Temporal Change Detection (2001-2008) Study of Sundarban
( Final Report )
Professor Sugata Hazra Kaberi Samanta , Anirban Mukhopadhyay & Anirban Akhand
School of Oceanographic Studies Jadavpur University 2010
- 0 - Temporal Change Detection (2001- 2008) Study of Sundarban
(Final Report)
Professor Sugata Hazra Kaberi Samanta , Anirban Mukhopadhyay & Anirban Akhand
School of Oceanographic Studies Jadavpur University
March, 2010
- 1 - Summary
The ‘Temporal Change Detection(2001-2008) study of Sundarban’ has been taken up by the School of Oceanographic Studies, Jadavpur University on October, 2009, as per the MOU executed between the WWF and Jadavpur University on 23rd. September 2009. Accordingly 75% of working expenses i.e. Rs. 3, 75,000/- has been received by the university on 28.10.2009.
The work has been conducted as per schedule according to the following TOR:
1. Identification, mapping and classification of vulnerable islands using satellite imageries/data (time series analysis) 2. Identification and classification of embankments from satellite imageries/data and ground truthing 3. Land use and land cover status for the period between 2001 and 2008 and carrying out change detection exercise using satellite imagery/data generated earlier. 4. Estimation of temperature rise over land and sea; Assessment of rainfall and cyclone trend over the island system 5. Estimation of Sea Level Rise from existing data 6. Change in forest cover for the period between 2001 and 2008 and carrying out change detection exercise using satellite imagery /data generated earlier.
The present report summarises the important findings of the above study. The supporting data and the maps have been appended to facilitate the understanding and analysis of sponsoring organisation. However , a comprehensive analysis will be appended with the final report. At the present level, the following conclusions can be drawn:
1. The shore line change detection study has been done using LISS III satellite images of January 2001 and January 2009 accompanied by field verification. It has been observed that the entire island system has suffered a net land loss of 44 Km2 within the study period with an average rate of erosion of 5.5 Km2 per year. This happens to be significantly higher than the rate approaching 4 Km2 as observed in the
- 2 - previous decades. Ten sea facing most vulnerable island- clusters, namely Sagar, Ghoramara, Jambudwip, Namkhana, Mousuni, Dakhsin Surendranagar, Dhanchi,Dalhousi, Bulchery, and Bhangaduani have borne the major thrust of erosion and submergence . They together constitute the 68% of the lost land to the sea. The offshore islands like Jambudwip in the west or Bhanduani on the east demonstrate loss of 20 to 16% of their land area within 20001 to 2009. The results have been discussed in Chapter 1
2. The embankments have been mapped from the high resolution images in consultation with pre existing maps of the department of Irrigation and Waterways, Govt. of West Bengal , with limited field checks. Four different types of embankments can be recognized in the field. The total length of the embankments is found to be 3638 Km. The vulnerable portion of the embankments was found and mapped to be 416 k m , before Aila. In the post Aila situation , the vulnerable portion appears to be close to 1000 amongst which 305 Km is totally breached, 553 Km stretch is severely damaged while around 140 km is partially damaged. The findings have been discussed in Chapter II
3. In the study of land use change, it has been observed that there is a significant increase in the settlement area from1226 Km2 to 1666 Km2 while the available agricultural land reduced from 2149 Km2 to 1691 Km2. The change detection analysis clearly depicts the land conversation from agriculture land to settlement area with vegetation. , particularly in the S 24 parganas. In the north 24 parganas, the change detection analysis brings out a different picture . Here conversion of agriculture land to aquaculture is more conspicuous. This conversion , along with the growth rate of population implies increasing threat to the ecological sustainability and food security of the study area. While the Mudflats are reduced almost by 50% during the study period , there is a marginal increase in the aquaculture farms from 603 Km2 to 649 Km2. Both water bodies and swamp area have increased . This appears to be driven by sea level rise and coastal erosion. The details have been discussed in the Chapter III.
- 3 -
4. For estimation of Temperature rise, rainfall and Cyclone pattern, it has been decided to access and extract daily information of Sea Surface temperature, Rainfall and Wind data set for the entire Bay of Bengal area from modern High resolution Ocean satellites (Aqua-Modis Level 3 , 11µ , Tropical Rainfall measuring Mission (TRMM) Microwave Imager , and AMSRE ). It is obvious that the temperature of the Sea Surface of the Bay of Bengal, hourly rainfall data per unit area of the Bay of Bengal and the Cyclone frequency and intensity over the northern Bay of Bengal are more representative climate Change indicator and drivers of the sea level change observed at Sagar Island at Sundarban. The initial observations are quite significant to understand the recent accelerated change of climatic pattern in the study area. During the period of observation (2003-2009)the SST showed a rising trend at the rate of 0.0453 oC/ year and reached the highest level in the last year under study This is . This is almost double of the rate observed (0.019 oC/ year ) during the period 1985-2000 (Hazra,2003, for a smaller space window). During the same period the monsoon rainfall has increased at the rate of 0.0041 mm/hr resulting in a marginal increase in the average annual rainfall in the Bay of Bengal area. However, the the total rainfall in the land area has not incresead during the study period. During the period 1999 to 2005, when there was a little downward trend in the SST, from several number of depressions formed, only three could be materialized into severe and super-cyclonic storms. Whereas in the next four years, with sharp rise of SST , seven such cyclonic storms have been generated from the in the northern bay of Bengal, which includes Mala, Sidr, Bijli and Aila impacting wide areas of Sundarban
5. The Tide guage data of Sagar Island observatory indicated a rise in the Relative Mean Sea Level (RMSL) at the rate of 17.8 mm/ year during the present decade. This is significantly higher than the rate of 3.14mm/year as observed during the previous decade.. The mean tide level of Sundarban seems to vary in close correlation with the SST and Rainfall in the Bay of Bengal. However, beside these two main factors, subsidence, siltation and other local causes may be responsible for the exceptionally high rate of relative sea level rise in Sundarban during the
- 4 - present decade. Normalising with the data from previous decade the composite average rate of SLR in Sagar island appears to be 8.63 mm/year 6. Forest cover change mapping indicates some serious impact of Climate Change and sea level rise. In most of the islands, dense forest seems to have grown, thanks to the sustained efforts of forest plantation. However the reduction of forest area from 2168.9 Km2 to 2132. Km2 is mainly due to two reasons , erosion and submergence and secondly, the conversion to saline blanks / salt pans, which has grown from 38.74 Km2 to 74.796 Km2 within this 8 years time span. However some re- colonisation by salt tolerant mangrove species can be observed in some islands
The increase is water area within the islands also points to a slow gradual invasion of the sea.
- 5 - Chapter I
Erosion- Accretion of Indian Sundarban
- 6 - Administrative Blocks in Indian Sundarbans: The Sundarban in the Indian part consists of 13 blocks in the South 24 Parganas and 6 blocks in the North 24 Parganas. The south 24 parganas consists of Sagar, Namkhana, Kakdwip, Patharpratima, Mathurapur I & II, Jaynagar I & II, Canning I & II, Basanti, Gosaba & Kultali. While the 6 blocks under North 24 parganas consists of Haroa, Hasnabad, Minakhan, Sandeshkhali I & II and Hingalganj.
Plate. No. 1.1
- 7 - Plate. No. 1. 2
Coastal erosion and accretion measures changes in shoreline dynamics. Detailed monitoring of these changes is very important, to assess the impact of climate change and sea level rise. Information on shoreline changes can help to predict future changes and to prepare the adaptation policies for climate change. Coastal erosion is constantly reshaping the islands of Indian Sundarbans. With more or less constant sediment and water flow in the estuary within the time frame concerned, coastal erosion appears to be a product of change in sea level and tidal hydraulics. With continuing tidal and storm surges of higher intensity / height, sediments that were previously in equilibrium with the hydraulic system, are dislodged, eroded and are deposited within the channel/sub tidal areas. This results in progressive reduction of land area with shallowing. of channel floor/near- lsland bathymetry. The eroded material may be carried by tidal currents to the north and can be redeposited in the tide- sheltered’ sections of north and east.
- 8 - Rate of coastal erosion in the Indian Sundarban have been measured to be about5.50 sq kms / year within the time frame of 2001 - 2009 and eventually it is most dominant in the south western edges of the individual islands. Erosion has affected both sandy beaches and mud flats. Even inlands with dense mangrove on the east (like Bhanga duani/Mayadwip, Dalhousi or Bulcherry) have been substantially eroded. Total land area of 6402.090 sq.kms of Indian Sundarbans in the year 2001 has been found to be reduced to 6358.048 sq.kms. in 2009 registering a land net loss of 44.042 sq.kms. This includes erosion of 64.162 sq.kms and the accretion of 20.120 sq.kms.
Shoreline recession is accompanied by an increase in coastal vulnerability to sea level rise, wave action, storm surge, and an overall increase in the potential for natural resource destruction.
Plate. No. 1.3 : Vulnerable islands of Sundarban
The southern islands are witnessing the maximum amount of erosion and this is well established from the graphs given below. The table no: 37 is showing the year-wise
- 9 - estimation of land loss of the following southern islands. The erosion rate is much higher for the southern islands than the whole of Sundarban area which is evident from the Figures 1.4 to 1.6.
Table 1.1 : Year-wise Estimation of land loss of the southern most vulnerable islands in Indian Sundarban (area in sq. km) Sl.No Islands 2001 2009 Loss 1. Dakshin 44.339 42.015 2.324 Surendranagar 2. Sagar 244.434 239.091 5.343 3. Namkhana 150.155 145.488 4.667 4. Moushuni 28.923 28.283 0.64 5. Ghoramara 5.339 4.564 0.774 6. Dhanchi 36.084 34.180 1.904 7. Dalhousie 67.101 62.201 4.9 8. Bulchery 26.915 23.287 3.628 9. Bhangaduni 31.316 26.159 5.157 10. Jambudwip 6.242 4.979 1.263
- 10 - Figure. No. 1.4
- 11 - Figure. No.1.5
Figure. No1. 6
- 12 - Chapter II
Study of the Embankments
- 13 - Plate. No. 2.1: Embankments and Risk Zone Map of Indian Sundarban
Four different types of earthen embankments (Plate 2.2-2.6) are commonly found in Sundarban; they are: a) 2m high earthen embankments bordering small channels, b) 2.7 m high earthen wall with brick pitching on island margins, c) 3m high embankment with brick pitching on wave exposed coasts, d) 3.67m high wall with boulder pitching on eroding stretches. However overtopping, toe erosion, wash over or beach lowering are frequent phenomena of these age old embankments erected in the early 20th Century. During the present course of study, the total length of the Embankments in the Indian Sundarbans has been found to be 3638.182 kms of which the total length of the vulnerable embankments was 470.962 kms (Before Aila).. However after the Aila, the vulnerable patches reportedly have gone up to 1000 Km which needs further verification.
- 14 -
Photo 2.2.. Breaching of embankment at Photo 2.3. Embankmment at Lakshmipur Beguakhali
Photo 2.4. Embankmment at Moushuni Photo 2.5 Embankmment at Patibunia, Namkhana
Photo 2.6. Embankmment at Shibpur, Sagar - 15 - Chapter III
Study of land use land cover Change
- 16 - The landuse / landcover change detection studies between 2001-09 time window has been accomplishede with the help of existing maps, satellite data and field work using a GIS platform . The forest area is found to be concentrated within the Gosaba block, Kultali block, Patharpratima block and Namkhana block.
Figure. No. 3.1
- 17 - Table. No. 3.1
SL.NO LANDUSE/LANDCOVER CLASSES YEAR 2001 YEAR 2009 1. DENSE FOREST 1655.878 1651.3275 2. DEGRADED FOREST 404.887 332.0008 3. SALINE BLANKS 38.93 74.7965 4. SETTLEMENT WITH VEGETATION 1226.334 1666.43 5. AGRICULTURAL LAND 2149.615 1691.246 6. AQUACULTURE FARM 603.603 649.1 7. WATER BODY 232.888 250.6531 8. MUDFLATS 23.897 12.6135 9. SAND (BEACHES/DUNES) 8.0835 8.7664 10. RECLAIMED LAND FROM FOREST 14.512 12.644 11. SWAMP 14.847 20.41 TOTAL 6373.4745 6369.9878
The landuse/ landcover changes data between 2001 and 2009 is given in the Table. No. 1. It is evident that there is a change in the forest cover distribution. Though the dense forest cover has not reduced significantly but the amount of saline blanks which was 38.93 sq.kms in the year 2001 has increased to 74.7965 sq.kms at the expense of the degraded forest part of Indian Sundarbans. The degraded forest area has reduced from 404.887 sq.km to 332.008 sq.kms.. However a decline in the total forest area is mostly due to coastal erosion of forested islands.
Figure. No.3. 2
- 18 - The human habited part of the Indian Sundarbans is witnessing an overall change in the settlement density pattern. The area under settlement with vegetation is increasing at the expense of the agricultural land. The aquaculture farms are also increasing but not at the same rate which occurred before 2001. The major change which has been observed during this phase of time is the conversion of agricultural land to settlement with vegetation and aquaculture farm. But these changes obviously vary from one block to another. Mainly the predominant characteristic in the South 24 parganas is the conversion of agricultural land to settlement with vegetation but in case of the North 24 Parganas is witnessing a major shift from agricultural land to aquaculture farm. In the recent years the brick kilns have also come up along with the aquaculture farms. These can be seen in the major parts of Minakhan, Hasnabad and Sandeshkhali I & II and Haroa.
- 19 - Plate. No.3. 2
Plate. No.3. 3
- 20 - Block Name : Basanti District Name : South 24 Parganas
Table 3.1: Jharkhali Island (Basanti Block)
SL NO LANDUSE CLASSES 2001 2009 1 Dense Forest 9.627 5.020 2 Settlement with Vegetation 49.375 63.832 3 Agricultural Land / Orchards 72.592 65.081 4 Aquaculture Farm 7.955 5.040 5 Aquaculture Farm (Dry) -- 6 Water Body / Marsh / Swamp 8.257 6.699 7 Mud Flats 1.287 2.822 8 Reclaimed Land 13.451 12.400 Total 162.544 160.894
Table 3.2: Basanti Mainland (Basanti Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 1.692 1.786 2 Settlement with Vegetation 45.207 60.837 3 Agricultural Land / Orchards 112.713 90.871 4 Aquaculture Farm 16.368 27.194 5 Aquaculture Farm (Dry) 1.924 - 6 Water Body / Marsh / Swamp -4.433 8 Mud Flats 1.370 1.738 Total 186.605 186.859
- 21 - Plate. No.3. 4
Plate. No.3. 5
- 22 - Block Name : Kultali District Name : South 24 Parganas
Table 3.3 : Kultali Mainland (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 2.461 5.841
2 Settlement with Vegetation 45.673 77.568 3 Agricultural Land / Orchards 130.10 93.818 4 Aquaculture Farm 9.784 10.651 5 Aquaculture Farm (Dry) 5.206 7.573 6 Water Body / Marsh / Swamp 0.128 8 Mud Flats 0.585 Total 195.957 195.451
Table 3.4 : Gurguria Island (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 3.523 4.056 2 Settlement with Vegetation 29.264 32.640 3 Agricultural Land / Orchards 32.305 25.382 4 Aquaculture Farm 2.622 5.197 5 Aquaculture Farm (Dry) 0.041 - 6 Water Body / Marsh / swamp 0.496 0.583 8 Mud Flats -0.059 Total 68.251 67.917
- 23 - Plate. No. 3.6
Plate. No.3. 7
- 24 - Block Name : Canning I & II District Name : South 24 Parganas
Table 3.5.: Canning I & II
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 1.949 3.847 2 Settlement with Vegetation 130.626 150.714 3 Agricultural Land 235.798 141.848 4 Aquaculture Farm 28.528 115.015 5 Aquaculture Farm (Dry) 7.696 - 6 Water Body / Marsh - 16.324 7 Mud Flats 0.599 - 8 Other vegetation 19.527 17.870 9 Swamp 14.847 - Total 439.570 445.618
Plate. No.3. 8
- 25 - Plate. No.3. 9
Table 3.6 Gosaba Mainland
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 10.725 4.622 2 Settlement with Vegetation 100.425 103.136 3 Agricultural Land 164.893 182.372 4 Aquaculture Farm 8.897 5.712 5 Aquaculture Farm (Dry) 13.613 0.198 6 Water Body / Marsh 4.287 2.408 9 Other vegetation 0 5.077 Total 304.05 303.525
- 26 - Plate. No.3. 10
Plate. No. 3. 11
- 27 - Block Name : Jaynagar I & II District Name : South 24 Parganas
Table 3.7.: Jaynagar I & II
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 0.760 0.627 2 Settlement with Vegetation 126.845 161.300 3 Agricultural Land / Orchards 176.735 152.723 4 Aquaculture Farm 7.953 2.406 5 Aquaculture Farm (Dry) 6.845 6 Water Body / Marsh / Swamp 9.584 2.020 7 Mud Flats - Total 322.722 322.076
Plate. No.3. 12
- 28 - Plate. No.3. 13
Block Name : Mathurapur I & II District Name : South 24 Parganas
Table 3. 8.: Mathurapur I & II
SL LANDUSE CLASSES NO 2001 2004 2009 1 Dense Forest 9.039 14.897 10.899 2 Settlement with Vegetation 112.542 115.487 123.931 3 Agricultural Land 235.570 235.226 230.312 4 Aquaculture Farm 13.434 9.421 9.771 5 Aquaculture Farm (Dry) 1.096 5.322 - 6 Water Body / Marsh / Swamp 3.096 4.096 1.655 7 Mud Flats - 0.766 - Total 377.004 376.348 376.568
- 29 - Plate. No.3. 14
- 30 - Plate. No.3. 15
Block Name : Kakdwip District Name : South 24 Parganas
Table 3.9.: Kakdwip
SL LANDUSE CLASSES NO 2001 2004 2009 1 Dense Forest 2.912 2.882 2.674 2 Settlement with Vegetation 68.875 80.433 97.796 3 Agricultural Land / Orchards 146.427 133.743 125.461 4 Aquaculture Farm 8.356 8.147 6.576 5 Aquaculture Farm (Dry) 3.714 4.377 - 6 Water Body / Marsh / swamp 2.528 3.213 4.670 8 Mud Flats - - - Total 232.812 232.795 237.177
- 31 - Plate. No. 3. 16
Plate. No.3. 17
- 32 - Table 3.10.1: Namkhana Island (Namkhana Block)
SL LANDUSE CLASSES NO 2001 2004 2009 1 Dense Forest 11.144 11.519 13.059 2 Settlement with Vegetation 54.666 58.975 74.262 3 Agricultural Land / Orchards 60.091 63.414 48.902 4 Aquaculture Farm 12.461 7.351 5.541 5 Aquaculture Farm (Dry) 5.465 1.748 - 6 Water Body / Marsh / Swamp 1.085 0.726 1.609 7 Sand (Beaches/Dunes) 2.662 2.687 2.113 8 Mud Flats - 4.838 1.389 Total 147.574 147.258 146.875
Table 3.10.2: Namkhana Mainland (Namkhana Block)
SL LANDUSE CLASSES NO 2001 2004 2009 1 Dense Forest 1.145 1.637 1.322 2 Settlement with Vegetation 20.026 20.603 24.938 3 Agricultural Land/Orchard 24.269 25.114 21.311 4 Aquaculture Farm 2.725 2.427 1.566 6 Water Body / Marsh / Swamp 0.023 0.536 0.184 7 Mud Flats 1.312 1.488 - Total 50.662 49.658 49.321
Table 3.10.3: Moushuni Island (Namkhana Block)
SL LANDUSE CLASSES NO 2001 2004 2009 1 Dense Forest 0.974 2.029 2.076 2 Settlement with Vegetation 12.567 12.655 14.190 3 Agricultural Land / Orchards 12.285 11.003 9.631 4 Aquaculture Farm 2.631 0.410 1.440 5 Aquaculture Farm (Dry) 0.736 0.176 - 6 Water Body / Marsh/ Swamp 0.436 1.155 0.363 7 Sand (Beaches/Dunes) 0.431 0.411 0.239 8 Mud Flats 1.559 0.502 0.116 Total 30.063 30.051 28.055
- 33 - Plate. No. 3.18
Plate. No.3. 19
- 34 -
Block Name : Patharpratima District Name : South 24 Parganas
Table 3. 11.1: Patharpratima Mainland (Patharpratima Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 3.514 4.654 2 Settlement with Vegetation 40.894 62.894 3 Agricultural Land / Orchards 78.835 57.359 4 Aquaculture Farm 3.713 5.901 5 Aquaculture Farm (Dry) 2.653 6 Water Body / Marsh / Swamp 1.655 0.952 8 Mud Flats - Total 131.264 131.760
Table 3.11.2: Patharpratima Island (Patharpratima Block)
Slno LANDUSE CLASSES 2001 2009 1 Dense forest 27.938 30.906 2 Settlement with vegetation 121.577 178.266 3 Agricultural land / Orchards 142.865 98.269 4 Aquaculture farm 22.018 10.003 5 Aquaculture farm (dry) 3.868 5.508 6 Water body / Marsh 7.577 3.927 7 Sand Beaches / dunes 2.607 0.701 8 Other vegetation 0 0.636 328.45 328.216
- 35 - Plate. No.3. 20
Plate. No.3. 21
- 36 - Block Name : Sagar District Name : South 24 Parganas
Table 3.12.1: Ghoramara Island (Sagar Block)
SL NO LANDUSE CLASSES 2001 2009 2 Settlement with Vegetation 2.432 2.438 3 Agricultural Land 2.021 2.051 4 Aquaculture Farm -- 6 Water Body / Marsh 0.043 - 7 Sand (Beaches/Dunes) -0.020 8 Mud Flats 0.853 - 9 Other vegetation -- Total 5.349 4.509
Table 3.12.2: Sagar Island (Sagar Block)
SL NO LANDUSE CLASSES 2001 2009 1 Dense Forest 2.160 9.191 2 Settlement with Vegetation 89.922 133.540 3 Agricultural Land / Other 132.480 81.043 vegetation 4 Aquaculture Farm 4.841 6.162 5 Aquaculture Farm (Dry) 0.000 - 6 Water Body / Marsh / 0.185 1.991 Swamp 7 Sand (Beaches/Dunes) 2.980 2.881 8 Mud Flats 11.737 6.232 Total 244.305 241.040
- 37 - Plate. No.3. 22
Plate. No.3. 23
- 38 - Block Name : Hasnabad District Name : North 24 Parganas
Table 3.13.: Hasnabad
SL LANDUSE CLASSES NO 2001 2009 1 Settlement with Vegetation 65.511 67.203 2 Agricultural Land / Orchards 27.956 28.483 3 Aquaculture Farm 11.043 39.575 4 Aquaculture Farm (Dry) 55.412 3.771 5 Water Body / Marsh / Swamp -- Total 159.922 161.359
Plate. No. 24
- 39 - Plate. No.3.25
Block Name : Hingalganj District Name : North 24 Parganas
Table 3.14.1: Hingalganj North (Hingalganj Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 0.240 0.030 2 Settlement with Vegetation 34.483 40.688 3 Agricultural Land / Orchards 60.142 49.163 4 Aquaculture Farm 5.069 9.122 5 Aquaculture Farm (Dry) 2.047 6 Water Body / Marsh / Swamp 1.912 3.331 8 Mud Flats 0.150 Total 102.131 102.334
- 40 - Table 3.14.2: Hingalganj Island (Hingalganj Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 26.803 25.923 2 Settlement with Vegetation 28.450 35.474 3 Agricultural Land / Orchards 74.549 66.749 4 Aquaculture Farm 2.046 1.495 5 Aquaculture Farm (Dry) 0.448 - 6 Water Body / Marsh / Swamp 1.993 2.109 7 Mud Flats -- Total 134.289 131.75
Plate. No. 26
- 41 - Plate. No. 27
Block Name : Haroa District Name : North 24 Parganas
Table 3.15.: Haroa
SL NO LANDUSE CLASSES 2001 2004 2009 1 Dense Forest - - - 2 Settlement with Vegetation 45.205 37.737 46.701 3 Agricultural Land 10.199 - 10.492 4 Aquaculture Farm 65.404 83.718 93.055 5 Aquaculture Farm (Dry) 24.725 6.051 0.466 6 Water Body / Marsh 0.963 4.565 3.129 9 Other vegetation 12.391 17.540 4.951 10 Swamp - 9.179 - Total 158.887 158.790 158.794
- 42 - Plate. No.3. 28
Plate. No.3. 29
- 43 -
Block Name : Minakhan District Name : North 24 Parganas
Table 3.16.: Minakhan
SL LANDUSE CLASSES NO 2001 2004 2009 1 Settlement with Vegetation 36.620 22.453 44.405 2 Agricultural Land / Orchards 16.258 21.067 2.410 3 Aquaculture Farm 51.543 69.502 108.208 4 Aquaculture Farm (Dry) 43.668 30.516 - 5 Water Body / Marsh - 0.694 0.808 6 Other Vegetation 8.538 12.188 - Total 156.537 156.420 155.831
- 44 - Plate. No. 3.30
Plate. No.3. 31
- 45 - Block Name : Sandeshkhali I & II District Name : North 24 Parganas
Table 3.17.: Sandeshkhali I & II
SL LANDUSE CLASSES NO 2001 2004 2009 1 Dense Forest - - 0.749 2 Settlement with Vegetation 65.574 69.577 69.677 3 Agricultural Land / Orchards 159.605 142.647 107.515 4 Aquaculture Farm 109.747 119.073 161.528 5 Aquaculture Farm (Dry) 15.943 8.741 0.426 6 Water Body / Marsh / Swamp 0.516 11.298 2.913 8 Mud Flats - - Total 351.385 351.336 342.808
- 46 - Chapter IV
Assessment of Air and Sea Surface Temperature, Rainfall, Cyclones and Sea level
- 47 - 4.1 Sea surface temperature:- One of the major consequences of global warming is the sea level rise, both through direct ocean warming causing thermal expansion and through a melting of continental and polar ice sheets. (T. M. Ali Khan et al.2005). Day time (11µ) AQUA MODIS level 3 sea surface temperature (SST) data (of 4 Km×4 Km resolution) have been used to study the monthly sea surface temperature of the study area in the Bay of Bengal (Range of Lat/Long). The monthly composite data were derived from the year 2003 to 2009. ERDAS-IMAGINE and ENVI softwares were used for processing of the data. The flow diagram below explains the methodology : MODIS SST DATA
Geometric Atmospheric Radiometric Correction Correction Correction
Subsetting the Area of Interest
Extracting SST
Analyzing
Fig 4.1. 1:- Extraction of Sea Surface Temperature from MODIS SST data:
- 48 - 2003/JUNE
2004/JUNE 2005/JUNE
2007/JUNE 2006/JUNE
2009/JUNE
2008/JUNE
Fig: 4 .1.2 Annual Change of SST over the Bay of Bengal
- 49 - 28.3
28.2 28.1 28 27.9
27.8 27.7 27.6 27.5
27.4 27.3 2003 2004 2005 2006 2007 2008 2009
The annual composite SST data during the study period 2003-2009 varied from 28.023 oC in the year 2004 to 29.381 oC in the year 2009. During this period the SST showed rising trend at the rate of 0.0453 oC/ year and reached the highest level in the last year under study. This rate observed from the present study is found to be in conformity with the estimation done by Singh (2000), which estimates a decadal rate of about 0.4 o to 0.5 o C.
Air Temperature:
CHANGE OF ANNUAL MEAN AIR TEMPERATURE AT THE HALDIA STATION (2002-2009)
28.5
28
27.5
27
26.5
26
2002 2003 2004 2005 2006 2007 2008 2009
TEM PERATURE IN DEGREE y = 0.1058x + 26.856 CENTIGRATE R2 = 0.3688 - 50 -
Annual mean air temperature was studied at the Haldia Station for the years 2002 to 2009. The data was processed from the daily maximum and minimum temperature recorded by the Indian Meteorological Department (IMD). The annual mean air temperature varied from 27.09385 o C in the year 2004 to 28.14508 in the year 2009. The significant increasing trend showed a temperature rise at the rate of 0.1058 o C per year. The rate of temperature rise which is depicted from the study is as alarming as 1 o C in a decade. This anomaly may be due to formation of a local heat pool due to the presence of the industrial hub.
4.2 Annual rainfall:- The rainfall over the Bay of Bengal has been extracted from TRMM Microwave Imager (TMI) data. The TMI is a nine-channel passive microwave radiometer based upon the Special Sensor Microwave/Imager (SSM/I). The key differences are the addition of a pair of 10.7-GHz channels with horizontal and vertical polarizations and a frequency change of the water vapor channel from 22.235 to 21.3 GHz. This change off the center of the water vapor line was made in order to avoid saturation in the tropical orbit of Tropical Rainfall Measuring Mission (TRMM) satellite. In addition, the TMI has significantly higher spatial resolution than SSM/I due to the lower orbit of the TRMM satellite.
- 51 - Fig. 4.2.1. : Annual Rainfall over Bay of Bengal
July2003 July2004
July2005 July2006
July2007 July2008July2008
July2009
Fig. 4.2.2. Changing Rainfall pattern over the Bay of Bengal (2003-2009)
- 52 -
Rainfall over Bay of Bengal From 2003 to 2009
28.5
28.4
28.3 28.2 mm/hr 28.1 28 27.9
27.8 2003 2004 2005 2006 S1 2007 Year 2008 2009
COMPARISON OF RAIN FALL IN THE HALDIA STATION AND BAY of BENGAL (2002-2008)
54 0.32
52 0.31
50 0.3
RAIN FALL IN mm AT 48 0.29 HALDIA RAIN FALL IN mm IN THE 46 0.28 BOB
44 0.27
42 0.26
40 0.25 123456
- 53 -
From the annual data it has been noticed that the rainfall has been increased over the Bay of Bengal during the study period. It is also evident from the study that the monsoonal rain fall (Figure 4.2.3) has significantly increased at the rate of 0.0041 mm/hr, along with SST. The rain fall pattern at the Haldia station was studied during the same time span. The study revealed no significant trend of change during this time. The comparison of change in rain fall between Haldia observatory and whole Bay of Bengal revealed same type of alteration in every consecutive year except for the last two years of the study period.
Fig. 4.2.3. Increasing Monsoonal Rainfall over the Bay of Bengal (2003-2009)
TREND OF MONSOONAL RAIN FALL OVER THE BAY OF BENGAL
0.51 0.49 0.47 RAIN FALL in 0.45 mm/hr 0.43 TREND LINE
0.41
0.39
0.37 y = 0.0041x + 0.4282
0.35 R2 = 0.1221 2003 2004 2005 2006 2007 2008 2009
- 54 - 4.3. Study of Cyclone Intensity and Frequency over the Bay of Bengal
A "Cyclonic Storm" or a "Cyclone" is an intense vortex or a whirl in the atmosphere with very strong winds circulating around it in anti-clockwise direction in the Northern Hemisphere and in clockwise direction in the Southern Hemisphere.
Cyclones are intense low pressure areas - from the centre of which pressure increases outwards- The amount of the pressure drop in the centre and the rate at which it increases outwards gives the intensity of the cyclones and the strength of winds.
According to the criteria followed by the Meteorological Department of India, low pressure systems in the Bay of Bengal and in the Arabian Sea can be classified as under :
A full-grown cyclone is a violent whirl in the atmosphere 150 to 1000 km across, 10 to 15 km high. Gale winds of 100 to 250 kmph or more spiral around the center of very low pressure area with 30 to 100 hPa** below the normal sea level pressure. The central calm region of the storm is called the "Eye". The diameter of the eye varies between 30 and 50 km and is a region free of clouds and has light winds. Around this
- 55 - calm and clear eye, there is the "Wall Cloud Region" of the storm about 5O km in extent, where the gale winds, thick clouds with torrential rain, thunder and lightning prevail. Away from the "Wall Cloud Region", the wind speed gradually decreases. However, in severe cyclonic storms, wind speeds of 50 to 60 kmph can occur even at a distance of 600 km from the storm centre. The gales give rise to a confused sea with waves as high as 20 metres, swells that travel a thousand miles. Torrential rains, occasional thunder and lightning flashes - join these under an overcast black canopy. Through these churned chaotic sea and atmosphere, the cyclone moves 300 to 500 km, in a day to hit or skirt along a coast, bringing with it storm surges as high as 3 to 12 metres, as if splashing a part of the sea sometimes up to 30 km inland leaving behind death and destructions.
Cyclones in the Bay of Bengal
Cyclones form in certain favorable atmospheric and Oceanic conditions. There are marked seasonal variations in their places of origin, tracks and attainment of intensities. These behaviors help in predicting their movements.
Cyclones affect both the Bay of Bengal and the Arabian Sea. They are rare in Bay of Bengal from January to March. Isolated ones forming in the South Bay of Bengal move west north westwards and hit Tamil Nadu and Sri Lanka coasts. In April and May, these form in the South and adjoining Central Bay and move initially northwest, north and then recurve to the northeast striking the Arakan coasts in April and Andhra-Orissa- West Bengal-Bangla Desh coasts in May. Most of the monsoon (June - September) storms develop in the central and in the North Bay and move west-north-westwards affecting Andhra-Orissa-West Bengal coasts. Post monsoon (October-December) storms form mostly in the south and the central Bay, recurve between 15o and 18o N affecting Tamil Nadu-Andhra Orissa-West Bengal-Bangla Desh coasts.
Pre and Post-monsoon storms are more violent than the storms of the monsoon season. Life span of a severe cyclonic storm in the Indian seas averages about 4 days from the time it forms until the time it enters the land. Severe Cyclonic Storms over Bay of Bengal registered 26% increase over last 120 years, intensifying in post monsoon, Fig. 4.3. (Singh, 2007). Cyclones bring strong wind, heavy rainfall and flooding,
- 56 - resulting in severe coastal erosion and embankment failure. The decadal frequency of storms from 1891 to 1961 as per the record of Indian Metrological Department (1964) indicate that a maximum of 56 cyclones have occurred from 1921–1930, while a minimum of 32 have been reported for 1951–1960. (Gopinath and Seralathan, 2005).
Present Situation
During the study period, both the Frequency and Intensity of Severe Cyclonic Storm has increased in the northern Bay of Bengal (Fig. 4.3.1). During 1999 to 2005, while ther were number of depressions only three could be materialized into severe and super- cyclonic storms. Whereas in the next four years, seven such cyclonic storms have been generated from the similar number of depressions (Table 4.3.1) from the Northern part of the Bay of Bengal. This closely corresponds to the rise in the Sea Surface Temperature as discussed in the previous section. It appears that severe and super cyclonic storms are increasing in frequency during recent years, which creates an alarming situation for Sundarban in the perspective of Climate Change.
- 57 - Table : 4.3.1. Severe Cyclones over Northern Bay of Bengal
Name of the Date of Occurrence Speed Category
Cyclone (Knots)
28th October, 1999 >140 Super Cyclonic Storm
28th October, 2000 <40 Cyclonic Storm
19th May, 2003 <60 Severe Cyclonic Storm
17th May, 2004 <60 Severe Cyclonic Storm
2nd October, 2005 <40 Cyclonic Storm
Mala 24th April, 2006 >120 Super Cyclonic Storm
Not given 13th May, 2007 <60 Severe Cyclonic Storm
Sidr 15th November, >120 Super Cyclonic Storm
2007
Not given 28th June, 2007 >120 Super Cyclonic Storm
Rashmi 26th October, 2008 >40 Cyclonic Storm
Nargis 27th April, 2008 <120 Very Severe Cyclonic
Storm
Bijli 16th April,2009 <60 Severe Cyclonic Storm
Aila 24th May, 2009 <60 Severe Cyclonic Storm
Fig. 4.3.1. Increasing Frequency of Severe Cyclones over Northern Bay of Bengal
FREQUENCY OF CYCLONIC STORM OVER NORTHERN BAY OF BENGAL 3.5
3
2.5
2 NUMBER OF CYCLONIC 1.5 STORM TREND LINE 1
0.5 y = 0.1818x + 0.0909 R2 = 0.4762 0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 -0.5 - 58 - In the next part of the chapter Fig. 4.3.2. depicts 14 such cyclones of the northern Bay of Bengal along with date, wind speed, track and corresponding sea surface temperature. Fig. 4.3.3. is reproduced from the publication of Singh, 1997 in ‘Mousam’ which indicates a 26% rise in the number of severe cyclones over Bay of Bengal in past 120 years
Fig. 4.3.2 : Wind Speed, Track and SST of the Cyclones generated in Northern Bay of Bengal
- 59 -
- 60 -
- 61 -
- 62 -
- 63 -
- 64 - Fig: 4.3.3. -Rise of frequency of Severe Cyclonic Storms OVER Bay of Bengal.
- 65 - Chapter V Sea Level Change
- 66 - INTRODUCTION:- The islands in the tropical oceans are some of the regions most vulnerable to sea-level rise and the associated impacts of climate change. These impacts include changes in weather patterns (temperature, winds, precipitation etc.), sea-level rise, coastal erosion, changes in the frequency of extreme events including potential increases in the intensity of tropical cyclones/hurricanes, reduced resilience of coastal ecosystems and saltwater intrusion into freshwater (J.A. Church et al.,2006). Global warming is the immediate threats to mankind and tropical regions are the most vulnerable to them. (Kumar et.al.2009). Greenhouse warming not only increases the air temperature, but also increases the SST (Manabe and Stouffer, 1980). One of the major consequences of global warming is the sea level rise, both through direct ocean warming causing thermal expansion and through a melting of continental and polar ice sheets. Both effects will lead to an increase in the volume of the oceans and relative sea level rise (Ali Khan. et al.2000). Another indirect cause of rising sea level, in addition to thermal expansion due to global warming is an increased rate of evaporation and subsequent rise in rainfall at some locations (O.P.Singh, 2000). As predicted by different studies both global mean temperature and global mean sea level are rising (Hansen et al., 1981; Gornitz et al., 1982; Mitchell et al., 1990; Gates et al., 1992; Singh et al., 2000). Sea level is rising globally at a rate of 1 to 2 mm/year (Gornitz, Lebedeff, and Hansen 1982) which may accelerate by a factor of 10 over the present rates (Ali Khan et al.,2000) and ultimately may lead to rise of the sea level as much as 3m by the year 2100 (Ortiz 1994). The IPCC predicts that average global temperatures will increase between 1.8°C and 5.8°C over the next century, and sea level will rise between 9 and 88 centimeters (IPCC, 2001). Sundarbans, the only mangrove tiger land of the globe, is presently under the threat of severe coastal erosion due to relative sea level rise (Hazra et al. 2003). To understand the total climetological system of this area, study on Sea surface temperature and rain fall over the Bay of Bengal has been attempted , as because these are the two major influencing parameters over the climate of the sunderbans. The relative sea level change has been measured from observed tide data of the period between 2002-2009. However, though tidal measurement from land can not be free from the data of land level change (subsidence, uplift, compaction of sediments, near shore siltation) this measured over a longer period gives a fairly correct estimate of the
- 67 - mean sea level persisting over the study area. For any coastal vulnerability analysis also, it is the relative sea level rather than some abstract mathematical or global value becomes more useful as only that contributes to the erosion, inundation and invasion of sea on the land area of the region.
Fig 5.1.Change In the Relative Mean Sea Level measured at Sagar Observatory:, Sundaraban
ANNUAL TREND OF MEAN TIDE LEVEL AT THE SAGAR ISLAND STATION (2003-2009)
3150
3100
3050 MTL in metre
3000
2950
2900 2003 2004 2005 2006 2007 2008 2009
The Relative Mean Sea Level of the Sundarban was studied by tide gauge situated at the Sagar island station. The Data of Mean Tide Level (MTL) indicated a rise in the Relative Mean Sea Level (RMSL) at the rate of 17.8 mm/ year. The general trend showed rising in every consecutive year from the previous year except in the year 2004 and 2006. From the year 2003 to 2006 the MTL showed a decreasing trend at the rate of 9.73 mm per year. In contrast with that the trend showed a rising trend as high as 4.71 cm per year during the period of 2006 to 2009.
- 68 - Considering the seasonal variability of the sea level change it is observed the rate of sea level rise is more pronounced in the pre monsoon period probably forced by the rise in sea surface temperature, while the rise is post monsoon is contributed mostly by increased surface runoff during this period in the BOB aided by cyclone induced rainfall and winter monsoon rainfall
- 69 - Fig. 5.2 Seasonal variability of the relative Mean Sea level with Rainfall and SST
PRE-MONSOON TREND OF MTL
3.05
3
2.95
2.9 MTL IN METRE 2.85 TREND LINE 2.8 y = 0.0263x + 2.7888 2.75 R2 = 0.669 2.7 2003 2004 2005 2006 2007 2008 2009
MONSOON TREND OF MTL
3.34 3.32 3.3 3.28 3.26 MTL IN METRE 3.24 TREND LINE 3.22 3.2 3.18 y = 0.0094x + 3.2442 3.16 R2 = 0.2423 3.14 2003 2004 2005 2006 2007 2008 2009
POST-MONSOON TREND OF MTL
3.05 3
2.95
2.9 MTL IN METRE 2.85 TREND LINE 2.8 y = 0.0179x + 2.8395 2.75 R2 = 0.3095 2.7 2003 2004 2005 2006 2007 2008 2009
- 70 -
INTER ANNUAL CHANGE OF MEAN TIDE LEVEL WITH RAINFALL (2003-2009)
3.15 0.32 0.31 3.1 0.3 MEAN TIDE LEVEL 3.05 0.29 IN METRE 0.28 RAIN FALL IN 3 mm/ hour 0.27 2.95 0.26 2.9 0.25 2003 2004 2005 2006 2007 2008 2009
INTER ANNUAL CHANGE OF MEAN TIDE LEVEL WITH SST (2003-2009)
3150 28.8
28.6 3100 28.4 28.2 3050 MEAN TIDE LEVEL IN 28 METRE 27.8 3000 SST IN DEGREE 27.6 CELCIUS
2950 27.4 27.2 2900 27
2003 2004 2005 2006 2007 2008 2009
Fig. 5.3 Correlation of Observed Mean Sea level with Rainfall and SST
During this seven year of study period, MTL of the Sundarbans varied in close correlation with the SST and/or Rainfall in the Bay of Bengal, except in the year 2007. However, beside these two main factors, subsidence, siltation and other local causes may be responsible for the exceptionally high rate of relative sea level rise in Sundarban. .
- 71 -
INTRA ANNUAL TREND OF MTL (2003-2009)
3.6 3.4 2003 2004 3.2 2005 3 2006 2007 2.8 2008 2.6 2009
2.4
h il y y r r a ne l e u Ju ber b ber Ap M J m to m Marc Augustte c JanuaryFebruary p O Se Nove December
Fig. 5.4 Intra annual Changes of the relative Sea level during the study period
Apart from the inter annual change, the intra-annual changes showed, the MTL starts to rise in the months of March and April, subsequently takes a steep rise in the months of May and June. On the ongoing months of monsoon, the MTL retain higher rate of rise , followed by declining trends in the post monsoon months. The MTL of the Pre-monsoon (February, March, April and May), Monsoon (June, July, August and September) and Post-monsoon (October, November, December and January), were studied to understand the seasonal trend of RMSL. The MTL in the monsoon showed an increasing trend at the rate 9.4 mm per year. As, rainfall prevails as governing factor of MTL in the monsoon , it can be inferred from the observation, that the rise of 9.4 mm per year in the MTL is due to rise in the rainfall. Taking the rising SST and Rainfall, as the principal causes of rise in RMSL, it can be observed from the study, that the rest of the rise i.e. 8.4 mm per year is due to rise in SST. Although, many workers have considered rising rate of rainfall as an indirect effect of rising rate in SST, as it promotes higher rate of evaporation and precipitation.
- 72 -
Study of the Relative mean sea level at the Sagar island observatory from the year 1985 to recent year revealed a rate of 8.63 mm rise per year.
Rise in Relative Mean Sea Level at Sagar Island Station 3200
3150 Relative Mean Sea 3100 Level in mm
3050 Linear (Relative Mean Sea Level in mm) 3000 y = 8.6388x - 14169 2950 R2 = 0.7547 1980 1985 1990 1995 2000 2005 2010
- 73 - Chapter VI Forest Cover Change
- 74 - FORESTS OF INDIAN SUNDARBANS
The Sundarbans has been classified as a moist tropical forest . Historically three principal vegetation types have been recognized in broad correlation with varying degrees of water salinity, freshwater flushing and physiography which are represented in the wildlife sanctuaries:
Sundari and Gewa occur prominently throughout the area with discontinuous distribution of Dhundul (Xylocarpus granatum) and Kankra. Among grasses and Palms, Poresia coaractata, Myriostachya wightiana, Imperata cylindrica, Phragmites karka, Nypa fruticans are well distributed. Keora is an indicator species for newly accreted mudbanks and is an important species for wildlife, especially for spotted deer (Axis axis). Besides the forest, there are extensive areas of brackish and freshwater marshes, intertidal mudflats, sandflats, sand dunes with typical dune vegetation, open grassland on sandy soils and raised areas supporting a variety of terrestrial shrubs and trees.
In Remote Sensing images, The forests of the Indian Sundarbans have a very bright vegetation signature. The reflectance values are quite high with a small range of variation. Therefore, the categorization in the vegetation reflectance values are difficult to achieve by simple classification methods. The classes which were taken in the present study are 1. Dense Forest, 2. Degraded Forest, 3.Saline Blanks, 4. Water Body, 5. Sand (beaches / dunes), 6. Mud flats and 7. Reclaimed land from forest.
The supervised classification has been carried out to identify the above features in the Sundarban forest part.
The principally observed general change is the transformation of Dense Forest area to Degraded forest and then to Saline blanks. Basically the degraded forests are being transformed into saline blanks. The area under saline blanks are found to have doubled during the given 8 years span. It is most dominant in Herobhanga, Ajmalmari East, West and north west, Dulibhasani East and Dulibhasani west where the saline blanks have increased significantly. Major reclamation of forest area has been observed in Jambudwip under Namkhana block and Jharkhali island under Basanti block. However, this conversion from forest land to reclaimed land took place before 2001.
- 75 - The drivers for such change appears to be increased inundation during high tide, water logging and salt precipitation. It has been reported that some areas are again being recolonised by salt tolerant mangrove species thus forcing migration of freshwater loving species land ward.
The details of forest cover types along with areas are given below along with the respective maps for each island/block.
- 76 - Plate. No. 6.1
Plate. No. 6.2
JAMBU ISLAND
- 77 - Table 6.1 Jambudwip (Namkhana Block)
.SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 3.6 3.6706 2 Degraded Forest 0.711 0.6238 3 Sand (Beaches/Dunes) 0.247 0.2375 4 Mudflats 0.274 0.2575 5 Reclaimed land from forest 1.061 0.2444 Total 5.893 5.0338
Plate. No. 6.3
5 HEROBHANGA
4 HEROBHANGA
6 HEROBHANGA
7 HEROBHANGA 8 HEROBHANGA
- 78 - Plate. No. 6.4
Table 6.20: Herobhanga Island (Basanti Block)
SL LANDUSE CLASSES
NO 2001 2009
1 Dense Forest 31.634 31.1256
2 Degraded Forest 12.119 12.1163
3 Saline Blanks 0.946 1.3969 4 Water body / Marsh 3.66 3.0088 Total 48.359 47.6476
- 79 -
Herobhanga AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense Forest to Degraded Forest 790.2500 7.9025 Dense Forest to Saline Blanks 60.0000 0.6000 Dense Forest to Water body 82.1250 0.8213 Degraded Forest to Dense Forest 274.1875 2.7419 Degraded Forest to Saline Blanks 79.1875 0.7919 Degraded Forest to water body 17.3750 0.1738 Saline Blanks to Dense Forest 0.0000 0.0000 Saline Blanks to Degraded Forest 0.0000 0.0000 Water body to Dense Forest 118.1875 1.1819 Water body to Degraded Forest 51.0000 0.5100 Water body to Saline Blanks 0.5000 0.0050 No Change 3390.5000 33.9050 4863.3125 48.6331
- 80 - Plate. No. 6.5
1 MAYADWIP
2A MAYADWIP
3 MAYADWIP 2B MAYADWIP
Plate. No. 6.6
- 81 - Table 6.30: Dalhousie Island (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 44.676 48.8825 2 Degraded Forest 14.465 6.5969 3 Saline Blanks 1.1668 2.5256 4 Water Body / Marsh / Swamp 8.137 7.4431 5 Sand (Beaches / Dunes) 1.1086 0.5225 Total 69.553 65.9706
The south eastern forested island of Indian Sundarban is divided into the following compartments like 1. Mayadwip 2a. Mayadwip, 2b. Mayadwip, 3. Mayadwip.
- 82 -
Dalhousie AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense Forest to Degraded Forest 364.0000 3.6400 Dense Forest to Saline Blanks 64.3750 0.6438 Dense Forest to Water body 247.1250 2.4713 Erosion 181.3125 1.8131 Degraded Forest to Saline blanks 130.5625 1.3056 Degraded Forest to Water body 137.8750 1.3788 Erosion 131.8125 1.3181 Water body to Degraded Forest 71.1250 0.7113 Water body to Saline blanks 43.0625 0.4306 No change 5696.6250 56.9663 7067.8750 70.6788
Plate. No. 6.7
4A MAYADWIP
5 MAYADWIP 4B MAYADWIP
- 83 -
Plate. No. 6.8
Table 6.4: Bhangaduni Island (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 21.6766 20.2106 2 Degraded Forest 7.0169 3.4644 3 Saline Blanks 0.9112 0.8031 4 Water Body / Marsh / Swamp 2.0239 2.6481 5 Mudflats 0 0 Total 31.629 27.1262
The south eastern t forested island Bhangaduni of Indian Sundarban is divided into the following compartments like 4a. Mayadwip, 4b. Mayadwip, 5. Mayadwip.
- 84 -
Bhangaduni AREA IN AREA IN SQ LANDUSE CHANGE HECTARES KMS Dense Forest to Degraded Forest 121.375 1.2138 Dense Forest to Saline Blanks 11.375 0.1138 Dense Forest to Water body 80.25 0.8025 Erosion 211.75 2.1175 Degraded Forest to Dense Forest 556.8125 5.5681 Degraded Forest to Saline Blanks 40.75 0.4075 Degraded Forest to water body 93.875 0.9388 Erosion 200.0625 2.0006 Saline blanks to Dense Forest 6.625 0.0663 Saline blanks to Degraded Forest 16 0.1600 Erosion 30.1875 0.3019 Water body to Dense Forest 49.0625 0.4906 Water body to Degraded Forest 30.375 0.3038 Water body to Saline blanks 5.25 0.0525 Erosion 56.8125 0.5681 Degraded Forest 15.5625 0.1556 Saline Blanks 0.9375 0.0094 Water body 21.875 0.2188 Erosion 11.875 0.1188 No change 1662.5 16.6250 3223.3125 32.2331
- 85 - Plate. No. 6.9
1 CHAMTA 3 CHAMTA 2 CHAMTA 4 CHAMTA 6 CHAMTA 1 CHANDKHALI 5 CHAMTA 2 CHANDKHALI 7 CHAMTA
8 CHAMTA 3 CHANDKHALI
4 CHANDKHALI
1 BAGMARA 2 GONA 1 GONA 3 BAGMARA
7 BAGMARA 4 BAGMARA 3 GONA 5 BAGMARA
8A BAGMARA 6 BAGMARA
Plate. No. 6.10
- 86 -
Table 6.5: Gosaba Island (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 399.15 399.15 2 Degraded Forest 77.042 77.042 3 Saline Blanks 6.2077 6.2077 4 Water Body / Marsh / Swamp 23.847 23.847 5 Sand (Beaches / Dunes) 0.4624 0.4624 Total 506.71 506.71
The Goasaba forest island is divided into the following compartments like 1. Chamta, 2. Chamta, 3. Chamta 4. Chamta, 5. Chamta 6. Chamta, 7. Chamta & 8. Chamta; 1. Chandkhali 2. Chandkhali 3. Chandkhali & 4. Chandkhali; 1. Gona, 2. Gona, 3. Gona; and 1. Bagmara, 2. Bagmara 3. Bagmara 4. Bagmara 5. Bagmara 6. Bagmara 7. Bagmara 8a. Bagmara
- 87 -
* DATA NOT AVAILABLE
Gosaba AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense Forest to Degraded Forest 1691.5 16.9150 Dense Forest to Saline Blanks 191.4375 1.9143 Dense Forest To Water body 488.875 4.8887 Degraded Forest to Dense Forest 3375.1875 33.7518 Degraded Forest to Saline Blanks 348 3.4800 Degraded Forest to Water body 128.5 1.2850 Saline Blanks to Dense Forest 7.375 0.0738 Saline Blanks to Degraded Forest 1.375 0.1375 Saline Blanks to water body 0.875 0.0088 Water Body to Degraded Forest 399.125 3.9913 Water Body to Saline Blanks 2.8125 0.0281 No change 100671.4 1006.7100 107306.4625 1073.1842
- 88 - Plate. No. 6.11
MALMELA 1 JHILLA FLOATING CAMP
2 JHILLA
3 JHILLA
4 JHILLA
5 JHILLA
6 JHILLA
Plate. No. 6.12
- 89 - Table 6.6: Jhilla Island (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 64.2172 55.4244 2 Degraded Forest 18.744 24.5644 3 Water Body / Marsh 7.2165 8.8 Total 90.1774 88.7888
The Jhilla forested island is divided into the following compartments like 1. Jhilla, 2. Jhilla, 3. Jhilla 4. Jhilla, 5. Jhilla & 6. Jhilla under Malmela Floating camp.
- 90 -
Jhilla AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense forest to Degraded Forest 1280.6250 12.8063 Dense Forest to water Body 410.5000 4.1050 Degraded Forest to Dense forest 633.6250 6.3363 Degraded Forest to water body 155.1875 1.5519 Water body to Dense Forest 108.6875 1.0869 Water body to Degraded Forest 246.3750 2.4638 No Change 6159.0630 61.5906 8994.0630 89.9406
- 91 - Plate. No. 6.13
2 ARBESI
3 ARBESI
BURHIR DABRI CAMP
4 ARBESI
5 ARBESI
KATUAJHURI CAMP 1 HARINBHANGA
1 KATUAJHURI
2 KATUAJHURI
2 HARINBHANGA 3 KATUAJHURI
3 HARINBHANGA
Plate. No. 6.14
- 92 - Table 6.7 Katuajhuri Island (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 220.35 220.35 2 Degraded Forest 42.869 42.869 3 Water body / Marsh / Swamp 10.14 10.14 Total 253.36 253.36
Katuajhuri Forest island is divided into various parts like. 2. Arbeshi, 3. Arbeshi, 4. Arbeshi & 5. Arbeshi under Burhidabri camp, while 1. Harinbhanga, 2. Harinbhanga & 3. Harinbhanga; 1. Katuajhuri, 2. Katuajhuri, 3. Katuajhuri under Katuajhuri camp.
- 93 -
katuajpuri AREA IN AREA IN SQ Landuse Change HECTARES KMS DENSE FOREST TO DEGRADED FOREST 2301.3744 23.0137 DENSE FOREST TO WATER BODY 422.4324 4.2243 DEGRADED FOREST TO DENSE FOREST 1816.3444 18.1634 DEGRADED FOREST TO WATER BODY 373.4224 3.7342 WATER BODY TO DENSE FOREST 370.1776 3.7018 WATER BODY TO DEGRADED FOREST 186.8464 1.8685 EROSION 1206.0516 12.0605 ACCRETION 91.3952 0.9140 NO CHANGE 19392.2768 193.9228 26160.3212 261.6032
- 94 - Plate. No. 6.15
11
12 AJMALMARI
AJMALMARI
Plate. No. 6.16
- 95 - Table 6.8 : Ajmalmari West Island (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 17.414 16.2175 2 Degraded Forest 5.1139 3.1663 3 Saline Blanks 0.338 3.0069 4 Water body / Marsh / Swamp 2.6958 3.3163 Total 25.561 25.707
- 96 -
Ajmalmari west AREA IN AREA IN SQ LANDUSE CHANGE HECTARES KMS Dense Forest to Degraded Forest 228.625 2.2863 Dense Forest to Saline Blanks 183.25 1.8325 Dense Forest to Water body 173.0625 1.7306 Degraded Forest to Saline Blanks 107.375 1.0738 Degraded Forest to Water body 66.9375 0.6694 Saline Blanks to Degraded forest 0.625 0.0063 Water body to Degraded forest 1.9375 0.0194 No change 1808.87 18.0887 2570.6825 25.7068
- 97 - Plate. No. 6.17
4 AJMALMARI
5 AJMALMARI
6 AJMALMARI 7 AJMALMARI
9 AJMALMARI
8 AJMALMARI 10 AJMALMARI
Plate. No. 6.18
- 98 -
Table 6.9 : Ajmalmari East Island (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 35.143 44.7869 2 Degraded Forest 31.919 10.8188 3 Saline Blanks 0.0703 4.7488 4 Water body / Marsh / Swamp 9.7385 15.1563 Total 76.87 75.5108
- 99 -
Ajmalmari east AREA IN AREA IN SQ LANDUSE CHANGE HECTARES KMS Dense Forest to Degraded Forest 600.5 6.0050 Dense Forest to Saline Blanks 156.875 1.5688 Dense Forest to Water body 505.375 5.0538 Degraded Forest to Saline Blanks 315.5625 3.1556 Degraded Forest to Water body 377.3125 3.7731 Saline Blanks to Dense Forest 0.6875 0.0069 Saline Blanks to Degraded forest 0.25 0.0025 Saline Blanks to Water body 0.1875 0.0019 Water body to Dense forest 72.25 0.7225 Water body to Degraded forest 13.4375 0.1344 Water body to Saline blanks 0.625 0.0063 No change 5512.44 55.1244 7555.5025 75.5550
- 100 - Plate. No. 6.19
9 HEROBHANGA 1 AJMALMARI
2 AJMALMARI
2 AJMALMARI
Plate 6.20
- 101 - Table 6.10 : Ajmalmari North-West Island (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 28.334 26.0438 2 Degraded Forest 12.052 10.4769 3 Saline Blanks 2.4363 4.6131 4 Water body / Marsh / Swamp 4.5752 6.1931 Total 47.3977 47.3269
- 102 -
Ajmalmari north west AREA IN AREA IN SQ LANDUSE CHANGE HECTARES KMS Dense Forest to Degraded Forest 320.3125 3.2031 Dense Forest to saline blanks 84.625 0.8463 Dense Forest to water body 263.375 2.6338 Degraded Forest to Dense Forest 723.5625 7.2356 Degraded Forest to Saline Blanks 230.875 2.3088 Degraded Forest to Water body 65.5625 0.6556 Saline Blanks to Dense Forest 21.875 0.2188 Saline Blanks to Degraded Forest 23.1875 0.2319 Saline Blanks to Water body 2.125 0.0213 Water body to Dense Forest 176.375 1.7638 Water body to Degraded Forest 32.5625 0.3256 Water body to Saline Blanks 1.4375 0.0144 No change 2942.94 29.4294 4888.815 48.8882
- 103 - Plate. No. 6.21
6 CHULKATI
7 CHULKATI
8 CHULKATI
Plate. No. 6.22
- 104 -
Table 6.11 Bulchery Island (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 14.857 15.725 2 Degraded Forest 5.736 3.0231 3 Saline Blanks 2.1747 0.8481 4 Water body / Marsh / Swamp 2.3626 2.6056 5 Mudflats 1.1276 0 6 Sand (Beaches/Dunes) 0.4935 0.69 Total 26.751 22.8918
- 105 -
Bulchery AREA IN AREA IN SQ LANDUSE CHANGE HECTARES KMS Dense Forest to Degraded Forest 178.3125 1.7831 Dense Forest to Saline Blanks 34.9375 0.3494 Dense Forest to Water body 172.1250 1.7213 Dense Forest to Mud Flats 17.2500 0.1725 Degraded Forest to Saline blanks 36.2500 0.3625 Degraded Forest Water body 28.1875 0.2819 Degraded Forest to Mud Flats 12.8125 0.1281 Saline blanks to Degraded Forest 11.3750 0.1138 Saline blanks to water body 0.3125 0.0031 Saline Blanks to Mud Flats 3.9375 0.0394 Water body to Degraded Forest 8.0000 0.0800 Water body to Saline blanks 1.5625 0.0156 Water body to Mud flats 4.2500 0.0425 Mud Flats to Dense Forest 10.9375 0.1094 Mud Flats to Degraded Forest 12.5625 0.1256 Mud flats to Saline Blanks 3.2500 0.0325 Mud Flats to Water body 1.1875 0.0119 Sand ( Beaches / Dunes) to Dense Forest 0.0000 0.0000 Sand ( Beaches / Dunes) To Degraded Forest 0.8750 0.0088 Sand ( Beaches / Dunes) to saline Blanks 0.0625 0.0006 Erosion 288.1250 2.8813 No change 1850.8750 18.5088 2677.1875 26.7719
- 106 - Plate. No. 6.23
1 DULIBHASANI
2 DULIBHASANI
6 DULIBHASANI
1 CHULKATI 7 DULIBHASANI
2 CHULKATI 8 DULIBHASANI
3 CHULKATI
4 CHULKATI
5 CHULKATI
Plate. No. 6.24
- 107 -
Table 6.12: Dulibhasani West Island (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 114.1 111.614 2 Degraded Forest 33.393 36.6063 3 Saline Blanks 1.899 3.1863 4 Water body / Marsh / Swamp 22.728 12.9206 5 Mudflats 0 0 Total 172.12 164.327
- 108 -
Dulibhasani west AREA IN Landuse Change HECTARES AREA IN SQ KMS EROSION 216.4552 2.1646 ACCRETION 103.9012 1.0390 NO CHANGE 10279.5264 102.7953 DENSE FOREST TO DEGRADED FOREST 821.7456 8.2175 DENSE FOREST TO SALINE BLANK 60.7048 0.6070 DENSE FOREST TO WATER BODY 178.9372 1.7894 DEGRADED FOREST TO DENSE FOREST 4220.8088 42.2081 DEGRADED FOREST TO SALINE BLANK 313.664 3.1366 DEGRADED FOREST TO WATER BODY 275.47 2.7547 SALLINE BLANK TO DENSE FOREST 50.7 0.5070 SALINE BLANK TO DEGRADED FOREST 66.4508 0.6645 SALINE BLANK TO WATER BODY 19.266 0.1927 WATER BODY TO DENSE FOREST 464.75 4.6475 WATER BODY TO DEGRADED FOREST 231.53 2.3153 WATER BODY TO SALINE BLANK 6.0164 0.0602 17309.9264 173.0993 - 109 - Plate. No. 6.25
4 DULIBHASANI
3 DULIBHASANI
5 DULIBHASANI
Plate. No. 6.26
- 110 -
Table 6.13 : Dulibhasani East Island (Kultali Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 18.122 18.0488 2 Degraded Forest 11.62 7.5788 3 Saline Blanks 0.7382 2.7088 4 Water body / Marsh / Swamp 8.3939 7.1881 Total 37.874 35.5245
- 111 -
Dulibhasani East AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense forest to Degraded Forest 325.9375 3.2594 Dense forest to Saline Blanks 53.1875 0.5319 Dense Forest to Water Body 130.9375 1.3094 Degraded Forest to Dense Forest 230.4375 2.3044 Degraded Forest to Saline Blanks 159.4375 1.5944 Degraded Forest to water body 101.6875 1.0169 Saline blanks to Dense Forest 12.2500 0.1225 Saline blanks to Degraded Forest 3.0000 0.0300 Saline blanks to Degraded Forest 0.1250 0.0013 Water body to Dense Forest 23.8750 0.2388 Water body to Degraded Forest 24.4375 0.2444 No change 502.5000 5.0250 1567.8125 15.6781
- 112 - Plate. No. 6.27
2 THAKURAN
3 THAKURAN
4 THAKURAN
Plate. No. 6.28
- 113 -
Table 6.14: Dhanchi Island (Patharpratima Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 24.0135 24.9844 2 Degraded Forest 9.7966 1.8325 3 Saline Blanks 0.2866 2.3006 4 Water body / Marsh / Swamp 1.0836 2.88 5 Mudflats 0.0791 0 6 Sand (Beaches/ Dunes) 0 0 Total 35.26 31.9975
- 114 -
Dhanchi AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense Forest to Degraded Forest 109.8125 1.0981 Dense Forest to Saline Blanks 64.5625 0.6456 Dense Forest to water body 157.0000 1.5700 Erosion 53.7500 0.5375 Degraded Forest to Dense forest 433.8750 4.3387 Degraded Forest to Saline Blanks 137.1875 1.3718 Degraded Forest to water body 44.6250 0.4462 Erosion 16.2500 0.1625 Saline Blanks to Dense Forest 22.9375 0.2293 Saline Blanks to Degraded Forest 0.3125 0.0031 Saline Blanks to Water body 1.2500 0.0125 Erosion 5.3750 0.0537 Water body to Dense Forest 133.6250 1.3362 Water body to Degraded Forest 13.8125 0.1381 Water body to Saline Blanks 6.0000 0.0600 Erosion 60.5000 0.6050 No change 2316.4375 23.1643 3577.3125 35.7726 - 115 - Plate. No. 6.29
LOTHIAN ISLAND
Plate. No. 6.30
- 116 - Table 6.15: Lothian Island (Namkhana Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 24.947 22.8144 2 Degraded Forest 7.708 9.6581 3 Saline Blanks 0.707 1.1431 4 Water Body / Marsh / Swamp 0.876 0.5425 5 Sand (Beaches/Dunes) 0.699 0.92 Total 34.937 34.1673
- 117 -
Lothian AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense forest to Degraded Forest 352.0625 3.5206 Dense Forest to Saline blanks 14.9375 0.1494 Dense Forest to Water Body 0.3125 0.0031 Dense Forest to Mud Flats 1.1250 0.0113 Degraded Forest to Dense Forest 433.8125 4.3381 Degraded Forest to Saline Blanks 44.5625 0.4456 Degraded Forest to water body 5.3750 0.0538 Degraded Forest to Mud flats 6.8125 0.0681 Saline blanks to Dense Forest 80.3125 0.8031 Saline blanks to Degraded Forest 166.5000 1.6650 Saline Blanks to water body 5.6250 0.0563 Saline blanks to Mud Flats 8.6875 0.0869 Water body to Dense Forest 57.0625 0.5706 Water body to Degraded Forest 5.7500 0.0575 Water body to Saline blanks 0.3125 0.0031 Water body to Mud Flats 6.5625 0.0656 No change 2535.7500 25.3575 3725.5625 37.2556
Plate. No. 6.31
NETIDHOPANI BEAT 1 NETIDHOPANI 2 NETIDHOPANI 3 NETIDHOPANI 1 MATLA
1 GOASABA
2 MATLA
4 MATLA 2 GOASABA 3 MATLA
3 GOASABA 2A CHOTAHARDI
2B CHOTAHARDI
3 CHOTAHARDI
4 GOASABA
- 118 -
Plate. No. 6.32
Table 6.16: Matla Island (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 263.37 266.32 2 Degraded Forest 76.264 46.85 3 Saline Blanks 0 10.4 4 Water Body / Marsh / Swamp 55.91 70.55 5 Mudflats 0 0 Total 395.54 394.12
The Saznekhali North is divided into various parts according to the forest boundary demarcation i.e : 1. Netidhopani , 2. Netidhopani and 3. Netidhopani under Netidhopani Beat ; 1. Goasaba, 2. Goasaba, 3. Goasaba & 4. Goasaba and 1. Matla, 2. Matla, 3. Matla & 4. Matla and 2a. Chotahardi, 2b. Chotahardi and 3. Chotahardi.
- 119 -
Matla AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense Forest to Degraded Forest 2157.4375 21.5744 Dense Forest to Saline Blanks 238.5625 2.3856 Dense Forest to water body 730.3750 7.3038 Degraded Forest to Dense Forest 1312.8750 13.1288 Degraded Forest to Saline Blanks 531.1250 5.3113 Degraded Forest to Water body 720.1250 7.2013 Saline Blanks to Dense Forest 128.7500 1.2875 Saline Blanks to Degraded Forest 9.0000 0.0900 Saline Blanks to Water body 6.1875 0.0619 Water body to Dense Forest 1033.3125 10.3331 Water body to Degraded Forest 1061.6250 10.6163 Water body to Saline blanks 92.1875 0.9219 No Change 31446.0625 314.4606 39467.6250 394.6763
- 120 - Plate. No. 6.33
1 PIRKHALI
DATTAR 2 PIRKHALI BEAT
1 PANCHAMUKHANI
4 3 PIRKHALI 2 PIRKHALI PANCHAMUKHANI
Plate. No. 6.34
- 121 - Table 6.17 Saznekhali North (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 87.798 100.385 2 Degraded Forest 19.343 11.8163 3 Saline Blanks 0 2.9625 4 Water Body / Marsh / Swamp 24.241 13.3056 Total 131.38 128.469
The Saznekhali North is divided into various parts according to the forest boundary demarcation i.e : 1. Panchamukhani; 2. Panchamukhani and 1. Pirkhali, 2. Pirkhali 3. Pirkhali. & 4. Pirkhali under Dattar Beat..
Plate. No. 6.35
3 PANCHAMUKHANI 5 PIRKHALI
4 PANCHAMUKHANI
6 PIRKHALI 5 PANCHAMUKHANI 7 PIRKHALI
- 122 - Plate. No. 6.36
Table 6.18: Sudhyanakhali , Saznekhali South (Gosaba Block)
SL LANDUSE CLASSES NO 2001 2009 1 Dense Forest 129.72 126.684 2 Degraded Forest 28.771 22.8969 3 Saline Blanks 21.048 27.945 Total 179.54 177.526
The Saznekhali south is divided into various parts according to the forest boundary demarcation i.e : 3. Panchamukhani; 4. Panchamukhani and 5. Panchamukhani and 5. Pirkhali, 6. Pirkhali & 7. Pirkhali.
- 123 - SL.NO LANDUSE/LANDCOVER CLASSES YEAR 2001 YEAR 2009 1. DENSE FOREST 1655.878 1651.3275 2. DEGRADED FOREST 404.887 332.0008 3. SALINE BLANKS 38.93 74.7965 4 WATER BODY 232.888 250.6531 TOTAL
Thus in conclusion the forest cover changes in Sundarbans can be reiterated from Chapter III Table 3.1. as follows
Saznekhali AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense Forest to Degraded Forest 616.6250 6.1663 Dense Forest to Saline Blanks 240.5000 2.4050 Dense Forest to water body 54.4375 0.5444 Degraded Forest to Dense Forest 606.9375 6.0694 Degraded Forest to Saline Blanks 52.5625 0.5256 Degraded Forest to Water body 23.7500 0.2375 Water body to Degraded forest 1188.0625 11.8806 Water body to Degraded forest 157.5000 1.5750 Water body to Saline Blanks 3.0625 0.0306 No Change 10117.0000 101.1700 13060.4375 130.6044
- 124 -
Sudhyanyakhali AREA IN AREA IN SQ Landuse Change HECTARES KMS Dense Forest to Degraded Forest 1807.6875 18.0769 Dense Forest to Saline Blanks 0.0000 0.0000 Dense Forest to Water body 558.5000 5.5850 Degraded Forest to Dense Forest 2012.2500 20.1225 Degraded Forest to Water Body 599.9375 5.9994 Saline Blanks to Dense Forest 45.1250 0.4513 Saline Blanks to Degraded Forest 5.1250 0.0513 Saline Blanks to water body 4.0625 0.0406 Water body to Dense Forest 355.1875 3.5519 Water body to Degraded Forest 286.0625 2.8606 No change 10656.5000 106.5650 16330.4375 163.3044
In most of the islands, dense forest seems to have grown, thanks to the sustained efforts of forest plantation. The reduction of forest area is mainly due to two reasons , erosion and submergence and secondly the conversion to saline blanks / salt pans. While erosion /inundation has a dominant impact in forest loss in southern islands like Dalhousi, Bulchery, Bhangaduani,Dhulibasani, Jambudwip even Dhanchi, conversion to saline blank is more pronounced in Herobhanga,Lothian, matla sajnekhali, Sudhanyakhali etc along with the southern islandsIn most cases, supratidal marshes or previously degraded forests are more vulnerable candidates for this natural conversion . The higher level tidal inundation due to rising sea and storm surges can be
- 125 - the probable drivers for water logging, evaporation and salt deposition in these baled patches within the core of the forest areas. Thus global warming and climate change, along with rise in sea level and cyclone intensities are observed to have serious impact on the health of the mangrove forest by forcing natural reduction in the forest cover. The increase is water area within the island points to a slow gradual invasion of the sea.
- 126 - LIST OF REFERENCES
Papers & Reports 1. Census Report. 1991. 24 Paraganas, Part XII-B.
2. Census of India 2001, Series-20, Provisional Population Totals of West Bengal.
3. Hazra, S., Ghosh,T., Dasgupta, R.,& Sen, G., 2002. Sea Level and associated changes in the Sundarbans. J. Science and Culture. Vol. 68, No.-9-12, pp.309- 321.
4. Hazra S.,Dasgupta R., Samanta K., Sen S. 2004. A Preparatory Assessment of Vulnerability of the Ecologically Sensitive Sundarban Island System, West Bengal, in the Perspective of Climate Change :in Gossain et al(Ed.) Proc. ‘Vulnerability Assessment And Adaptation Due To Climate Change On Indian Water Resources, Coastal Zones And Human Health, IIT Delhi (India, NATCOM), pp 66-82
5. Sanyal, P., 2003.Study of Mangrove Ecosystem of Sundarbans &Sustainable use of its resources; Unpublished Ph.D Thesis, Jadavpur University.
URL 1. www.wikipedia.org
2. http://www.sandwatch.ca/New%20Sandwatch%20Manual/Chapter%205%20Erosi on%20and%20Accretion.pdf
3. www.deduce.eu.pdf
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