Changes And Urban Expansion In Greater Dhaka Environmental Sciences Essay

This survey evaluates old termland usage alterations and urban enlargement in Greater Dhaka, Bangladesh, between 1975 and 2003 utilizing satellite images and socio-economic informations. Spatial and temporal kineticss of old termlandnext term use/cover old termchangesnext term were quantified utilizing three Landsat images, a supervised categorization algorithm and the post-classification old termchangenext term sensing technique in GIS. Accuracy of the Landsat-derived old termlandnext term use/cover maps ranged from 85 to 90 % . The analysis revealed that significant growing of built-up countries in Greater Dhaka over the survey period resulted important lessening in the country of H2O organic structures, cultivated old termland, following term flora and wetlands. old termUrban land expansionnext term has been mostly driven by lift, population growing and economic development. Rapid old termurban expansionnext term through infilling of low-lying countries and glade of flora resulted in a broad scope of environmental impacts, including habitat quality. As dependable and current informations are missing for Bangladesh, the old termlandnext term usage maps produced in this survey will lend to both the development of sustainable old termurban landnext term usage planning determinations and besides for calculating possible hereafter old termchangesnext term in growing forms. Urbanization is one the most widespread anthropogenetic causes of the loss of cultivable old termlandnext term ( Lopez, Bocco, Mendoza, & A ; Duhau, 2001 ) , habitat devastation ( Alphan, 2003 ) , and the diminution in natural flora screen. The transition of rural countries into old termurbannext term countries through development is presently happening at an unprecedented rate in recent human history and is holding a pronounced consequence on the natural operation of ecosystems ( Turner, 1994 ) . Although old termurbannext term countries presently cover merely 3 % of the Earth ‘s old termlandnext term surface, they have marked effects on environmental conditions at both local and planetary graduated tables ( [ Herold etA al. , 2003 ] and [ Liu and Lathrop, 2002 ] ) , including clime old termchangenext term ( Grimm, Grove, Pickett, & A ; Redman, 2000 ) . Since ecosystems in old termurbannext term countries are strongly influenced by anthropogenetic activities, well more attendi ng is presently being directed towards supervising old termchangesnext term in old termurban landnext term usage and old termlandnext term screen ( LULC ) ( Stow & A ; Chen, 2002 ) . Such surveies are peculiarly of import because the spacial features of LULC are utile for understanding the assorted impacts of human activity on the overall ecological status of the old termurbannext term environment ( Yeh & A ; Li, 1999 ) . LULC old termchangenext term due to human activities is presently continuing more rapidly in developing states than in the developed universe, and it has been projected that by the twelvemonth 2020, most of the universe ‘s mega metropoliss will be in developing states ( World Bank, 2007 ) . Increasing population in developing metropoliss has caused rapid old termchangesnext term in LULC and increased environmental debasement ( Holdgate, 1993 ) . The consequence of population is peculiarly relevant given that the planetary old termurbannext term population is projected to about duplicate by 2050 ( UN, 2008 ) . In order to extenuate the damaging effects associated with old termurbannext term growing on the environment and to keep optimum ecosystem operation ( Fang, Gertner, Sun, & A ; Anderson, 2005 ) , spacial and temporal LULC forms, and the factors impacting these old termchangesnext term ( Serra, Pons, & A ; Sauri , 2008 ) , are well of import in developing rational economic, societal and environmental policies ( Long, Tang, Li, & A ; Heilig, 2007 ) . Bangladesh has experienced rapid old termurbannext term population growing in recent decennaries ; the population numbered 14.1 million in 1981, 22.5 million in 1991, 31.1 million in 2001 ( BBS, 2001 ) and 35 million in 2005 ( CUS, NIPORT, & A ; MEASURE, 2006 ) . Rapid urbanisation has led to the transmutation of rural countries into developed countries, and it has been estimated that more than 809A km2 of agricultural old termlandnext term is converted to metropoliss, roads and substructure yearly ( BBS, 1996 ) . The lessening in agricultural activities, the largest sector of the Bangladeshi economic system, and the attendant loss of cultivated old termlandnext term is likely to lend to landlessness, nutrient deficits and endanger the economic system ( Ahmad, 2005 ) . Dhaka, the capital of Bangladesh, is expected to be the 3rd largest metropolis in the universe by 2020 ( World Bank, 2007 ) and the rapid old termurbannext term growing experienced by the metropolis in recent decennaries is one of the highest in the universe ( [ Islam, 1999 ] and [ Islam, 2005 ] ) . old termUrban expansionnext term of Dhaka was slow in the 1950s, but strong growing followed the independency of Bangladesh in 1971 ( Chowdhury & A ; Faruqui, 1989 ) . The considerable growing observed in the population of Dhaka is thought to hold occurred in response to large-scale rural-previous termurbannext term migration, which has contributed, significantly to the increased rate of urbanisation ( Islam, 1996 ) . To day of the month, the environmental and socio-economic sustainability of Dhaka, which is indispensable for development planning, has received comparatively small attending. This has resulted in widespread environmental jobs across the metropolis, mostly stemming from unpl anned urbanisation, extensive old termurbannext term poorness, perennial episodes of implosion therapy, significant growing of slums, development of resources, and the misdirection of limited old termlandnext term resources ( Hasan & A ; Mulamoottil, 1994 ) . Geographic Information Systems ( GIS ) and distant detection ( RS ) are powerful and cost-efficient tools for measuring the spacial and temporal kineticss of LULC ( [ Hathout, 2002 ] , [ Herold etA al. , 2003 ] , [ Lambin etA al. , 2003 ] and [ Serra etA al. , 2008 ] ) . Distant feeling informations provide valuable multi-temporal informations on the procedures and forms of LULC old termchange, following term and GIS is utile for function and analysing these forms ( Zhang etA al. , 2002 ) . In add-on, retrospective and consistent synoptic coverage from orbiters is peculiarly utile in countries where old termchangesnext term have been rapid ( Blodget, Taylor, & A ; Roark, 1991 ) . Furthermore, since digital archives of remotely sensed informations provide the chance to analyze historical LULC old termchanges, following term the geographic form of such old termchangesnext term in relation to other environmental and human factors can be evaluated. Numerous old termchangenext term sensing methods have been developed to measure fluctuations in LULC utilizing satellite informations ( [ Coppin etA al. , 2004 ] , [ Lu etA al. , 2004 ] and [ Singh, 1989 ] ) . Of these techniques, the pre- and post-classification comparings have been extensively used ( [ Coppin etA al. , 2004 ] and [ Singh, 1989 ] ) . In the pre-classification attack, processs such as image differencing ( Toll, Royal, & A ; Davis, 1980 ) , band rationing ( Nelson, 1983 ) , old termchangenext term vector analysis ( Johnson & A ; Kasischke, 1998 ) , direct multi-date categorization ( Li & A ; Yeh, 1998 ) , flora index differencing ( Townshend & A ; Justice, 1995 ) and principle constituent analysis ( Fung & A ; LeDrew, 1987 ; Hartter, Lucas, Gaughan, & A ; Aranda, 2008 ) have been developed ( [ Hardin etA al. , 2007 ] , [ Jensen, 1996 ] and [ Singh, 1989 ] ) . The basic premiss of these processs is that old termchangesnext term in LULC consequence in differences in the pel coefficient of reflection values between the day of the months of involvement. However, while these techniques are effectual for turn uping old termchange, following term they can non place the nature of old termchangenext term ( Ridd & A ; Liu, 1998 ) . Conversely, post-classification comparings examine old termchangesnext term over clip between independently classified old termlandnext term screen informations. Despite the troubles associated with post-classification comparings ( [ Coppin etA al. , 2004 ] and [ Singh, 1989 ] ) , this technique is the most widely used for placing LULC old termchangesnext term ( [ Jensen, 1996 ] and [ Lu etA al. , 2004 ] ) , peculiarly in old termurbannext term environments ( Hardin etA al. , 2007 ) . However, one of the disadvantages associated with this attack is that the truth of the end point LULC old termchangenext term maps depends on the truth of the single categorization, intending that such techniques are capable to error extension ( Y uan, Sawaya, Loeffelholz, & A ; Bauer, 2005 ) . However, such post-classification techniques are peculiarly utile for bring forthing ‘from-to ‘ maps ( Jensen, 1996 ) , which can be used to clear up the magnitude, location and nature of the old termchangesnext term shown ( Howarth & A ; Wickware, 1981 ) . In add-on, the technique can be employed utilizing informations acquired from detectors with different spatial, temporal and spectral declarations ( [ Alphan, 2003 ] and [ Coppin etA al. , 2004 ] ) . RS is really effectual for exemplifying the interactions between people and the old termurbannext term environments in which they live ( Gatrell & A ; Jensen, 2008 ) . Space-borne orbiter informations are peculiarly utile for developing states due to the cost and clip associated with traditional study methods ( Dong, Forster, & A ; Ticehurst, 1997 ) , and these techniques have become feasible options to conventional study and ground-based old termurbannext term mapping methods ( Jensen, Hodgson, Tullis, & A ; Raber, 2004 ) . Several surveies have demonstrated the pertinence of RS to developing sourcing information and for back uping decision-making activities in a broad scope of old termurbannext term applications ( [ Gatrell and Jensen, 2008 ] , [ Jensen and Cowen, 1999 ] and [ Zeilhofer and Topanotti, 2008 ] ) . In the country of old termurbannext term planning, of import RS research has been conducted to day of the month, peculiarly in old termurban changenext term analysis and th e mold of growing ( [ Bahr, 2004 ] , [ Hardin etA al. , 2007 ] , [ Hathout, 2002 ] , [ Herold etA al. , 2003 ] , [ Jat etA al. , 2008 ] , [ Jensen and Im, 2007 ] , [ Liu and Lathrop, 2002 ] , [ Maktav and Erbek, 2005 ] , [ Ridd and Liu, 1998 ] , [ Yang, 2002 ] and [ Yuan, 2008 ] ) , LULC rating ( [ Alphan, 2003 ] , [ Lopez etA al. , 2001 ] , [ Xiao etA al. , 2006 ] , [ Yang and Lo, 2002 ] and [ Yuan etA al. , 2005 ] ) , and old termurbannext term heat-island research ( [ Kato and Yamaguchi, 2005 ] and [ Weng, 2001 ] ) . In peculiar, RS-based multi-temporal old termlandnext term use old termchangenext term informations provide information that can be used for measuring the structural fluctuation of LULC forms ( Liu, Gao, & A ; Yang, 2003 ) , which can be applied to avoiding irreversible and cumulative effects of old termurbannext term growing ( Yuan, 2008 ) and are of import to optimise the allotment of old termurbannext term services ( Barnsley & A ; Barr, 1996 ) . In add-on, accura te and comprehensive old termlandnext term use old termchangenext term statistics are utile for inventing sustainable old termurbannext term and environmental planning schemes ( [ Alphan, 2003 ] and [ Jensen and Im, 2007 ] ) . It is hence really of import to gauge the rate, form and type of LULC old termchangesnext term in order to foretell future old termchangesnext term in old termurbannext term development. Small is known about the spacial and temporal dimensions of the LULC old termchangesnext term that have shaped the old termurban expansionnext term of Greater Dhaka. Although most developed states have both recent and extended LULC information, the comparative deficiency of geospatial informations or entree thereto, is prevailing in developing states, peculiarly in Bangladesh. For case, aerial exposure are classified for the populace. The metropolis does non hold any official statistics on old termlandnext term usage forms, and the Master Plans do non incorporate either a map or quantitative information on the bing forms of old termlandnext term usage in the metropolis ( [ Islam, 1996 ] and [ Islam, 2005 ] ) . The old termlandnext term usage forms of Greater Dhaka were officially categorized in 1991 utilizing land observation informations ( Flood Action Plan ( FAP ) 8A, 1991 and [ Islam, 2005 ] ) . Due to the easiness of entree and recent nature of nose count records, the local autho ritiess of Dhaka often use nose count informations to construe old termlandnext term use old termchanges.next term As a consequence, the kineticss of development are non clear and frequently deceptive ( Talukder, 2008 ) . Numerous factors, including fiscal restraints, restricted entree to informations, bureaucratism and deficiency of geospatial expertness in the planning bureaus account for the absence of historical and current old termlandnext term usage informations. Furthermore, every bit many as 18 ministries are involved in the development and planning of Dhaka, and there is a general deficiency of coordination between these organic structures ( Mohit, 1991 ) . This empirical survey will try to place the spatio-temporal form of LULC old termchangesnext term for Greater Dhaka utilizing geospatial informations so that both the scientific community and determination shapers can measure the assorted kineticss impacting LULC old termchangesnext term in this old termurbannext term en vironment. The aims of this survey were therefore to research the features of LULC old termchangesnext term and qualify the underlying drive forces in the Greater Dhaka country by doing usage of remotely sensed informations and socio-economic information. Specifically, the aims are: ( a ) to clarify and measure the LULC old termchangesnext term between 1975 and 2003 ; ( B ) to research the spacial and temporal features of old termurban expansionnext term in this period ; and ( degree Celsius ) to analyse the drive forces of old termlandnext term use old termchange and urban expansion.next termStudy countryAs shown in Fig.A 1, the survey country of Greater Dhaka is located in the centre of Bangladesh between 23A °68aˆ?N ( BTM 533233.91A m ) , 90A °33aˆ? E ( BTM 619052.83A m ) and 23A °90aˆ?N ( BTM 550,952.57A m ) , 90A °50aˆ? E ( BTM 642511.56A m ) , severally. Topographically, the country is level with a surface lift runing from 1 to 14A m ( Fig.A 1 ) , with most old ter murbannext term countries located at lifts runing from 6 to 8A m ( FAP 8A, 1991 ) . The metropolis is situated chiefly on an alluvial patio, popularly known as the Modhupur patio dating from the Pleistocene period. The survey country is surrounded by four major river systems: the Buriganga, Turag, Tongi and the Balu, which flow to the South, west, north and east, severally. These rivers are chiefly fed by local rainfall and besides receive overflow from the well larger Ganges, Brahmaputra and Meghna rivers. The metropolis has a humid sub-tropical monsoon clime and receives about 2000A millimeters of rainfall yearly, more than 80 % of which falls during the monsoon season from June to September. Life-size image ( 137K ) – Opens new window Life-size image ( 137K ) Fig.A 1.A Location of survey country. River webs, embankment and administrative units are draped over a digital lift theoretical account. Brightest countries represent higher lift ; bright grey represents average lift while dark pels show the lowest lift.Position Within ArticleThe happening of heavy monsoon rainfall combined with floodwater overflow from the rivers environing the metropolis mean that Dhaka is really prone to monsoon implosion therapy. The metropolis has experienced a figure of lay waste toing inundations in recent times, with the inundations in 1988, 1998 and 2004 being the most terrible ( Alam & A ; Rabbani, 2007 ) . Quantitative appraisals of the countries inundated by these flood events revealed that in 1988, 47.1 % of greater Dhaka were flooded, while in 1998 and 2004, about 53 % and 43 % countries were inundated ( [ Dewan etA al. , 2007 ] , [ Dewan and Yamaguchi, 2008 ] and [ Dewan etA al. , 2006 ] ) . The inundations caused harm to lodging and substructure amou nting to US $ 2.2A m in 1988, 4.4A m in 1998 and 5.6A m in 2004 ( Ahmed, Gotoh, & A ; Hossain, 2006 ) . The badness of inundation harm was considerable, even in 2004, which was considered more moderate of the three inundations, and which was believed to be the consequence of hapless old termurbannext term planning and renewal and development of natural countries, such as wetlands and low-lying countries, that would otherwise hold attenuated the implosion therapy. A survey utilizing hydrological record and RS-based LULC information has shown that inundation continuance and extent has increased well as a consequence of the extended old termurbannext term development on Lowlandss and flood plains of natural river channels ( Dewan & A ; Yamaguchi, 2008 ) . It has been suggested that the exposure of Dhaka to deluge harm will increase due to continued unplanned old termurban expansionnext term ( Faisal, Kabir, & A ; Nishat, 1999 ) and the consequence of clime old termchangenext term ( Ala m & A ; Rabbani, 2007 ) , and that these in bend will increase the agony to the dwellers of Dhaka and do extended harm to belongings in the part.Data and methodological analysisData acquisition and readyingLandsat informations ( MSS, TM and ETM+ ) were acquired and used to measure LULC old termchanges and urban expansionnext term in Dhaka. Geometric rectification was performed on all the images utilizing a Landsat TM image of the same country from 1997 as mention. At least 45 land control points ( GCPs ) were used to register the images to the Bangladesh Transverse Mercator ( BTM ) system. GCPs were dispersed throughout the scene, giving a RMS mistake of less than 0.5 pels. A first order multinomial tantrum was applied and images were resampled to 30A m end product pels utilizing the nearest neighbour method. All brooding sets were used in image categorization and the thermic set was excluded. In add-on, geospatial informations including municipal boundaries, route webs, geomorphic units and lift units were used to bring forth GIS beds from beginnings such as Survey of Bangladesh ( SOB ) topographical maps ( sheet no. 79 I 5 & A ; 6 ) , municipal boundary map and geomorphic map ( Asaduzzaman, Nasreen, & A ; Olsen, 1999 ) . Multi-year socio-economic informations were obtained from Bangladesh Bureau of Statistics ( BBS ) and published literature ( [ Islam, 1996 ] , [ Islam, 2005 ] and [ Siddiqui etA al. , 2000 ] ) . Reference informations, which varied given the retrospective nature of the survey ( Table 1 ) , were used for both developing country choice and for the rating of map truth. In add-on to utilizing high-resolution imagination, intensive fieldwork was conducted in the survey country from 6 February to 22 March 2003 to roll up land truth information for the analysis of the 2003 image. A hardcopy false colour composite ETM+ ( RGB 432 ) image picturing different LULC types was used in the field to place bing old termlandnext term screen characteristics, with particular attending given to spectrally similar characteristics. Based on this fieldwork, a land truth map was prepared for turn uping preparation pels on the image and 200 mention informations points were collected utilizing a planetary placement system ( GPS ) . This GPS information was so overlaid with the image in GIS to choose developing countries and for accuracy appraisal ; 100 of the GPS points were used for trying and the ot her 100 were used for measuring the truth of the categorization. Table 1. Different informations types used in this survey.Sl. No.Type of informations usedScale/resolutionYear1 Survey of Bangladesh topo-sheets 1: 50,000 1973, 1991 2 CUS old termlandnext term usage map 1: 10,000 1975 3 FAP 8A old termlandnext term usage map 1: 10,000 1991 4 Landsat MSS image 79A m 1975 5 SPOT Pan image 10A m 1989/90 6 Landsat TM image 28.5A m 1992 7 Landsat ETM+ image 28.5A m 2003 8 IKONOS Pan image 1A m 2003 9 Municipal boundary informations 1: 50,000 2001 10 Geomorphic map 1: 25,000 1999 11 Drain map 1: 25,000 2000 12 City Guide Maps 1: 20,000 1991, 2002 13 Socio-economic informations Annually and decadala 1973-2005 Full-size tabular array aA Census records.Position Within ArticleImage categorizationA alteration of the Anderson Scheme Level I method was used to measure LULC old termchangesnext term in this survey ( Anderson, Hardy, Roach, & A ; Witmer, 1976 ) . Specifically, extra factors such as the major old termlandnext term usage classs within the survey country and differences in the spacial declaration of the images, which varied from 30 to 79A m, were considered in planing the categorization strategy. Six separate LULC types were identified: H2O organic structures, wetlands/lowlands, built-up countries, cultivated old termland, following term flora and bare soil/landfill ( Table 2 ) . Table 2. old termLandnext term use/cover categorization strategy. old termLandnext term use/Cover TypesDescriptionBuilt-up Residential, commercial and services, industrial, transit, roads, assorted old termurban, following term and other old termurbannext term Bare soil/landfill sites Exposed dirts, landfill sites, and countries of active digging Cultivated old termlandnext term Agricultural country, harvest Fieldss, fallow old termlandsnext term and vegetable old termlandsnext term Vegetation Deciduous forest, assorted forest old termlands, following term thenars, conifer, chaparral and others Water organic structures River, lasting unfastened H2O, lakes, pools and reservoirs Wetland/lowlands Permanent and seasonal wetlands, low-lying countries, marshy old termland, following term rivulets and gully, swamps Full-size tabular arrayPosition Within ArticleAll orbiter informations were studied utilizing spectral and spacial profiles to determine the digital Numberss ( DNs ) of different LULC classs prior to categorization. Training samples were selected from the mention informations and accessory information ( Table 1 ) . Sixty to seventy preparation sites, runing in size from 286 to 7800 pels, were used to develop the images. Training samples included 5-10 subclasses for each category except for bare soil/landfill. The preparation samples were so refined, renamed, merged, and deleted after rating of the category histogram and statistical parametric quantities. A supervised upper limit likeliness categorization ( MLC ) algorithm, antecedently demonstrated to obtain the best consequences from remotely sensed informations if each category has a Gaussian distribution ( Bolstad & A ; Lillesand, 1991 ) , was so applied to each image. However, several of the categories were falsely classified in the supervised categorization of LULC, with certain old termurbannext term colonies being misclassified as landfill sites due to their holding similar spectral features. Similarly, the wetland category was merged with the lowland category as it was non possible to divide them due to similar spectral belongingss, and the wetland/lowland class and cultivated old termlandnext term were besides falsely classified. Post-classification polish was hence used to better the truth of the categorization as it is a simple and effectual method ( Harris & A ; Ventura, 1995 ) . In add-on, since the old termurbannext term surface is heterogenous and composed of a complex combination of characteristics ( e.g. edifices, roads, grass, trees, dirt, H2O ) ( Jensen, 2007 ) , assorted pels are a common job when utilizing medium-spatial declaration informations such as Landsat ( Lu & A ; Weng, 2005 ) . The job of assorted pels was addressed in several ways. For illustration, thematic information ( e.g. H2O organic structures, flora, and bare dirt ) was foremost extracted from the Landsat informations utilizing the V-S-W index ( Yamagata, Sugita, & A ; Yasuoka, 1997 ) , before a rule-based technique utilizing thematic information and GIS informations ( e.g. DEM, municipal maps and H2O organic structures, etc. ) was employed in ERDAS spacial modeller to rectify antecedently misclassified old termlandnext term scree n classs. Although this rule-based technique greatly improved the MLC categorization, some misclassification between wetland and cultivated old termlandsnext term was still observed, chiefly because of the geographical adjacency of these classs. GIS tools, such as Area of Interest ( AOI ) were so applied to the informations utilizing ocular analysis, mention informations, every bit good as local cognition, to divide and recode these screens so that they more closely reflected their true categories. By using these techniques, the consequence obtained utilizing the supervised algorithm could be well improved. Finally, to cut down the salt-and-pepper consequence, a 3A A-A 3 bulk filter was applied to the classified old termlandnext term screens ( Lillesand & A ; Kiefer, 1999 ) .Accuracy appraisalBy and large, categorization truth refers to the extent of correspondence between the remotely sensed informations and mention information ( Congalton, 1991 ) . In order to measure the truth of old termlandnext term screen maps extracted from Landsat informations, a sum of 125 graded random pels were generated for the 1975 and 1992 informations and 100 pels for the 2003 old termlandnext term screen map. Accuracy appraisal of the LULC maps was so performed utilizing field informations and the geographical characteristics on old termlandnext term usage maps, high-resolution images, and SOB topographic maps, and the consequences were recorded in a confusion matrix. A non-parametric Kappa trial was besides used to mensurate the categorization truth as it accounts for all the elements in the confusion matrix instead than merely the diagonal elements ( Rosenfield & A ; Fitzpatirck-Lins, 1986 ) . The entire truth of the Landsat-derived LULC information was 85.6, 89.6 and 90 % with matching Kappa statistics of 82.7, 87.5 and 87.9 % for MSS, TM and ETM+ , severally, confirming the standard truth of 85-90 % for LULC mapping surveies as recommended by Anderson etA Al. ( 1976 ) . The application of rule-based post-classification polish was found to be effectual and improved truth by 10-12 % . The MSS image had the lowest overall truth, which may be due to its harsh spacial declaration ( Haack, 1987 ) . Yang and Lo ( 2002 ) besides noted that the jobs associated with right sorting assorted pels additions with diminishing image declaration, ensuing in spectral confusion. In this survey, spectral confusion was higher in the MSS image than in the TM/ETM+ images. old termChangenext term sensing This survey employed the post-classification old termchangenext term sensing technique, which is efficient in observing the nature, rate and location of old termchanges, following term and has been successfully used by a figure of research workers in the old termurbannext term environment ( Hardin etA al. , 2007 ) . An overlay process utilizing the GIS was adopted in order to obtain the spacial old termchangesnext term in LULC during three intervals: 1975-1992, 1992-2003 and 1975-2003. Application of this technique resulted in a bipartisan cross-matrix, depicting the chief types of old termchangenext term in the survey country. Cross tabular matter analysis on a pixel-by-pixel footing facilitated the finding of theA measure of transitions from a peculiar old termlandnext term screen category to other old termlandnext term usage classs and their corresponding country over the period evaluated. A new thematic bed incorporating different combinations of â€Å" from-to † old termc hangenext term categories was besides produced for each of the three six-class maps. LULC old termchangesnext term and kineticss of old termurban expansionnext term Spatial forms of LULC old termchangesnext term in the Greater Dhaka country for 1975, 1992 and 2003 are shown in Fig.A 2. In 1975, lowlands, cultivated countries and H2O organic structures were the dominant old termlandnext term usage types, and the way of old termurban expansionnext term ( herein referred to as the built-up class ) was northerly. In 1992, the built-up class replaced most of the H2O organic structures and depressions within the metropolis every bit good as the cultivated old termlandnext term along the peripheral zone. Surveies of historical maps and the available literature suggest that the depressions and H2O organic structures within the metropolis disappeared comparatively rapidly after independency as countries were developed for residential, commercial, academic and concern intents ( Siddiqui etA al. , 2000 ) . Between 1975 and 1992, when route transit from Dhaka to the backwoods was improved by the building of Bridgess over the rivers ( Islam, 1996 ) , old ter murban expansionnext term extended further to the North, north-west and to the West. Consequently, the country of cultivated old termlandnext term and H2O organic structures declined markedly during the period 1975-1992 ( Louis Berger & A ; BCL, 2005 ) . In 2003, the forms of LULC old termchangenext term revealed that Dhaka started to spread out in all waies, chiefly at the disbursal of vegetated and wetland/lowland countries. The rate of old termurbannext term invasion ( Fig.A 2 ) on other old termlandnext term utilizations increased significantly following the readying of a new Master Plan in 1995 and the development of substructure ( Siddiqui etA al. , 2000 ) . The building of a span over the Buriganga River accelerated old termurban expansionnext term in the southern and northwesterly waies. The spacial distribution of the exposed soil/landfill class is besides seeable in the maps produced ( Fig.A 2 ) , clearly exemplifying the transmutation of lowland countries to landfills on the outskirts of Dhaka. Life-size image ( 292K ) – Opens new window Life-size image ( 292K ) Fig.A 2.A Classified old termlandnext term use/cover maps of Greater Dhaka in 1975, 1992 and 2003.Position Within ArticleThree sectors, viz. the populace, private, and individual-household sectors, are responsible for all of the old termlandnext term developments in Dhaka. Most of the old development undertakings were undertaken on an ad hoc footing by the populace sector, chiefly in countries that were antecedently used for agribusiness and that were free from flood ; illustrations of such developments include Gulshan Model Town, Banani, Uttara Model Town and Dhanmondi ( Chowdhury, 2003 ) . In recent old ages, belongings development has proliferated in Dhaka, and belongings developers have developed both wetlands and agricultural countries without any consideration of the attendant environmental costs. In add-on, single families have started to develop the peripheral countries ( Islam, 1996 ) . In the fieldwork conducted in this survey, old termlandnext term guess was observed to ho ld had a pronounced influence on the development of suburban countries. In response to increasing old termlandnext term monetary values and turning demand for lodging, Lowlandss and agricultural countries in the periphery zone are quickly going built-up by the person and belongings developers. While suburban development is a really complex procedure that is known to be influenced by a assortment of factors, including guess and old termlandnext term monetary values, these factors may non adequately explicate the procedure of suburban development in the survey country. A more elaborate survey is hence required in order to understand the assorted factors act uponing suburban development in the greater Dhaka country. Furthermore, hapless coordination among executive bureaus is besides responsible for the decrease observed in natural resources in the survey country. For illustration, in the Dhaka-Narayangonj-Demra ( DND ) undertaking, despite about 6000A hour angles being set aside for a gricultural production in the 1960s, the country has been used by local and migratory people for residential intents since 1990s without any blessing from the governments concerned. Cases such as this illustrate the deficiency of effectual coordination among the organisations involved in the planning and development of Dhaka. Analysis of the LULC old termchangesnext term in Dhaka over clip revealed a considerable addition in the built-up countries over the survey period ; built-up countries increased by 6132A hour angle between 1975 and 1992, which is an norm of more than 360A haA yra?’1. Similarly, built-up countries increased in size by 4422A hour angle from 1992 to 2003, more than 400A haA yra?’1, and the net addition of old termurbannext term countries over the survey period was 10554A hour angle ( Table 3 ) . When compared with other metropoliss in the part, such as Ajmer City in India, the rate of the old termurban expansionnext term in Ajmer City was 29.2A haA yra?’1 over the period 1977-1989 and 32.4A haA yra?’1 from 1989 to 2002 ( Jat, Garg, & A ; Khare, 2008 ) . Although urbanisation is by and large related to demographic old termchangenext term and economic growing ( Li, Sato, & A ; Zhu, 2003 ) , the nature of old termurban expansionnext term in the survey country ma y besides be associated with other factors such as topography, old termlandnext term usage, and transit. Close scrutiny of the old termchangenext term sensing statistics revealed that about 6132A hour angle of the urbanised country in Dhaka were antecedently either agricultural countries or H2O organic structures between 1975 and 1992. Conversely, 4422A hour angle of the freshly urbanized countries were antecedently flora or wetlands during the same period. By and large, two factors were observed to hold promoted old termurbannext term growing: ( 1 ) increased economic activity associated with the constitution of economic zones ( e.g. export treating zone ) and ( 2 ) redefinition of the metropolitan country. Between 1975 and 1992, reclassification of old termurbannext term countries every bit good as infrastructural development played a important function in the old termexpansion of urbannext term countries. For case, the nor'-west and southerly old termexpansionnext term of the met ropolis occurred in response to building of a inundation embankment in 1992 ( Fig.A 1 ) and a span on the Buriganga River in 2001. The spacial features of built-up countries have besides been shaped by the building of a figure of transit paths in the same period, as understood from historical map analysis and field visit. The old termexpansionnext term to the E and nor'-east led to the development of unplanned suburbs in the Lowlandss and agricultural countries that were antecedently located in those countries. Table 3. Consequences of old termlandnext term use/previous termlandnext term screen categorization for 1975, 1992 and 2003 images demoing country of each class, category per centum and country changed. old termLandnext term use/cover types197519921975-1992 country changed ( hour angle )20031992-2003 Area changed ( hour angle )Area ( hour angle )%Area ( hour angle )%Area ( hour angle )%Water organic structures 2976.1 7.2 2492.8 6.0 a?’483.3 2050.9 4.9 a?’441.9 Wetland/lowlands 13155.1 31.7 11646.8 28.0 a?’1508.3 9124.0 22.0 a?’2522.8 Cultivated old termlandnext term 12040.8 29.0 7934.3 19.1 a?’4106.5 8466.6 20.4 532.3 Vegetation 6585.2 15.8 5686.7 13.7 a?’898.6 3992.2 9.6 a?’1694.4 Built-up 5550.5 13.4 11682.4 28.1 6131.9 16104.6 38.7 4422.2 Bare soil/landfill 1256.2 3.0 2121.0 5.1 864.8 1825.7 4.4 a?’295.4 Entire 41564 100 41564 100 41564 100 Full-size tabular arrayPosition Within ArticleThe GIS analysis besides revealed that the country occupied by H2O organic structures decreased by 16.2 % , wetlands by 11.5 % , cultivated old termlandnext term by 34.1 % , and flora by 13.6 % between 1975 and 1992. Another important old termchangenext term was the diminution in wetlands and flora from 1992 to 2003. In 1992, wetlands and flora occupied 28 % and 13.7 % of the entire survey country, but by 2003, these countries had declined to 21.7 % and 5.5 % , severally. Conversely, built-up countries increased in size by 37.9 % in the period from 1992 to 2003. A little addition in cultivated old termlandnext term ( 6.7 % ) was besides observed in this period. The diminution of flora and wetlands was clearly due to intensification of old termurbannext term development in the greater Dhaka country, peculiarly through the procedure of suburban development. As shown in Table 4, there has been a pronounced old termchangenext term in LULC ove r the 28-year survey period. Table 4. Major old termlandnext term use/cover transitions from 1975 to 2003.‘From category ‘‘To category ‘1975-1992 Area ( hour angle )1992-2003 Area ( hour angle )Water organic structures Built-up 655.7 269.5 Bare soil/landfill 71.4 82.7 Wetland/lowland Built-up 660.0 1414.7 Cultivated old termlandnext term 2007.8 2743.6 Bare soil/landfill 416.8 492.5 Cultivated old termlandnext term Built-up 3944.3 2309.0 Bare soil/landfill 794.7 391.8 Vegetation Built-up 1725.1 1069.1 Cultivated old termlandnext term 932.4 1387.5 Bare soil/landfill 333.7 287.3 Bare soil/landfill Built-up 453.8 1047.4 Full-size tabular arrayPosition Within ArticleThe post-classification comparing of old termchangenext term sensing was carried out utilizing GIS, bring forthing old termchangenext term maps for understanding the spacial form of old termchangenext term between old ages ( Fig.A 3 ) . Table 4 shows a sum-up of the major LULC transitions, viz. ‘from-to ‘ information, which occurred during the survey period. As indicated, the bulk of old termurban landnext term was acquired by change overing countries that were antecedently agricultural old termland, following term flora, H2O organic structures or low-lying countries, proposing the being of increased force per unit area on natural resources in Greater Dhaka to run into the increasing demand for old termurban land.next term Life-size image ( 247K ) – Opens new window Life-size image ( 247K ) Fig.A 3.A Major old termlandnext term use/conversions in Greater Dhaka ( a ) 1975-1992 ( B ) 1992-2003.Position Within ArticleThe survey revealed that the old termurban expansionnext term in Dhaka has been comparatively rapid and has resulted in widespread environmental debasement. The procedure of old termurban expansionnext term in Dhaka was observed to change markedly over the old ages examined in this survey ; specifically, the metropolis expanded by 6131.9A hour angle during the 17-year period from 1975 to 1992 and 4422.2A hour angle in the 11-year period from 1992 to 2003. Landsat images revealed that old termurban expansionnext term in two periods examined in this survey did non happen equally in all waies ; new developments were observed along the fringe of old termurbannext term countries every bit good as in the countries that had already been urbanized. The rapid gait of urbanisation in Dhaka means that it has non been possible for the municipal authorities to supply basic old termurbannext term comfortss to the population, which has led to a broad scope of environmental jobs. For illustration, old termurbannext term development facilitated by old termlandnext term filling has been shown to hold a negative impact on natural home ground and biodiversity ( [ Alphan, 2003 ] and [ Dewidar, 2002 ] ) . Vulnerability to temblor related jeopardies has besides increased since a major part of Dhaka ‘s recent development has taken topographic point in landfill sites ( Kamal & A ; Midorikawa, 2004 ) . In southern Dhaka, landfills have contributed to dir ty pollution, ensuing in reduced flora ( Khatun & A ; Hoque, 1994 ) . Uncoordinated urbanisation and the creative activity of landfill sites have intensified the extent of flood in the metropolis during the moisture season ( Alam & A ; Rabbani, 2007 ) , which is peculiarly critical in the western parts of Dhaka ( Maathuis, Mannaerts, & A ; Khan, 1999 ) . Flood hazard potency has been elevated due to continued infilling of H2O organic structures, wetlands and low-lying countries ( Dewan & A ; Yamaguchi, 2008 ) . In add-on, the speed uping growing of slums is impacting the metropolis ‘s physical and human environment. Harmonizing to CUS etA Al. ( 2006 ) , the slum population of Dhaka ( about 37 % of the metropolis ‘s population ) has doubled in a decennary, to make 3.4 million in 2006 from 1.5 million in 1996. The environment of these informal colonies is highly unhygienic as they are in close propinquity to solid waste mopess, unfastened drains and cloacas, embankments, a nd along railroad lines ( Islam, 1999 ) . Consequently, the people populating in slums are highly vulnerable to inundations ( Rashid, 2000 ) and they besides suffer from an acute deficit of drinkable H2O ( Akbar, Minnery, Horen, & A ; Smith, 2007 ) .Driving forces analysisLULC old termchanges and urban expansionnext term of Greater Dhaka is governed by a combination of geographical, environmental and socio-economic factors. Although population growing is the primary cause for rapid urbanisation, the part of other causes such as economic development and physical factors besides needs to be assessed. To measure the mechanisms underlying the old termchangesnext term in LULC and subsequent old termurban enlargement, following term we performed a arrested development analysis of built-up countries utilizing selected physical and socio-economic variables ( lift, incline, population and GDP ) , and presented the consequences in Table 5. old termUrbannext term country informations were extr acted from one-year BBS statistics since RS informations merely cover three old ages. To analyze the effects of incline and lift on old termurban enlargement, following term average values of incline, and lift of both developed and developing countries in the metropolis were calculated from a digital lift theoretical account. Socio-economic informations, such as population and GDP values were obtained from the decadal and annually one-year tabular arraies of the Bangladesh Bureau of Statistics ( Table 1 ) . Table 5. Regression analysis of factors underlying old termurban expansion.next termDriving factorsCoefficientsRobust criterion mistakeTpA & gt ; A |t|Population 1.776 0.633 2.808 0.019 GDP 0.0001 0.000 4.730 0.001 Elevation 0.549 0.295 1.861 0.092 Slope 0.028 0.057 0.494 0.404 Changeless a?’5.058 5.811 a?’0.870 0.404 Full-size tabular array R2A =A 0.947 ; ( ProbA & gt ; A FA =A 0.000 ) ; Dependent variable: Built-up country.Position Within ArticleCensus informations indicate that the old termurbannext term population of Dhaka was merely 0.34 million in 1951, increasing to 2.6 million in 1974 with an one-year growing rate of 9.32 % during 1961-1974 ( Islam, 1999 ) . By 1981, the population had reached 3.44 million. The population reached 6.92 million in 1991 and 10.7 million by 2001 ( BBS, 2001 ) . Presently, the population of Dhaka is more than 12 million with an one-year mean growing of 5 % , compared to the national growing of 2.1 % ( Bangladesh Bureau of Statistics ( BBS ) , 2005 and [ The World Bank, 2007 ] ) . The rapid growing of the old termurbannext term population has chiefly resulted from rural-previous termurbannext term migration and estimates show that more than 60 % of people in Dhaka have migrated from rural countries ( Islam, 1991 ) . Intelligibly, this addition in the population had the consequence of i ncreasing force per unit area on the limited resource-base, and significantly contributed to the old termexpansion of urbannext term countries by glade of natural flora and infilling of low-lying countries. Table 5 clearly shows that old termurban expansionnext term is positively related to population growing. Dhaka ‘s economic development is another factor that has contributed to rapid urbanisation. For illustration, Dhaka ‘s gross domestic merchandise ( GDP ) was about 11,312 million Taka1 in 1976, 129,665 million Taka in 1992 and 162,490 million Taka in 1995. Presently, the GDP of Dhaka is 354,240 million Taka and the metropolis ‘s portion of the national economic system is 19 % ( BBS, 2005 ) . The economic development associated with the roar in ready-made garments since the 1980s has had a important impact on old termexpansionnext term of the metropolis country. This economic activity has besides resulted in a big inflow of rural-previous termurbannext term migrators in the same period ( Islam, 1996 ) . In add-on, Dhaka supports more than 40 % of Bangladesh ‘s industry, farther suggesting that the economic development and industrialisation has led to a higher rate of old termurban expansion.next term The arrested development analysis revealed that GDP exercised positive effects on old termurban land expansionnext term ( Table 5 ) . As in other old termurbannext term centres, the way of old termurban expansionnext term in Dhaka has been extremely influenced by its physical scene, peculiarly its topography. The four major rivers, swamps and depressions within and around the metropolis have ever played a polar function in the development of built-up countries in the metropolis. Urbanization ab initio occurred in the elevated countries that were non affected by inundation. Once all the elevated places had been developed, the lifting demand of old termurban landnext term has been met by the transmutation of low-lying countries, vegetated countries and wetlands. The development of wetlands, for case, has led to a significant loss of natural resources and an addition in habitat debasement. The growing of belongings developers has accelerated invasion of old termurbannext term countries on wetlands and threatens biodiversity. Two geophysical indexs were used in the arrested development analysis ( Table 5 ) and found th at lift has major influence on old termurban expansionnext term while incline has non passed the important trial.DecisionsThis survey has assessed LULC old termchangesnext term and the kineticss of old termurban expansionnext term in Greater Dhaka, Bangladesh utilizing RS informations in concurrence with socio-economic variables. old termUrban expansionnext term was quantified for the last 28 old ages utilizing the post-classification comparing technique. Greater Dhaka was found to hold experienced rapid old termchangesnext term in LULC, peculiarly in built-up/previous termurbannext term countries. Analysis revealed that old termurbannext term countries increased by 6131A hour angle during 1975-1992 and 4422A hour angle from 1992 to 2003, which resulted in a significant decrease in the country of H2O organic structures, flora, cultivated countries and wetlands/lowland. The dramatic old termexpansion of the urbannext term countries of Dhaka exhibited clear spatio-temporal differences . The transition of H2O organic structures, flora and low-lying countries to old termurban landnext term has caused extended and varied environmental debasement in the survey country, and the exposure to implosion therapy and the growing of slums have been the chief negative results associated with the rapid old termurbannext term development. old termUrban land expansionnext term has been mostly driven by lift, population growing and economic development. Integrated usage of GIS, RS and socio-economic informations could therefore be efficaciously used to understand the spatial and temporal kineticss of LULC old termchanges.next term The reading and categorization of RS informations were utile for gauging the rate and spacial form of the old termurban expansionnext term in Greater Dhaka of Bangladesh. As dependable and current informations are missing for Bangladesh, the old termlandnext term usage maps produced in this survey will lend to both the development of sustainable old termurban landnext term usage planning determinations and besides for calculating possible hereafter old termchangesnext term in growing forms.