Remote Sensing and GIS Technology for Monitoring Bhola Island of Bangladesh

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1 Remote Sensing and GIS Technology for Monitoring Bhola Island of Bangladesh S M Mizanur Rahman, M Rahman Akhand, M Hashem Uddin Bangladesh Space Research and Remote Sensing Organization (SPARRSO) Agargaon, Sher-e-Bangla Nagar, Dhaka-1207, Bangladesh ABSTRACT The Island of Bhola is one of the biggest island of Bay of Bengal (BoB), Bangladesh. The purpose of this study was to study how coastal transformations had influenced the people on the island of Bhola and vice versa. Three different methods have been used, field observations/mapping, use of GISapplications and interviews. Integrated analysis of Remote Sensing (RS) and Geographic Information (GIS) can gives a vital input for management of natural resources, because RS observation with its unique capability provides cost-effective support about the environment of coastal area, while GIS facilitates uses for multidisciplinary analysis and decision support. In the field interviews have been made from the local people for verified the interpretation of previous images as well as current situation. Near infra-red band of Landsat-MSS/TM have been used for separation of land and water classes. In this case a methodology has been developed by selecting Digital Number (DN) of near infra-red region of MSS and TM imageries. Coastal transformation maps have been produced using raster base GIS analysis. The result shows that about ha area of the eastern part of Bhola Island has been disappeared in the sea during 37 year ( ). The variation in magnitude depends on the different grade of vegetation cover, beach slope gradient, soil compaction and the grade of influence by human beings. People living by the embankment have had to move between 2 to 4 times during a period of due to the erosion. Many of these people have been landless, and are now living illegal by the embankment in serfdom. Keywords: Remote sensing, GIS, Landsat MSS/TM 1. INTRODUCTION The Bay of Bengal (BoB), the marine area of Bangladesh, is characterized by a semi-enclosed tropical basin (Brammer, 1996). The coastline of the country comprises about 710 km extending from the tip of Teknaf in the south-east to the south-west coast of Satkhira. More than hundreds of off-shore Islands (OSI) of BoB, have been exists. Bhola Island is one of them. Natural resources in this island have been used for multiple purposes and have strongly influenced socio-economic development (Encyclopedia Britannica, ). The Island builds up over time and also eroded according to the rivers flow. Most of the erosion was caused by migration of channels and it might be considered as compensatory because erosion and accretion almost simultaneously occur. The BoB drains the combined discharges of the Ganges, Brahmaputra, Meghna (GBM) rivers amounting on the average to m 3 /s (Magnus K, 1999). These three rivers drain about 85 % of the total volume of water brought into Bangladesh. These are distinct seasonal in fluctuations inflow with extreme discharge in the monsoon (Siddiqi. p168). These water discharges influence to make erosion in the north part of Bhola Island. The average annual sediment load carried by the GBM Rivers to the Bay of Bengal is around 2 billion tons annually (Viles and Spencer 1995, p 294). Heavy sediment load coming from GBM and high tidal flow resist the sediment to go directly to the Bay of Bengal may a factor for accretion of inner rivers of the island. The area is dominated by semi-diurnal tidal currents, the maximum tidal range of 5 meters occurs in the Meghna estuary which gradually decreases southeastwards along the Chittagong coast (Viles et. al, 1995). Landsat MSS (80 m) data of 1973, Landsat TM (30 m) data of 1989 and 2010 were used to generate digital data base of different time period, analysis of erosion and accretion and finally produce digital map of Bhola island of Bangladesh. The combination of Remote Sensing and GIS analysis can produces a vital input for better planning, policy formulation for management of Island (Hossain et al. 2003). The prime objectives of this study is (i) to generate digital data sets for the year 1973, 1989 and > RJSITM: Volume: 04, Number: 04, February Page 68

2 2010 (ii) to prepare erosion and accretion map of Bhola island of the study area over 37 years ( ) and statistics under different time period 2. OBJECTIVES The objectives of the study is (i) to generate digital data sets for the year 1973, 1989 and 2010, (ii) to generation of Erosion and Accretion map of Bhola island of the study area over 37 years ( ), and statistics under different time period. STUDY AREA Bhola is an administrative district (zila) in south-western Bangladesh, which includes Bhola Island, the largest island of Bangladesh. It is located in the Barisal Division and has an area of km². It has a population of nearly 1,776,795 (Population Census 2011). It is bounded by Lakshmipur and Barisal Districts to the north, the Bay of Bengal to the south, the lower Meghna river and Shahbazpur Channel to the east and Patuakhali District and the Tetulia river to the west. Its coordinates are 22 20'57" to 22 36'43" N and 91 23'49" to 91 34'56" E. Landsat TM Frame 137/44 Bhola Island 137/44 136/44 Landsat TM Frame 137/45 137/45 136/45 Figure 1: Bhola Island over TM Frame of 137/44 & 137/45 Figure 2: Location of tide gauge stations and TM frames of study area 3. DATA AND SOFTWARE USED 3.1 Remote sensing data and Tide data Selection of data is very important for delineation of coast line of Bhola Island due to tidal effect. For avoiding low tide data a large number of data sets have been collected for selection of high tide data. Because our study have been conducted on high tide data Landsat data Landsat MSS data of 80 meter resolution of 1973, Landsat TM data of 30 meter resolution of 1989 and 2010 have been used in the study. Data sets for one season has two frames. The frames of Landsat MSS are 147/44 & 147/45 and TM are 137/44 & 137/45. Dates are 2 February 973, 28 January 1989 and 30 January The data receiving time is around 09:45 AM. Figure 2 shows the location of frames of 1973, 1989 and 2010 of study area. All the data are IMG format Tide data Most of the Landsat data during study period were found low and medium tide condition. Only two data received during study period almost in high tide condition in one station out of four stations Software used ERDAS Imagine and Raster based GIS have been used for data pre-processing, generation and analysis. 4. APPROACH > RJSITM: Volume: 04, Number: 04, February Page 69

3 To monitor the Bhola Island, extraction of land-water digital data sets and finally generation of change detection maps as well as statistics is very difficult due to tidal effect as well as frequent erosion and accretion process of river bank. To overcome the tidal effect, high tide water line have been selected to delineate the coastline in this study and spectral signature on remotely sensed data also provides information on different parts of the tidal flat i.e. foreshore intersection (Sarker M H et. al 2013). 5. PROCEDURE OF DATA GENERATION Generation of change detection data sets of Bhola Island involves remote sensing data collection/reception, pre-processing, layer generation, data analysis, finally extraction of erosion and accretion data sets i.e. output of study. Procedures are shown in figure 3. Figure 3: Procedures of data generation 5.1 Generation of Digital data sets of Bhola Island Change detection of Bhola Island, Bangladesh have been generated from Landsat MSS/TM data of 1973, 1989 and To generate Landsat MSS/TM images from , some pre-processing steps are involved those are describe bellow: Reception Landsat-MSS/TM data In Bangladesh, there is no ground station to receive LANDSAT data. For research work we have downloaded Landsat-MSS/TM data from the website during the dry period of 1973, 1989 and Total numbers of downloaded data sets are shown in table-1. The data we have downloaded are frame wise. Figure-5 shows the sample of down loaded frames of one season including atmospheric corrected and geo-referenced Pre-processing of Landsat-MSS/TM data a) Atmospheric correction Many atmospheric correction methods have been proposed for use with multi-spectral satellite imagery. The dark-object atmospheric correction method, (Hadjimitsis et al., 2010), was probably the most widely used approach for atmospherically correcting different remotely sensed imagery. The scheme is based on identification of dark cluster of pixels of water having near-zero percent reflectance which is considered to be free from intervention of the parameters like turbidity and chlorophyll concentration. To fulfill the above mentioned requirement, the clusters of pixels were selected in the deeper part of the Bay of Bengal, where the intervention of the above mentioned parameters was minima. A seed cluster of water having the lowest Digital Number (DN) values was > RJSITM: Volume: 04, Number: 04, February Page 70

4 selected from a 6 frames of MSS/TM images. Based on the mean value of the seed cluster, the images used in the study were corrected. Figure 1 shows the atmospheric corrected images of 2010 (sample of one season). It is mentioned that atmospheric, geometric as well as geo-referencing was done during my central coast study (Sarker M H et. al 2013). b) Geo-referencing Many geo-referencing methods have been used to geo-reference multi-spectral satellite imagery. One is the method is collection of Ground Control Point (GCP) from study area using Global Positioning System (GPS)/Differential GPS. In this method GCP collected from study area and transformed this coordinate to input image (same area images) by using geometric model of ERDAS imagine software (AutoSync). At first our frames/images of 2010 were geometrically corrected and were projected to Bangladesh Transverse Mercator (BTM) system by selecting 10 GCPs per image. Second order polynomial and then re-sampled with bilinear algorithm have been used during the re-sampling method. All the ten selected GCP s were easily identifiable and permanent in nature for measuring accurate results. A Root Mean Square (RMS) error of 0.30 (less than one pixel, 30m) was accepted for the correction process. The images/frames of other two seasons (1989 and 1973) were corrected from the geo-referenced images of 2010 as referenced images. Figure 1 shows the geo- referenced images of one season Land-water Classification based on Algorithm A simple algorithm was used to land-water classification. For land and water separation band 4 (0.76 to 0.90 µm) NIR have been used because band 4 of Landat-TM is suitable for land and water separation. In this case DN values of water have been collected carefully from the histogram of the selected image and found DN value 40. This value applied in the equation 1. An algorithm also needs to use for mask the cloud cover areas. If the clouds are not masked in the images, it will reflect the wrong value in processing. Luckily we have found the cloud free images, so no need to mask out the cloud. Figure 4 shows the land-water classification of frame 137/45 of Similarly all the images have been classified in similar way. Either (Landsat-5 TM) IF (Band 4<41) or 0 otherwise ---- (1) INPUT Figure 4: The land-water classification of frame 137/45 of 2010 Figure 5: Land-water digital data sets of 1973, 1989 & Generation of Bhola Island data sets > RJSITM: Volume: 04, Number: 04, February Page 71

5 Digital data sets of Bhola Island 1973, 1989 and 2010 have been generated from Landsat MSS/TM images using land-water classification of equation-1. Tidal flat areas have been masked carefully by using spectral signature of TM band4. Figure 5 shows the digital data sets of Bhola Island during 1973, 1989 and 2010 respectively at high tide condition Generation of change detection map For generation of erosion and accretion map during , the base layers of 1973, 1989 and 2010 generated by algorithm (equation 1) have been used as an input of raster based GIS as well as ArcGIS environments. Figure 6 shows the change detection map of Bhola Island, Bangladesh Field data collection, verification and incorporation Field visit was conducted in three times during study period. Firstly ground control point (GCP) was collected using GPS for geo-referencing of satellite images. Secondly, generated geo-referenced data was verified by field using GPS at laboratory. Lastly, field survey has been conducted to verify the land-water (LW) classified images of study period 1973, 1989 and During field visit information aimed to collect the accuracy of LW classified images and also migration of islands. Classified images as well as raw images along with GPS and digital camera have been carried during field visit. Collection of tidal information from local people as well as local water development board was also very important. During field visit Interviews also were made in three villages, the purpose was to investigate how the erosion had affected the people living in these villages, especially how many times they had had to move because of the erosion. People living by the embankment have had to move between 2 to 4 times during a period due to the erosion. Many of these people have been landless, and are now living illegal by the embankment in serfdom. After the fieldwork, field data have been incorporated into LW classified time series images and for final analysis these were brought into raster based GIS environments. Figure 7: False Color Composite (FCC) of Landsat image of Bhola Island during 1973, 1989 & 2010 Figure 6: Change detection map of Bhola Island during RESULT AND DISCUSSIONS 6.1. Visual Interpretation of Raw Images of Bhola Island. > RJSITM: Volume: 04, Number: 04, February Page 72

6 The objective of the visual interpretation is to identify the tone, texture, shape and color of the images in different time period that will helpful for GIS analysis. Figure 8 shows the RGB (4, 3, 2) of 1973, 1989 and 2010 of Landsat images. In this figure the red color shows in all three images are settlement and mangrove, blue color shows the water area and magenta color shows bare land. It is clearly seen from the figure that settlement areas have increasing tendency in 1989 in compare to 1973 and dense settlement shows in 2010 compare to 1973 & Images of 1989 and 2010 shows less wide area compare to image 1973 may due to erosion. Image of 1989 shows severe erosion on the top compare to image 1973 and on the top of the image 2010 shows large area have been visible during low tide condition compare to GIS analysis of Bhola Island GIS analysis image shows the erosion and accretion of Bhola Island during 37 years ( ) in figure 6. It is clear from the figure 6 and figure7 that, Bhola Island has been eroded and accreted both the time periods 1973 to 1989 and 1989 to But erosion observed higher compared to accretion in both the time period 1973 to 1989 and 1989 to These observations are mostly in upper and east part of the Island. Southwest, south and southeast parts are remaining unchanged both the time period. Table 1: Statistics of Bhola Island during the study period 1973, 1989& 2010 Figure 8: Bar diagram of Bhola Island during the study period 1973, 1989& 2010 Table 1 shows the statistics of erosion and accretion of Bhola Island. Bar diagram of figure 8 shows that, the area of Bhola Island is gradually decreasing both the time period during and 1989 to Decreasing tendency may be for higher percentage of erosion due high speedy current coming from GMB during monsoon period. The study reveals that about ha area has been disappeared in the sea during the last 37 year ( ). 7. CONCLUSIONS AND RECOMENDATIONS Bhola Island was occurred erosion dominating due to tidal driving force and hydro-dynamic effects. Erosion observed severe in eastern part of the Island during compare to due to high speedy current coming from GMB in monsoon period. Hydro dynamic interaction of river and ocean water may another factor for erosion of Bhola Island. So, further research on hydro-dynamic factors like speed of water flow, depth of water, etc will be added to improve the accuracy of study. 8. ACKNOWLEDGEMENT > RJSITM: Volume: 04, Number: 04, February Page 73

7 We are very much grateful to National Aeronautic Space Administration (NASA) for providing free Landsat data from their website and honorable Chairman, SPARRSO for providing laboratory facility to complete the research work. REFERENCE 1. BBS (Bangladesh Bureau of Statistics). Population Census Brammer, Hugh., The Geography of the Soils of Bangladesh, Dhaka Encyclopedia Britannica ; http//: 4. Hadjimitsis, D. G., Papadavid, G., Agapiou, A., (2010) Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices, In Natural Hazards And Earth System Science 10 (1). 5. Hossain, M.S., Lin, C.K., Tokunaga, M., Demaine, H., and Hussain, M.Z., (2003). Land use zoning for solar salt production in Cox s Bazar coast of Bangladesh: A Remote Sensing and GIS analysis. Asian Journal of Geo Informatics, 3 (4), http//: 7. Magnus Krantz (1999), Coastal Erosion on the Island of Bhola, Bangladesh; Earth Science Centre, Department of Physical G eography, GÖTEBORG University, B178, Sweden. 8. Sarker, M. H., Akhand, M. R, Rahman, S. M. M., Molla, F., (2013). Mapping of Coastal Morphological Changes of Bangladesh using RS, GIS and GNSS Technology. The International Journal of Remote Sensing and GIS. ISSN: , (27-34). 9. Siddiqi, Masroor-Ul-Haq. Land Erosion and Accretion in the Coastal Area. Bangladesh, Centre For Advanced Studies. Dhaka. 168 p. 10. Viles, H, Spencer., Tom.; (1995), Coastal Problems. London. 350 p. > RJSITM: Volume: 04, Number: 04, February Page 74