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Determination of Land Cover Changes and Suitable Shrimp
Farming Area Using Remote Sensing and GIS in
Southwestern Bangladesh
Md. Monirul Islam1*, Md. Kawser Ahmed2, Md. Abdus Shahid3, Sirajul Hoque4and
Dilshad Islam5
1Department of Fisheries, University of Dhaka, Dhaka-1000, Bangladesh,
E-mail: monir7369@yahoo.com , *Corresponding Author
2Department of Fisheries, University of Dhaka, Dhaka-1000, Bangladesh,
E-mail: kawser_du@yahoo.com
3Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon,
Dhaka, Bangladesh, E-mail: shahid_rajib2003@yahoo.com
4Department of Soil, Water and Environment, University of Dhaka, Dhaka-1000, Bangladesh,
E-mail: sirajswedu@yahoo.com
2Department of Fisheries, University of Dhaka, Dhaka-1000, Bangladesh,
E-mail: dilshadislam_du@yahoo.com
ABSTRACT
The present study was conducted to identify and quantify suitable sites for shrimp farming at
Debhata upazila of Satkhira district, Bangladesh, using remote sensing technique and GIS.
The spatial and temporal changes of land cover were determined using Landsat images of
1977, 1990, 2000 and 2004. The Landsat TM data and secondary data that included land
elevation, crop intensity, land capability association and soil salinity along with primary data of
water and soil characteristics such as pH, dissolved oxygen, salinity, phosphorus, potassium,
tidal fluctuation and soil texture were used to produce a shrimp farming suitability map. The
map was also verified by integrating with different facilities such as sources of water, sources
of shrimp post larvae, roads, ice factories, shrimp markets, shrimp processing plants and
NGOs. Shrimp farming areas were gradually increased while cropland areas were gradually
decreased that reveals an unplanned horizontal expansion of shrimp farms. The shrimp
farming suitability map indicates that out of 17362 ha available land, 5756.82 ha (33.14 %),
2336.02 ha (13.45 %), 3089.42 ha (17.78 %) and 6188.34 ha (35.62 %) were under very
suitable, suitable, moderately suitable and unsuitable categories, respectively. The study
suggests that shrimp farming should be confined within the very suitable areas to avoid
horizontal expansion of shrimp farming without any environmental and social consequences.
The present study has demonstrated the usefulness of remote sensing technique and GIS to
select suitable sites and as a tool for planners to develop strategic plans for sustainable
aquaculture development.
KEY WORDS: Remote sensing, GIS, land cover, shrimp farming
Mathematics Subject Classification: 54C99
JEL Classification: Q22, Q25.
INTRODUCTION
Site selection for aquaculture is essential, as it can greatly influence economic viability. The main
problem for proper planning and sustainable development of coastal fisheries in Bangladesh is the
lack of baseline information about the physiographic environment that makes it difficult to assess
resources and start efficient management. The conventional methods to collect this information are
time consuming and need a lot of manpower. On the other hand, it is very difficult to visit the coastal
International Journal of Ecology & Development
Winter 2009; Vol. 12, No. W09 ; Int. J. Ecol. Dev.; 28-41
ISSN 0972-9984 ( Print ); ISSN 0973-7308 (Online)
Copyright © 2009 IJED, ISDER
areas and error may crop up due to variation of efficiencies of different field survey teams. Therefore,
there is a need for an approach that can be used to rapidly identify the coastal area of Bangladesh
suitable for various kinds of aquaculture as an aid to development planning.
Remote Sensing data have been proven useful in assessing the natural resources and in monitoring
the changes (Ratanasermpong et al., 1995). Remote Sensing technique is also a useful source of
information as it provides timely and complete coverage of the study area, complementing field
surveys of higher information content (Satyanarayana et al., 2001). GIS that can be considered as a
database management system has an important role in planning process where land use changes as
well as the existing pattern are intensive (Salam and Ross, 1999; Burrough, 1986). By using remote
sensing technique and GIS, the advantage is not only in time and cost effectiveness but also in
achieving a more comprehensive and integrated treatment of aquaculture development criteria, which
is difficult through conventional techniques alone (Kapetsky et al., 1987). A GIS, however, is not
automated decision making system but a tool to query, analyze and produce map in support of the
decision making process (Burrough, 1993). Satellite remote sensing technique is being used as a tool
to know location, extent and spatial and temporal changes of coastal fisheries, especially coastal
shrimp farming areas (Populas and Lantieri, 1991).
Shrimps are being traditionally cultured along the coast of Bangladesh for a long time. But now a
days, shrimp farming areas in Bangladesh have been increasing rapidly due to steadily rising demand
of shrimp in international markets and higher economic returns of shrimp culture compared to other
activities such as rice and salt (Shahid and Islam, 2003). However, the expansion of shrimp culture
has caused ecological and environmental concerns in most places. Therefore, careful planning is
necessary to develop an environment friendly integrated coastal aquaculture program as a
sustainable technique. So that, coastal aquaculture would develop as a good source of animal protein
for the growing population, a foreign currency earner as well as maintainer of ecological balances in
the brackish-water region. An attempt was, therefore, made to use remote sensing and GIS to identify
suitable areas for shrimp farm development at Debhata upazila, Satkhira, Bangladesh (Figure 1).
MATERIALS AND METHODS
Data Used
Three Landsat TM images of 14 Nov. 1990, 17 Nov. 2000 and 29 Nov. 2004 and one Landsat MSS
image of 09 Feb. 1977 were used to determine the land cover changes. Different types of thematic
information on the study area such as land elevation, crop intensity, land capability association and
soil salinity were collected from Soil Resources Development Institute (SRDI, 1993).
During the study period (2004-2005) different primary data such as salinity/ electrical conductivity, pH,
nitrate, phosphorus and potassium of both soil and water and texture of soil were derived from
laboratory analysis of soil and water samples, while dissolved oxygen of water was measured directly
in the field and the data on tidal fluctuation were collected from field survey. Soil and water samples
were collected from seven stations of Debhata upazila, each for three times (19 November 2004, 25
January 2005 and 20 May 2005).
Geographical positions of the sampling stations were taken in the field by GPS (etrex Legend,
GERMIN). Particle size of soil was analysed using hydrometer method as described by Day (1965).
Textural classes of soil were determined by Marshall’s Triangular co-ordinates as devised by the US,
Department of Agriculture (USDA, 1951). Electrical conductivity of the saturation extract of soil and
water were determined by using conductivity meter (Conmet 1). pH of water and soil sample (soil to
water ratio of 1:2.5) were determined with the help of a glass electrode pH meter (Jenway 3305).
Int. J. Ecol. Dev.; Vol. 12, No. W09, Winter 2009 29
Digital dissolved oxygen meter (HANNA: HI 9142) was used to determine the concentration of
dissolved oxygen. Point five mole K2SO4extractable nitrate was determined colorimetrically using
spectrophotometer (Jenway 6100, UK). Olsen method (0.5M NaHCO3at pH 8.5) was used for
extraction of soil phosphorus and the phosphorus contents of both water and extracted soil samples
were determined by ascorbic acid blue colour method (Murphy and Riley, 1962). Ammonium acetate
(pH 7.0) extractable soil potassium as well as potassium content of water was determined flame
photometrically.
Number and locations of different facilities in the study area such as sources of shrimp post larvae
(PL), shrimp processing plants, shrimp markets, ice factories, and NGOs which involved with shrimp
farming were collected by field survey. Sources of water (rivers and canals) for shrimp farming and
roads were digitized from SRDI map and updated from Landsat TM image of 2004.
Software Used
Two software’s were principally used: 1). ERDAS Imagine digital image processing software
integrated with the additional vector module and 2). Arc/Info GIS for the GIS related part.
Processing of Remote Sensing Data
Digital data of Landast MSS (1977) and Landsat TM (1990, 2000 and 2004) were pre-processed to
remove data errors and anomalies. After georeferencing both supervised and unsupervised methods
of classification were employed. Five broad land cover classes were assigned each of the 4 images in
the time series: settlement, river water, cropland area, shrimp farm and fallow water bodies. These
classes were finally edited on the computer screen to eliminate small errors. Extensive GPS (etrex
Legend, GERMIN) based field works were carried out over the study sites in support of the satellite-
derived information for their correction and validation (Figure 2).
GIS Analysis
For the preparation of shrimp farming suitability map eighteen vector databases were produced and
combined in GIS environment (Figure 2). Throughout this study, classification scheme was carried
out according to Kapetsky and Nath, 1997. Four levels of suitability class were used in order to keep
the analyses manageable and to make the results more easily comprehensible and comparable. The
levels were very suitable (VS), suitable (S), moderately suitable (MS) and unsuitable (US).
The databases for land elevation, crop intensity, land capability association, soil salinity and land
cover were produced by digitization. The polygon layer of each of the databases contained four
suitability classes (Table 1).
The databases for soil and water characteristics were produced using terrain surface interpolation
technique of ERDAS Imagine. The polygon layer of each of the database contained four suitability
classes (Table 2).
Thresholds pertaining to a desired level of suitability for each criterion of Table 2 were selected
according to BAFRU, 1990; Boyd and Clay, 2002; Davis et al., 2004; Kungvankij et al., 1985; Salam
and Ross, 2000; ASEAN Cooperation in Food, Agriculture and Forestry, 1996; Kontara, 1988;
Chakraborti et al., 1985; Das, 1998; Boyd, 1995 and Kungvankij and Chua, 1986.
Integration of Different Facilities with Suitability Map
Based on the suitability score (Table 3) for each facility, buffer area was made on suitability map
using ‘point buffer’ and ‘line buffer’ command of Arc/Info. All the buffered vector layers were then
overlaid on the suitability map.
30 International Journal of Ecolo
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RESULTS AND DISCUSSION
The land cover classes of different years were extracted by digital classification of the processed
satellite images. The classified satellite images are shown in Figure 3 and the areas of land cover
classes in 1977, 1990, 2000 and 2004 are summarized in Table- 4.
The extent of cropland area decreased drastically between 1977 and 2004 mainly due to the rapid
expansion of shrimp farm (the dominant land cover category) and gradual increase of settlement
area. In the lowland, fallow water bodies of 1099.96 ha (6.33%) was present in 1977 but fully
converted to shrimp farms by 1990 (Table 4 and Figure 3). Shrimp farming area has been rapidly
increased in the saline and semi saline tidal river system of Bangladesh during the last decade
(Shahid, et al., 1992).
This horizontal expansion of shrimp farming area in the cropland is causing irreversible damage to the
environment. Most important matter of concern is increase of soil salinity due to salt water seepage.
Moreover, shrimp farming from January to September has been hampering rice cultivation. Shahid
and Islam (2003) stated the delay of transplantation and lower production of rice. There has also been
a significant reduction of livestock and poultry in the shrimp farming areas ( Rahman et al., 1995). It is
therefore, urgently necessary to select suitable area for shrimp farming to reduce horizontal
expansion in order to ensure sustainable resource management.
Shrimp Farming Suitability Map
The shrimp farming suitability map was produced by combining the databases of soil characteristics,
water characteristics and thematic and satellite data. The databases of soil and water characteristics
were developed from average value of the particular characteristics. The average value and range of
three seasons (November, January and May) of different soil and water characteristics are given in
table 5 (a and b) and 6(a and b).
Table 5 and 6 shows that average salinity of both soil and water was higher at stations 1 and 7. Soil
salinity of different sampling stations was lower in November (1.8-5 ppt), medium in January (2.11-8
ppt) and higher in May (11.14-16.89 ppt). Water salinity also showed mostly similar seasonal trend.
Average pH was slightly alkaline. However, water pH was slightly acidic at station 1 (6.42) and station
2 (6.80) during May. Average soil nitrate, phosphorus and potassium were much higher than those of
water. Again, the concentration of nitrate in water was nil at stations 1, 2, and 4 during November.
Two types of soil; silty clay and silty clay loam were found. Dissolved oxygen concentration of water at
seven sampling stations ranged from 6.25 to 8.60 mg/litre and 6.50 to 8.36 mg/litre in January and
May, respectively, while average concentration ranged from 6.37 to 8.48 mg/litre. Average tidal
fluctuation was higher for station 3 and 7 (2 m and 1.75 m respectively), while it was medium (0.75 m)
for station 2 and 6 and lower (0.35 m) for station 1, 4 and 5. The value ranges of different
characteristics show some of the lower concentrations but those would not create any problem as
those values were found during November –the off-culture period of shrimp.
The shrimp farming suitability map is shown in Figure 4. Table- 7 summarizes the area of different
suitability classes and their percentage of total study area. The suitability classes of Figure 4 and
Table 7 can be explained in each category as follows:
Very suitable
All the low land (except rivers), some medium land in the middle and eastern side and a small area in
the northwestern part fell under this category. This class covered 5756.82 ha (33.14 %) of the total
area. Elevation was low and medium, crop intensity was fallow to single crop, land capability
Int. J. Ecol. Dev.; Vol. 12, No. W09, Winter 2009 31
association was poor agricultural land and soil salinity was good for shrimp culture. All the soil and
water characteristics were under well acceptable range. Shrimp farming should be restricted to this
very suitable area.
Suitable
Of the total area, 2336.02 ha (13.45 %) were under this category. Most of the areas were medium
land and found scatteredly in the entire area. These areas had well acceptable water pH, dissolved
oxygen, nitrate, and tidal fluctuation but low concentration of water salinity, phosphorus and
potassium. These areas also had well acceptable soil pH, nitrate and texture but good concentration
of soil phosphorus was found in some of these areas. However, soil salinity and potassium were not
in well acceptable range in most of these areas. In these areas shrimp farming can be possible if the
lacking parameters are fulfilled.
Moderately Suitable
This class includes 3089.42 ha (17.78 %), of the total area. Some of the areas were high land and
some were low and found in the middle and western part. Most of the areas of this class had low
water salinity, phosphorus and potassium but had good water pH, dissolved oxygen, nitrate and tidal
fluctuation. Most of these areas also had low soil salinity, phosphorus and potassium although soil
pH, nitrate and texture were good. Significant interventions may be required before shrimp farming
operations can be carried out in these lands.
Unsuitable
This class covers the largest area of 6188.34 ha (35.62 %) of the total area. These areas were found
in the middle and western part and included settlement and river but most of the areas of
southwestern part were under this class. Crop intensity was double to triple and single to double
crop, land capability association was good and moderate agricultural land. Water and soil
characteristics of the unsuitable areas were same as those of moderately suitable areas except that
tidal fluctuation was very low in some areas. Therefore, this area is not suitable for shrimp farming
because the time or cost, or both, are too great to be worthwhile for shrimp farming.
The different classes of the shrimp farming suitability map were verified by the integration of buffer
area produced from location of different facilities. It was found that almost all the very suitable areas
were within <2km buffer zone of river and roads. This means very suitable area has very good water
source and communication system. For other facilities such as sources of shrimp post larvae (PL),
shrimp processing plants, shrimp markets, ice factories, and NGOs, nearly all the very suitable areas
were covered when 5-10km buffer area was considered. However, as the communication facilities are
good in the study area, it would be possible to supply shrimp PL and ice easily. Farmers will be able
to carry shrimp to markets and processing plants within short period and NGO workers will be able to
contact easily to farmers.
The suitability map also reveals that almost all of the moderately suitable and half of the suitable
areas are present in the middle and western part of the study area. Classified Landsat TM image of
2004 (Figure 3) shows that much of these areas are already under shrimp cultivation. It is interesting
to note that some portion of unsuitable class of land is already under shrimp cultivation. In these
currently operated shrimp farming land, shrimp is cultured from January to July and at the start of
rainy season when soil salinity reduced to nearly zero, then paddy is cultivated together with some
freshwater fish and prawn. Rahman et al. (1995) found the similar result.
32 International Journal of Ecolo
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There are some advantages and disadvantages of culture of shrimp and paddy in the same field;
although in terms of sustainable aquaculture development, disadvantages are greater than
advantages. The most important advantage is that farmer gets one extra crop of paddy which in many
cases helps to compensate the sudden loss due to diseases or natural disaster. Islam et al. (2005)
found similar result.
Among the disadvantages, salinization of soil is the most important matter of concern. From Table 5 it
is found that during November (when no shrimps are cultured) in the western side of the study area,
soil salinity at stations 2 and 4 (where shrimps as well as paddy are cultured in the same land) is
higher than water salinity. Saline water remains on the land for five to seven months and this
increases the total quantity of salt percolating into ground during one season. Consequently, the salt
remains after the shrimp culture period not wash out by rain completely and the concentration of salt
in this land has been increasing day by day. Shahid et al.. (1992) found the similar results. He also
added that increased salt load replaces nutrients valuable for crop growth.
Several factors affected the various outcomes of this study. These include factors that may have been
derived from inaccurate data sources, their spatial and temporal variability and the analytic
approaches and assumptions adopted here. Nonetheless, the rapidly expanding access to digital
datasets at low cost and in some cases free through the web, the rapid development of more powerful
hardware and affordable software continues. These simple but extremely powerful tools are
invaluable for solving many real-world problems of planning applications, and providing information for
decision-making. Most of the possible problems affecting this study will be minimized or eliminated as
more data become available and experience is gained with aquaculture related GIS application.
CONCLUSION
Remote sensing analysis of shrimp farming using Landsat data over a period of twenty seven years
(1977-2004) and GIS modelling revealed an uncontrolled and unplanned growth of shrimp farms in
the study area. Shrimp farming operation should be confined within very suitable area for sustainable
aquaculture development. In suitable areas shrimp farming can be possible if the lacking parameters
can be fulfilled. The moderately suitable areas will require significant interventions before shrimp
farming operations can be carried out. Therefore, moderately suitable along with unsuitable area is
not currently suitable for shrimp farming. The results of this study are also indicative of the usefulness
of remote sensing and modelling power of GIS and could be used to refine the models in future,
particularly if supported by further updated and accurate input data.
ACKNOWLEDGEMENTS
The authors are grateful to Bangladesh Space Research and Remote Sensing Organization
(SPARRSO), Dhaka and Department of Soil, Water and Environment, University of Dhaka for giving
permission to use the laboratory facilities and their kind cooperation during the course of the present
study.
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TABLES
Table-1. Scores and suitability classes for the databases of thematic information and satellite data
(modified after Shahid et al., 1997).
Suitability
classes Very Suitable Suitable Moderately Suitable Unsuitable
Databases
Crop intensity Fallow-single
crop Single-double crop Double-triple crop Triple crop &
settlement
Land capability
association
Poor
agricultural
land
Moderate
agricultural land
Moderate to good
agricultural land
Good agricultural
land
Land Cover Shrimp farm Crop land Crop land Settlement and
river
Land Elevation Low Low-medium Medium High
Soil salinity Saline Moderately saline Slightly saline Non saline
Int. J. Ecol. Dev.; Vol. 12, No. W09, Winter 2009 35
Table-2. Scores and suitability classes for the databases of water and soil characteristics which are
taken from different published literatures.
Suitability
classes Very Suitable Suitable Moderately Suitable Unsuitable
Databases for water characteristics
Salinity (ppt) 10-25 5-9, 25-32 4 -5, 32-35 4!35
pH 6.9-9 5.5-6.9 4.5-5.5
4.5, !9
Dissolved
oxygen (ppm) 4-9 3-4, 9-12 3-3.5, 12-13 3, !13
Nitrate (mg/l) <50 50-60 60-70 >70
Phosphorus
(mg/l) 0.2-0.5 0.1-0.2, 0.5-1 0.05-0.1, 1-1.5 0-0.05, >1.5
Potassium
(mg/l) 110-214 80-109, 215-300 50-80, 300-350 50 !350
Tidal fluctuation
(m) 1-2 0.5-1, 2-4 0.35-0.5, 4-5 0.35, >5
Databases for soil Characteristics
Salinity (ppt) 8-26 5-8, 26-32 4-5, 32-37 <4 >37
pH 6.5-8.5 5.5-6.5, 8.5-8.8 4.5-5.5, 8.8-9
4.5 !9
Nitrate (mg/l) 0-200 200-250 250-300 >300
Phosphorus
(mg/l) 13-120 10-13,120-150 8-10, 150-200 8!200
Potassium
(mg/l) 400-1200 300-400, 1200-
1300 200-300, 1300-1400 200 !1400
Texture silty clay, sandy
clay, silty clay loam silt loam sandy clay loam
sandy loam,
loamy sand,
sand
Table-3. Scores and suitability classes for the databases of different facilities (according to Aguilar-
Manjarrez, 1996; Hoque et al., 1997 and Salam and Ross, 2000).
Suitability classes Very Suitable Suitable Moderately Suitable Unsuitable
Distance to Different Facilities (km)
Water Sources (River) 11-2 2-4 !4
Sources of Post Larvae 33-7 7-12 !12
Roads 22-3 3-5 !5
Processing Plants 33-5 5-10 5-10
Ice Factories 11-3 3-5 !5
Markets 11-3 3-5 !5
NGOs 55-10 10-12 !12
Table-4. Area and percentage of land cover classes for the study area in different years showing the
continuous increase of shrimp farms.
1977 1990 2000 2004
Land cover
categories Area (ha) %Area (ha) %Area (ha) %Area (ha) %
Settlement 2227.33 12.8 2714.05 15.6 2921.06 16.8 3016.23 17.4
Cropland
area 13349.08 76.9 5663.69 32.6 3517.52 20.3 3179.70 18.3
Fallow water
bodies 1099.96 6.3 0.00 0.00 0.00 0.00 0.00 0.00
River water 685.96 3.9 632.15 3.6 770.37 4.4 668.88 3.9
Shrimp farm 0.00 0.00 8381.89 48.3 10178.16 58.6 10522.81 60.6
36 International Journal of Ecolo
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Table-5a. Average and Value range of different soil characteristics (salinity, pH and nitrate) collected
from seven sampling stations during three seasons of study period.
Salinity
(ppt) pH Nitrate
(ppm)
Stations
Range Average Range Average Range Average
1 4.09-16.89 9.21 7.49-8.40 7.99 25-100 61.66
2 3.33-11.14 6.04 7.75-8.32 8.01 0-120 58.33
3 1.26-12.42 5.26 7.13-8.26 7.69 0-90 50.00
4 1.8-9.92 5.55 7.71-8.26 7.94 0-70 36.66
5 2-15.14 7.69 7.50-8.02 7.76 1.66-100 57.22
6 2.95-14.53 7.27 7.39-8.02 7.71 5-100 58.33
7 5-16 9.66 7.50-8.22 7.79 20-140 76.66
Table-5b. Average and Value range of different soil characteristics (phosphorus, potassium and
texture class) collected from seven sampling stations during three seasons of study period.
Phosphorus
(ppm)
Potassium
(ppm)
Stations
Range Average Range Average
Soil texture
class
1 1.5-19 10.16 285-660 456.66 Silty clay loam
2 7.5-16 12.50 305-780 495.00 Silty clay
3 19-26 22.00 195-380 275.00 Silty clay
4 7.5-16 10.50 175-840 455.00 Silty clay
5 19-46 28.16 375-1160 740.83 Silty clay loam
6 8.5-17 12.00 205-1040 623.33 Silty clay
7 3.5-26 15.83 265-1340 745.66 Silty clay
Table-6a. Value range of different water characteristics (salinity, pH, nitrate, and phosphorus)
collected from seven sampling stations during three seasons of study period.
Salinity (ppt) pH Nitrate (ppm) Phosphorus (ppm)
Stat
ions Range Average Range Average Range Average Range Average
1 3.87-18.18 9.85 6.42-7.49 7.10 0-7 4.66 0.037-0.15 0.09
2 2.78-16.45 7.36 6.80-7.63 7.34 0-10.5 5.83 0.10-0.47 0.23
3 0.63-21.44 8.08 7.58-7.73 7.64 0.30-5 3.26 0.05-0.16 0.12
4 1.07-14.05 6.44 7.61-7.97 7.78 0-10 4.66 0.012-0.15 0.07
5 1.29-14.40 6.10 7.27-8.35 7.81 0.30-10 4.10 0.012-0.15 0.07
6 2.41-13.41 6.72 7.27-8.30 7.69 3.50-22 10.83 0.10-0.49 0.23
7 4.50-18.40 10.43 7.55-8.26 7.80 2-9 6.00 0.05-0.10 0.07
Table-6b. Value range of different water characteristics (potassium, dissolved oxygen and tidal
fluctuation) collected from seven sampling stations during three seasons of study period.
Potassium (ppm) Dissolved Oxygen (ppm) Tidal fluctuation (m)
Stations Range Average Range Average Range Average
1 56-175 119.00 6.75-8.25 7.50 0.30-0.40 0.35
2 38-172.5 91.50 7.34-8.27 7.80 0.65-0.85 0.75
3 7.9-220 90.63 8.36-8.60 8.48 1.75-2.25 2.00
4 21-140 81.66 7.20-8.00 7.60 0.30-0.40 0.35
5 29-130 73.00 7.80-8.50 8.15 0.30-0.40 0.35
6 39-105 75.33 6.25-6.50 6.37 0.65-0.90 0.75
7 57-175 123.33 7.20-8.47 7.83 1.65-1.85 1.75
Int. J. Ecol. Dev.; Vol. 12, No. W09, Winter 2009 37
Table-7. Area of different shrimp farming suitability classes and their percentage of total study area,
calculated from Figure 4.
Suitability
classes Area (ha) % of the total
study area
Very suitable 5756.82 33.14
Suitable 2336.02 13.45
Moderately suitable 3089.42 17.78
Unsuitable 6188.34 35.62
FIGURES
Figure 1. Location map of the study area in Bangladesh.
38 International Journal of Ecolo
gy
& Development
Figure 2. Schematic flowchart of methodology showing how different layers have been
integrated to produce shrimp farming suitability map.
Int. J. Ecol. Dev.; Vol. 12, No. W09, Winter 2009 39
Figure 3. Classified Landsat images showing changes of land cover (a) 1977, (b) 1990, (c) 2000
and (d) 2004.
40 International Journal of Ecolo
gy
& Development
Figure 4. Shrimp farming suitability map of Debhata upazila based on thematic information,
satellite data, and soil and water characteristics.
Int. J. Ecol. Dev.; Vol. 12, No. W09, Winter 2009 41
