4135 ha (32%) of forest area between 1976 and 1989. Similarly, a vegetation index (NDVI) analysis suggested that not only the area but also the density of the mangroves has changed over the years. The forests seem to have been denser in 1976 than in 1989. In 2000 the density appeared to have increased again, while decreased again in 2015. The study also found a substantial increase between 1989 and 2000 while a considerable density decreases in the Sundarbans region between 2000 and 2015. However, Mangroves area change was not significant in the context of classification uncertainty. A little error source was found due to the similar spectral reflectance between mangroves and non-mangrove vegetation, for example, in Patuakhali-Bhola. An accuracy assessment was performed using confusion matrices, showed maximum likelihood algorithm produce a better result for mangrove classes than other Land use/ Land cover classes. The overall accuracy of Landsat 8 OLI, ETM+, TM, and the MSS classified images (five classes) were found to be 97%, 87%, 80%, and 80% respectively, with Kappa values of 0.96, 0.82, 0.73, 0.74. Several possible factors such as cyclones, sedimentation and erosion, deforestation, shrimp and salt farming, and mangrove plantation were identified, which might be responsible for mangrove variations/changes in Bangladesh. (Less)
Popular Abstract
The Mangrove forests are lies between land and sea in tropical and subtropical coastlines around the world. They are source of fuelwood and medicinal plants, shrimp and fish breeding zones, attracting places for tourist, and protect coastal areas from cyclone and tsunamis. However, Mangrove forests are threatening in Bangladesh due to cyclone, deforestation, and land use changes. In this study, Landsat images from 1976 to 2015 were used to the preparation of time-series. Two standard approaches supervised classification and Vegetation Index (NDVI) were used to detect mangroves cover and vegetation density changes in the study area. The results indicate that Bangladesh gained 3.10% (58140 ha) of mangroves area from 1976 to 2015, where 1.79%... (More)
The Mangrove forests are lies between land and sea in tropical and subtropical coastlines around the world. They are source of fuelwood and medicinal plants, shrimp and fish breeding zones, attracting places for tourist, and protect coastal areas from cyclone and tsunamis. However, Mangrove forests are threatening in Bangladesh due to cyclone, deforestation, and land use changes. In this study, Landsat images from 1976 to 2015 were used to the preparation of time-series. Two standard approaches supervised classification and Vegetation Index (NDVI) were used to detect mangroves cover and vegetation density changes in the study area. The results indicate that Bangladesh gained 3.10% (58140 ha) of mangroves area from 1976 to 2015, where 1.79% (33587 ha) of this increase took place from 2000 to 2015. Although a mangroves area lost were found in Sundarbans about 1.03% between 2000 and 2015. Similarly, NDVI analysis suggests that the forests seem to have been denser in 1976 than in 1989. In 2000 the density appeared to have increased again, while decreased again in 2015. The study also found cyclones, deforestation, shrimp and salt farm, mangrove plantation, coastal erosion and deposition are associated with mangroves change in the country. The area estimation was evaluated using a standard validation approach which ensures it was possible using Landsat Imagery to monitor mangrove changes in the study area. Furthermore, this study results may assist in conservation and management planning of Mangrove forests in Bangladesh. (Less)
Please use this url to cite or link to this publication:
author
Islam, Md Monirul LU
supervisor
organization
course
NGEM01 20171
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Bangladesh, Physical Geography and Ecosystem Analysis, Landsat, mangroves, change detection, time-series, NDVI, supervised classification
publication/series
Student thesis series INES
report number
415
funder
Svenska Institutet
language
English
additional info
funder: Svenska Institutet
id
8915599
date added to LUP
2017-06-15 15:14:07
date last changed
2017-06-15 15:14:07
@misc{8915599,
  abstract     = {Present, accurate, and reliable estimation of mangrove forests in Bangladesh is limited. Former estimation of mangroves extent and density has been more or less restricted to Sundarbans and do not represent the whole country. In this study, a time series analysis was performed using Landsat images from four epochs, namely: 1976 (Landsat MSS), 1989 (Landsat TM), 2000 (Landsat ETM+) and 2015 (Landsat L8 OLI) to accurately quantify mangroves extent and density change/variation in the study area. An atmospheric correction using the Dark Object Subtraction method and a radiometric normalization using pseudo-invariant features was performed to reduce haze and sedimentation effects of the images. A standard approach to study changes in forest characteristics is to perform a time series analysis using images that have undergone a supervised classification. Results are indicating a gradual increase of forest area in most parts of the study area. Overall, the areal coverage increased by 3.10% (58140 ha) from 1976 to 2015, where 1.79% (58140 ha) of this increase took place from 2000 to 2015. The Sundarbans area turned out to be an exception. There, the mangrove forest area remained almost unchanged, although a little change (decrease by 1.03%) was found between 2000 and 2015. The study also claimed that one of the oldest mangrove forests in Bangladesh (Chakaria Sundarbans) had lost 4135 ha (32%) of forest area between 1976 and 1989. Similarly, a vegetation index (NDVI) analysis suggested that not only the area but also the density of the mangroves has changed over the years. The forests seem to have been denser in 1976 than in 1989. In 2000 the density appeared to have increased again, while decreased again in 2015. The study also found a substantial increase between 1989 and 2000 while a considerable density decreases in the Sundarbans region between 2000 and 2015. However, Mangroves area change was not significant in the context of classification uncertainty. A little error source was found due to the similar spectral reflectance between mangroves and non-mangrove vegetation, for example, in Patuakhali-Bhola. An accuracy assessment was performed using confusion matrices, showed maximum likelihood algorithm produce a better result for mangrove classes than other Land use/ Land cover classes. The overall accuracy of Landsat 8 OLI, ETM+, TM, and the MSS classified images (five classes) were found to be 97%, 87%, 80%, and 80% respectively, with Kappa values of 0.96, 0.82, 0.73, 0.74. Several possible factors such as cyclones, sedimentation and erosion, deforestation, shrimp and salt farming, and mangrove plantation were identified, which might be responsible for mangrove variations/changes in Bangladesh.},
  author       = {Islam, Md Monirul},
  keyword      = {Bangladesh,Physical Geography and Ecosystem Analysis,Landsat,mangroves,change detection,time-series,NDVI,supervised classification},
  language     = {eng},
  note         = {Student Paper},
  series       = {Student thesis series INES},
  title        = {Tracing mangrove forest dynamics of Bangladesh using historical Landsat data},
  year         = {2017},
}