Keywords: BangkokMetropolitanRegion,LandscapeMetrics,Fragstats Extended MetropolitanRegion. the in landscapes ecological of complexity the of characteristics spatial reveal to parameters research as related to the increased dissimilarity of landscape composition. The Ecological landscape metrics were used pattern and has unique spatial characteristics. It also appears that the loss of landscape diversity its changed is has possibly landscape BMR selected Each complex. more been previously have patterns landscape ecological BMR’s that reveals metrics landscape of changes the “Fragstats”, analysis software computer the using by and its change, land-use and agricultural on landscape focusing ecology,by ecological landscape BMR’sstudying By of changes. overview the understand to is study this of goal The land-uses. landscapes, the richness of patches and the diversity of ecology are defined by complex patterns of mixed perennial plots, horticulture, farming facilities and aquaculture lands. It could orchards, be fields, said crop that fields, 140 BMR’s paddy usage; surrounding than agricultural various more to related has classifications land-use BMR of types the Thailand, Bureau, Development Land the of database 2012 to According Komgrij Thanapet Landscape in theBangkokMetropolitanRegion Configuration Changes Spatial Compositionand ABSTRACT ** * B Taiwan [email protected] College ofPlanningandDesign,NationalChengKungUniversity, Taiwan Correspondingauthor:[email protected] College ofPlanningandDesign,NationalChengKungUniversity, Square Kilometers of the most significant delta area and productive agricultural lands of Thailand. of lands agricultural productive and area delta significant most the of Kilometers Square angkok and fiveprovinces in the vicinity, called Bangkok MetropolitanRegion, BMR,occupies 7,650 * / Shiann-FarKung Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape **

Nakhara 9 Nakhara 10 C Overlay2057BMR developmentmapbyDPTon201211-categories land-usemapbyLDD (C) 2057BMRdevelopment planbyDPT, Urban-ruralContinuuminThailand, Thailand,(B)Webster’s (A) Figure 1: of the delta area. This study of the changes in BMR’s productive agricultural land and the complex ecology on impact an created has development economic case study where the fast growth of urban sprawl and interesting an is Region Metropolitan Bangkok The to develop theories and an understanding of change. McGee’s “Desakota” is also being used as a model China, today’s and Asia Southeast In Theory”. Place “Central Christaller’s or bands Thunen von as known Influence” of “Zones models: classic these using planned and was studied region urban the Historically cities. satellite and towns, villages, building, scattered with mosaic space green a ring, urban surrounded the and land built continuous of area metropolitan the of combination a is region From an ecological landscape perspective the urban L Region o B Komgrij Thanapet/Shiann-FarKung a a nd ng sca k o k pe f

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a t n U e r ogeneo rba n us r “Phak Mahanakhon” ( or Metropolitan Region is also called “Greater Bangkok” Nonthaburi, SamutPrakanandSakhon. This Thani, Pathum Pathom, Nakhon provinces- vicinity five its and Bangkok of area the includes Region administration of Thailand, the Bangkok Metropolitan and organization regional official the to According conditions andecologicallandscapeapproach. planning in Thailand using the spatial environmental regional further encourage to expected is land-use experiencing fractal physical development because is BMR the policies, decentralization current the to small autonomous governances are assembled. Due are administratively independentwherehundredsof territories BMR All mean. national the than higher times 14 also is density average census. The 2012 the to according population nation’s the of % 22.6 reached it has land % ofnational 1.5 only occupies that region primate a is it although because area BMR is considered a national strategic development ภาคมหานคร ) in Thai. The) Areas under urbanization process, 3) Rural areas Rural 3) process, urbanization under Areas 2) areas, developed Fully 1) areas; development urban of types 4 of configurations spatial the with this plan purposed the future structure of the region conservation, and development urban balance To development distributionthroughouttheregion. and economy, in sufficiency agriculture, urban quality high by surrounded city compact a of ideas conceptual the purposed policy this thus million, 12.4 reach will population BMR 2057 the that is Expectations plan. development BMR 2057 the instituted (DPT) Thailand- Interior, of Ministry the the Department of Public Works and Town Planning- To respond to the rapid growth of the 1990s, in 2004, (Ratanawaraha, 2010) Administration. Metropolitan Bangkok BMA, the government, local primate Thai only and one the by dominated is system administrative BMR’s the their own comprehensive plans. On the other hand, Tambon haveto or level township the at governments local the (E) McGee’s DesakotaDiagrammodifiedbyRodrigue ThailandDynamicRegion,(D)Gawin’s(C) Webster’s BangkokMega-urbanregion,and (A) Forman’s BangkokUrbanRegion,(B)TheMini-megalopolis byin-migration(Sternstein,1976), Figure 2: depend on themselves in preparing preparing depend onthemselvesin Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape Furthermore, based on McGee’s “Desakota” theory, 2006) Wanisabut, (Suwat 2003) (Webster, region. sub- Riviera Thai as known gulf Thai of side other dynamic region from Eastern Seaboard (ESB) to economic the an as extended been have economics Bangkok’s that out points Webster boundary, Unlike the perceptions of the political administrative 14.56 millionbytheyear2010. exceeded population the and 2013 by million 10.5 reached already BMR the of population registered Works and Town Planning, 2004) It Publicis noted that the of Department (The pieces. smaller into and road networks, turning the agricultural landscape would be connected by low-density residential zones These towns. satellite and sub-centers of types metropolitan region will be decentralized with various lands. whole agricultural the plan, this to According and rural of Centers 4) and centers, District and Provincial 3) centers, Regional 2) center, a National 1) centers; urban of types four included also plan The areas. Rural 4) and urbanization, under

Nakhara 11 Nakhara 12 today’s BMR. In relation to the direction of national of direction the to relation In BMR. today’s compound is the area of 4 rivers and the location of of ChaoPhrayaDeltadevelopment. This delta years 300 illustrated Kaida and Jarupongsakul review, historical on Based 2004) Kuneepong, & (Tonmanee involvements. stakeholders’ and the region. These problems require pollution controls throughout structures land-use of change the from stem problems environmental BMR’s that noticed Kuneepong Tonmanee2002) and (Jones, regions. urban these of future the predict to infrastructure of development and conditions, socio-economic of population projections, size of spatial expansion, mega-urban regions, Jakarta and Manila, in terms ASEAN two other with Bangkok compared also Thailand regions. (McGee & Greenberg, 1992) Jones growth compared with other ASEAN cities and other presents the BMR sectors’ economics and population Greenberg and McGee development. economy socio- and elements spatial between relationships and changes, growth, of terms in conditions spatial BMR the explained have scholars Several towns. (Forman,2008) green space, villages, distributed constructions, mosaic, and land of compounds the with Ring region Urban- 4) and Cities, Satellite Outer and Inner 3) City, 2) Metropolitan Area and Continuous Built Land, this area could be classified into 4 sections: 1) Major region where the urban population is the 250,000 to 10 For million, vicinities. to center urban the from urban region could be defined with flow or movement interrelationships. Therefore, the boundary of the where the urban area and its surrounding have close Forman defines an urban region as a land or territory Mosaic”. “Land as region whole of cover land and land-use the consider to is planning ecological with planning ormetropolitanregionalalong regional urban of principle basic the that indicates (2008), Forman, cropland. dominated and rivers 4 of areas delta the of system complex the center, city Bangkok’s from area extended 80-km the includes BMR the concept Forman’s Using BMR. or about 2.6 times bigger than an official size of the clgcl esetv, s agr hn 000 Km 20,000 than larger is perspective, ecological T.T.Richard on based landscape region, Forman’s metropolitan Thai of size the contrary, the On Muller, 2004) & (Webster peri-urbanization. of model Thai the extension from Bangkok through ESB, it represents km. 190 With definition. extension ASEAN’surban of character associate and unique the on based “peri-urban” a area the considers study Webster’s Komgrij Thanapet/Shiann-FarKung 2

ht h evrnet f h 21 the of environment the that the urban fringe. Yokohari and others also suggests on populations for sustainability and resiliency high has landscape of kind This landscape. vernacular is belt green BMR’s of characteristic unique the Yokohari and Desakota, McGee’s to Referring flourish. to sprawl urban and development density low- allows that zone conservation agricultural and rural called so a is belt green Bangkok’s growth. urban control to prepared not and disconnected is Bangkok of belt green the cities, European some and cities two these Unlike areas. belt green denotes thatthesemetropolitanregionshave (2002) al. et and Yokohari cities. Asian mega two Seoul, and Tokyo with similarities has Bangkok land. (Suwanarit,2010) agricultural peri-urban on agglomerations urban modern systemsand irrigation manmade along expansion land paddy the of reviews historical on based- area, Rangsit BMR, east the of morphology Paksukcharern, 2012) Suwanarit also pointed to the & Peerapun, (Summaniti, at1:50,000. analyzed 2001 – 1998 and 1975 – 1968 1913, - 1903 from data using areas urbanized modern and markets, floating orchards, canals, rivers, of structures delta structures to the west of BMR that are based on the Kaida, 2000) Summaniti and et al. mentions spatial & (Jarupongsakul networks. road and trains speed high of use the through centers the connecting “Multipolis” a became BMR 2020 The Cities”. pictured the 2020 landscape of the BMR as “Satellite development before 2000, Jarupongsakul and Kaida areas, urbanized areas, and agri-lands. They cited They agri-lands. and areas, urbanized areas, natural with interactions positive had BMR the of landscapes the that noted Thaitakoo and McGrath symbiosis. For their perception of “Amphibious City”, a were eco-system and patterns, agricultural lives, complex river, canal, and wetland system. People’s a through areas surrounding the to connected was Bangkok diversity. landscape of because land arable productive a was BMR the and Bangkok of landscape The city. land-based a to city based points out that Bangkok has changed from a water- Thaitakoo and McGrath vicinities. its and Bangkok of perception Thaitakoo’s Danai and McGrath’s “Amphibious City” and “Liquid Perception” are Brian Watanabe, & Yokota, 2000) even Sunday farmers’ activities. (Yokohari, Takeuchi, and environment, healthy and recreation balance, ecological as such requirements urban for support The BMR’s green belt could provide multifunctional landscapes. rural and urban of mixture the control st etr should century tools. 18 land mosaic indicators are selected as the scale, this research selects Fragstats as the analysis Devoted to a spatial change study at the metropolitan types ofplantation.) about details provides land-use by LDD. (For example, the third level of agricultural classified detail data of level third the included and BMR whole the of cover land and land-use include 01, 2006 – 07, and 2011 – 12. The data details also – 2000 different- three periods time collection data into divided was data this purposes, academic For used for present national agricultural zoning projects. Cooperation, Thailand, which is the same database and Agriculture of Ministry the (LDD), Department Development Land the of data spatial manipulates matrix. Referring to patch metrics studies, this study focus on land mosaic, patch, corridor, to and landscape and BMR the of configuration and composition study aims to investigate spatial structure, landscape this perspectives, ecology landscape on Based controls andspatialdevelopmentdatabase. development urban proper of lack to due emerging are that areas built-up rapidly from disturbances experiencing is BMR The 2005) Thaitakoo, & (McGrath resiliency. and balance natural of loss the to leading thus species some of extinction the dynamics, rapid man-made disturbance could cause patch to leads this Although ecosystem. the of diversity and species of number the balance help natural disturbances, such as big floodThe or bush matrix. fires, ecological of part a was disturbance” “the even that indicate Thaitakoo and McGrath Dynamics”, Patch “Ecology Pickett’s Steward to Referring degrees. different in aquaculture and agriculture urban to changes cause would road the of part Each fringe. urban the on spaces green the occupying land-uses and settlements new to lead transportation of modes new where case the as road ring Kanchanaphisek of emergence the used They expressways. of infrastructures modern the to due BMR the throughout scapes food- productive of loss the mentioned (2005) Thaitakoo and McGrath Aquacultural Fringe”, In utility and consumption. (McGrath & Taitakoo, 2010) infrastructures: transportation, irrigation, recreation, all of the demands that could be gained from modern served systems water-based delta, Bangkok the In of infrastructure could serve more than one purpose. kind one how of examples as Bangkok of side east and north the in paddies rice and Bangkok of side west the on system orchard-ditch the of cases the “Tasting the Periphery: Bangkok’s Agri- and Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape within thesamedistance. land-based infrastructure on peri-urban landscapes of impact the investigate to BMR the of road ring is the set of seven selective areas along the second module last The zones. land-use future to referring sub-landscapes nine contains module This DPT. bythe purposed and planned plan, development BMR 2057 the to referred areas cropped of set the is module second The module. controlled a as study. The first module is the whole BMR landscape modules are classified according to the aims of the study three The metrics. diversity and metrics, metrics, shape metrics, contrast metrics, aggregation classified into five simple categories; area and edge be would metrics Fragstats 18 All land). industrial and area, urbanization medium and high village, villages or gated community area, semiagri-land and on 5 land-use classification- agriculture land, urban landscape level and 2) land-use class level (focused three study modules on two levels: 1) the of whole BMR patterns landscape quantify to metrics primary and classes of the landscape. In the program, there patches of configurations quantitative investigates it addition In diversity. patch and evenness, patch richness, patch composition, class and patch also designed to study not only landscape structure, but also was program The Mosaics. Ecological of changes 3) elements, landscape of functions 2) structure, ecology landscape 1) landscapes: It was designed to study three aspects of ecological consider landscapes in to terms of habitat is patches. and matrix Fragstats the of basis the Therefore, elements. landscape other and patches of mosaic the landscape is an area or territory comprised of a that determines McGarigal landscape, of definition Godron’s and Forman’s 1986 to reference In 4.2. version is software current The software. ArcGIS program has been developed to be compatible with This 1995) Marks, & (McGarigal USA. Agriculture, forestry studies,supportedbytheDepartmentof USA for distributed and created was software the of version early The Oregon. of University the from programmer computer a Marks, J. Barbara and Massachusetts, of University at Professor and ecologist an McGarigal, Kevin by developed was program the of version second the theory, ecology landscape Forman’s to referring Strongly study. ecology landscape for program computer freeware well-known a is program Fragstats The Ecological Fragstats Metrics LandscapeStudy and

Nakhara 13 Nakhara 14 n UC (adue n ln-oe cags of changes) land-cover and (land-use LULCC on is used to report the environmental conditions based- future environmental planning, the CORINE program changes in various scales, sizes, and locations. For process of the phenomenon of urban and landscape other tools to investigate structure, function, and the as a significant tool, or used and then compared with used is It applied. are metrics landscape Fragstats the which to reports and studies several are There habitat systems complex and exchange ecological referencing own uniquespatialarrangementsorpatterns their have systems the of All systems. ecological or landscapes smaller-scale several a of be compound could there region a in that consider to has study the science, spatial a as ecology landscape regional understand to Furthermore, habitats. their own landscape matrix based on various species and its has land,- of piece small one even or regional, be they- global, continental, national, regional, sub- level landscape the of scales different the because area study of scale spatial the about concern be to needed researcher the that noted strongly Forman 3) 2) 1) elements (Forman,1995): be simply understood with three simple spatial could it complex, and diversified was world the of area each in ecology landscape though even that out points Forman of Landscapes and Regions”, In ring. urban-region in ecology to land-use planning and to study landscape In 1995, Forman discusses how to apply landscape whole landscape. the and “class”, “patch”, “cell”, from are metrics the of scales The metrics. the of scales proper or levels proper the are what realize to and metrics differentthe all of uses and Fragstats purposes the understand to researcher the upon incumbent is It selected. be to indicators or metrics of dozens are Komgrij Thanapet/Shiann-FarKung

landscape systemorlandmosaics. patch and corridor, or corridor and corridor as a patch, and patch between systems functional and coordination logical the is which Matrix, land coversorecologicalsystems. inadominanttypeofland-use, is homogenous it where land of piece long a Corridor,is which ecological systems. in a dominant type of land-uses, land covers or Patch or the piece of land, which is homogenous “Land Mosaic:the Ecology connectivity connectivity by investigating landscape structure and habitat predict to tool primary the as applied were China, as their case study and Shandong, five City, Fragstats metrics Jinan of part chose They model. gravity and theory graph with connectivity space green studied al. et and Kong 2006) (Blaschke, introduced. were metrics 20 Almost assessment. structural for criterion generate to and parameters, spatial research questions, to sustainable landscape connect a wide range of spatial metrics to particular virtue of this research on Fragstats application is to landscapes with an emphasis on the role of GIS. The highlights elucidate spatial concepts for sustainable which paper Blaschke’s is development, economic socio- and capital natural combines that direction 2002) Ahern, landscape sustainable on based Also & (Leitao planning. of phases or theme different a landscape composition metrics. Each metric is fit to critical ten recommended and paper Ahern’sLeito ecology. landscape Zonneveld’s and Forman’s 1995’s or planning landscape Steinitz’s 1990 and Fabos’s 1985 as such ideas experts’ renowned many to reference in review critical a made (2002) Ahern and Leitao Application”, its and Planning Land “Sustainable of principle the to relation In 2004) Nagendra, & Munroe, (Southworth, other. each to complementary were methods both that found authors The analysis. NDVI-based with compare to were applied metrics class Eight classification. forestry on focusing change, cover land and to examine the patterns of landscape fragmentation the use of vegetation indices (continuous data) and classification-based techniques (Discrete Data) with compare to aimed al. et and Southworth 2011) Bui, & Yamaguchi, (Pham, metrics. landscape of patterns unique had cities four all that found They land management legitimating the study areas. and planning of directions significant and quantity spatial of changes the on based were discussions their measurement, as metrics landscape seven Hanoi, Hartford, Nagoya, and Shanghai. By applying cities: four of composition urban of characteristics the compare and evaluate to wanted co-authors and study,Pham expansion urban an on Focusing metrics. (Uuemaa, Roosaare, Oja, & Mander, 2011) landscape 15 analyzed and km, 15 x km 15 sizes, sampling 35 in classifications land-cover 21 to picture of Estonian landscape. The authors referred whole the for explanation general a gave al. et and Uuemaa 2000) Union, (European countries. EU the of conditions spatial compare to IJI- and SHDI, NC, ED, PD, metrics- simple five only used report CORINE The Countries. Community European 11 successes, limitations, and possibilities of enriching enriching of possibilities and limitations, successes, the review to Thailand of area rural in study case a areas. (Millington & Bradley, 2008) Crew (2008) used forest on urbanization) and (farming settlement human and (road) development infrastructure of impact the investigate to Basin, Amazon the in Bolivia, of region Chapare the in communities old three 3 cultivation and settlement, management, land of phases the to metrics class simple three Millington and Bradley (2008) matched and correlated fragmentation, landscape forestry the of especially and ecologist landscape of concern key a on Based & Zhang,2011) differed in each period of study . (Tian, Jiang, Yang, megalopolis expansions and coalescence processes YRD of characteristics different that showed analysis Metric Changzhou. and Wuxi, Suzhou, megalopolitan regions in China: Shanghai, Nanjing, (YRD) Delta YangtzeRiver the of areas urbanized rapidly six of growth urban of patterns dynamic class metrics to investigate the spatial and simpletemporal ten applied Zhang and Yang Jianf, Tian, 2006) Underhill, & Twibell, Ma, (Ji, indices. based population- conventional to land-consumption of indices construction-based the compare to core urban the to areas built-up of distances between correlation another investigated also research The development.. urban of effect the study to land other vegetational forestland,and of built-up, metrics of classes between correlation the studied Ma, Ji, Twibellscales, city Underhill’sand research county,and metropolitan, the across trends sprawl urban of variations the compare and detect To (Herold, Couclelis,&Clarke,2005) products. mapping sensing remote of improvement and metrics spatial signature or tailored required process urban analysis, urban of studies the that suggested authors The changes. and structure spatial modeling: urban improve to metrics spatial Barbara, California, to combine remote sensing and Clarke used examples from the urban area of Santa and Couclelis Herold, application, Fragstats and 2011) In 2005, in the early days of LULCC research Botequilha-Leitão, & Valenzuela, (Aguilera, cities. characteristics of urban four land-use found in European on based interpretations made and 2020 in scenarios future simulated three with data spatial 2004 compared al. et study.and scenario Aguilera future a to applied were metrics class-based these the results of the study became more complex when quantifying changes in the urban growth patterns, but Nakagoshi, & Zong, 2010) This was done by simply patch cohesion patterns of green space. (Kong, Yin, Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape Kilianová, &Machar, 2013) Jelínková, (Pechanec, mosaic. landscape the in increase dissimilarity patterns of neighboring patches area, Pechanec and et al. introduced TECI metrics to To analyze the landscape fragmentation of the study 2008) (Crews, patterns. from function and process to linkages stronger exploring for means provided change, the detecting and time over subjects same metric approach, or longitudinal method: following the LULCC research. Crew found that the paneled-pattern area orperi-urbanization. urbanized to settlement rural from transformation 9% in 2007. The changes in this area represent the to up and 2001 in landscape BMR total the of 5% about is Classification peri-urbanization. or areas urbanized to settlements rural from transformation 9% in 2007. The changes in this area represent the to up and 2001 in landscape BMR total the of 5% about is classification second the in included not is classification of type This categories. study the to added is (Agri-Village) Residences Density Low or patch, the Agricultural Land Mixed with Rural Villages land same the on villages rural or urban 50% and areas are classified as 50% various agricultural land some which in classification LDD of level third the landscape and spatial change patterns. Because in ecological the of characteristics quantitative land-uses are the main focus to study and compare five first the study, this In Mangroves. or Bushes, Forrest, 11) and Land, Recreation or Parks Public 10) Sites, Garbage-dump or Pits, Rocks, Swamp, Government Bureau, 8) Water Bodies, 9) Meadows, and Land Institutional 7) Supply, Utility Public and Land, 5) Industrial Land, 6) Land for Transportation Villages or Low Density Residences, 4) Agricultural Rural with Mixed Land Agricultural 3) Community, Gated and Villages Urban by Occupied Land 2) Town and or High City and Medium Density 1) Urbanized Land, land-use: of types or classes 11 into classification land of levels three the aggregate supply.none-irrigation Therefore, thestudyhasto and supply areas, thatofirrigation as twoseparate classified was data The dataprocessing. and collection LDD of year first the is that as analyzed closely be will 2001 from Data research. this of focus primary the as data of level second the only from the different periods of time the study chooses the second levels of data. To correctly compare data and spatial patterns of land-use only in the first and After several reviews, the study focuses on change Methodology

Nakhara 15 Nakhara 16 1) They are: study. this in analysis landscape of modules two exception of the BMR landscape analysis, there are BMR landscape into modules for analysis. With the The analysis procedure starts by cropping the whole ArcGIS computersoftwareversion10.1. rasterizing, or attribute dissolving are operated with reclassifying, justifying, data the of All maintained. be would lands agricultural and bodies water of details significant the scale, grid meters square 2,500 the At meters). square x40 40 is database scale of LDD database. (The smallest detail of LDD square meters, which is proper to 1:4000 to 1:25,000 50 x 50 is patch each for size raster selected The images. mosaic the of compounds are which the grid files, to berasterized to have files vector all properly, program Fragstats the file. use vector To The LDD data is in the digital format of GIS polygon Research procedure Figure 3: Komgrij Thanapet/Shiann-FarKung density Residential Zone I (ELD 1), 3) the East the 3) 1), (ELD I Zone Residential density density Urbanized Zone (MD), 2) the East Low- Medium- 1) zones: development 30 selected of out zones nine to refers module This DPT.by purposed and planned is which plan, BMRdevelopment 2057 the of classification the uses study the of module first The 2) the case studies because they are in the BMR. Only seven from eight sections are selected as center.city the from road radius major the with eight sections based on important intersections into divided is road Kanchanaphisek of length two sides of the road. The whole 168-kilometer on kilometers five buffered areas linear along ring road modules or “K” modules are classified suburban and peri-urban. This Kanchanaphisek BMR’s the through cuts that road ring second the is which road, Ring the Kanchanaphisek of study a is module second The expected land-usesorfutureregionalzoning. of types all throughout selection the diversify to 2) and region the of river main the River, East or West side of BMR or of the the Chaophraya by separated be could which landscapes are:1) to diversify the area of study following the areas research primary The 2). (WAC II Zone Conservation Agricultural and Rural West the 9) and (WA1), I Zone WestAgricultural the 8) West Low-density Residential Zone II (WLD 2), the 7) 1), (WLD I Zone Residential density Low- West the 6) (EAC), Zone Conservation Zone I (EI 1), 5) the East Rural and Agricultural Agriculture Zone I (EA 1), 4) the East Industrial groups of index variables. The first is patch area patch is first The variables. index of groups basic two into classified be could metrics the of All applicable toclasslevelanalysis. classes, the study had to select the metrics that are some of configuration and composition on focusing analysis the For study. the of purposes the with capability their for tested and selected are metrics the of all Therefore, metrics. class and landscape both be could metrics the of Some (SHDI). Index & Juxtaposition Index (IJI), and Shannon’s Diversity (CONTAG),Interspersion Index Contagion (TECI), Index Contrast Edge Total (ECON), Distribution Index Contrast Edge (CWED), Distribution Edge Contrast-weighted (ENN), Distance Neighbor Nearest Euclidean (PAFRAC), dimension Fractal Perimeter-Area (PARA), Ratio Area Perimeter-to (AREA_MN), Patch Area Mean (LSI), Index Shape Landscape (ED), Density Edge (LPI), Index Patch Large (PD), Density Patch (PLAND), Landscape of Percentage (NP), Patch of Number (CA), Area metrics are as follows: Total Area (TA), Total (Class) Fragstats metrics as the basic indicators. These 18 18 selects primarily study the landscape, BMR the To study composition, configuration, and changes of Analysis modules Figure 4: Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape patches istoolow. sample of number the because interpreted be not could result the Sometimes, level. landscape and demonstrate the complexity of patch tometrics at class deviation standard or median, mean, as such functions statistic simple be to has metrics of kind Moreover, to apply to higher levels of the metric, this range of metrics from patch level to landscape wide level. in applicable be could it Therefore, patches. same-class the between distance the measures index This metrics. aggregation an is which ENN, is indices special of One variables. two between ratio and area, of size length, percentage, as such to select the indicators with different representation tried also study This metrics. shape complexity,as chosen for the same purpose, to understand shape this research. For example, in LSI, PARA, metrics and each PAFRAC are for used be could that index the results and to consider what the most applicable more than one index per one metric type to compare and equations could be selected, the study selected landscape composition. Because dozens of metrics or class understanding for equation the of forms several make could patch each of attributes simple two These parameter. patch is second the and

Nakhara 17 Nakhara 18 not be adjacent or share their edges together.The edges their share or adjacent be not should they logics, some with or, contrast high a when the two patches or classes of each patch have on a primary classification. The weight equals to “1” based conditions physical or attributes ecological in differ but edge same the share which patches two any between differences or similarities reflect from 0 to 1 scale measuring different magnitudes to Contrast weight ‘matrix’ (table and specified. 1) is a set of required numbers is file weight contrast the dissimilarity, or metrics contrast edge study To Dissimilarity Model Edge ContrastWeight or before running contrast metric models in Fragstats. up set or study separate a requires also metrics weight contrast edge or model dissimilarity The numbers. differentunequal among into types patch or a dissimilarity model to dissimilate the relationship weight contrast edge requires metrics of type This metrics. contrasting is it and equation the complete One type of metrics requires an escalation factor to metrics. corresponding as or index surrogate a as both landscape and class metric have to be selected Some of aggregation metrics that could be applied to of diverse metrics are only landscape level metrics. normally,but correlations, negative indices and the positive both be could correlation. They good a be some variables and index characteristics which could aggregation metrics and diversity metrics, there are between example, For data. of types all to applied be can that analysis an make to chosen then are indices several metrics), class and landscape both for used be could some metrics, patch only applied to every range of study (some becould support not could indices all because Furthermore, Table 1:Contrastweightmatrixordissimilarity Komgrij Thanapet/Shiann-FarKung term changeinecologicalconditions inthearea. long and major to lead could which farmland, rural of socio-ecology the to threat minor a as concern cause could estates community gated emerging floor area ratio of urban villages are considered low, and ratio open-space though even of contradiction, utility services, and economic activities. In this case based utilization causes changes in infrastructures, spoliation. Changing from major water-based to road- expresses urban sprawling and potential ecological village expansion into agricultural lands in Thailand urban areas, urbanized the in expansion density low- general Unlike definition. contrast weight of concern another are estates community gated and villages urban Expended concern. major a is “Green” and “Brown” between differentiation the that said be could it study, this In low. considered is weight contrast the which in ecology coherent as infrastructures such as water bodies are considered natural and forest, farmland, spaces, green among and between edges the contrary, the On land. industrial and land recreation and park or land industrial and land agricultural between edge the to given is contrast of degree high a Therefore, uses. other from pattern and change, land-use, 3) the research direction to differentiate agricultural according to the 2013 BMA comprehensive plan, and conducted uses nonconforming and conforming to related aspects 2) characteristics, ecological and natural use,- each of characteristics land-cover between differentiation the 1) aspects: different 3 from considered also is magnitude weight the interaction and ecological dissimilarity. In this study, land-use of guideline theoretical a from generated is classes between scheme weight a Developing value shownbetweenthetwoclasses. contrast no is there or same the as classified are weight becomes “0” when two shared-edge patches 1 Table 3:2001,2007,and2012landscapemetricscomparison Table 2:2001,2007,and2012landscapemetricscomparison . patch hasbeenbrokendownintoasmallersize. decreased number of LPI shows that the dominated the Subsequently, complexities. shape patch and patches of numbers the of terms in complex more become been has landscape BMR whole the that shows PARA, ED, PD, as such metrics, many the of number increased The system. complex more a into changed gradually has BMR the of the landscape 2012, to 2007 From time. of periods across comparison in the same year rather than comparing and projection data of tendency a represent could data the Therefore, collection. of means others t differenta in collected was from data way 2001 the characteristics, data the on (TableBased years. 2) that the 2001 data structure is incompatible with other Comparison ofthedatafromdifferent periodsshows Result WAC 2=theWest Rural and Agricultural ConservationZoneII Low-density Residential Zone I, WLD 2 = the West Low-density Residential Zone II, WA 1 = the West Agricultural WestZone I, the = 1 WLD Zone, Conservation and Agricultural Rural East the = EAC I, Zone Industrial East the = 1 EI Agriculture East I, Zone the = 1 EA I, Zone Residential Low-density East the = 1 ELD Zone, Urbanized Medium-density = MD Classified planningzonesin2057 BMRplan Contrast Edge Total= TCEI Distribution, Index, CONTAGIndex =Contagion Index,IJI=Interspersion&JuxtapositionandSHDIShannon’s DiversityIndex Contrast Edge = ECON Distribution, Edge Contrast-weighted = CWE Distance, Neighbor Nearest Euclidean = ENN dimension, Fractal Perimeter-Area = PAFRAC Ratio, Area Perimeter-to PARAArea, Patch = Mean = AREA_MN Index, Shape Landscape = Density,LSI Edge = ED Index, Patch Large = LPI TA =Total Area, CA = Total (Class) Area, NP = Number of Patch, PLAND = Percentage of Landscape, PD = Landscape Indices Patch Density,

In-text Abbreviation list. and Discussion Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape 1 ratio between edge ratio between contrast but based on TECI and ECON, which is the CWED, agricultural land could have the highest edge on Based considered. to aspects different two are and PARA_MN. For the edge contrast metrics, there gated communities have or significantly high land numbers in LSI village urban land, the of size and parameter patch between ratio the by measured complexity shape the For area. the in patch largest the contains and landscape BMR whole the of % 50 than more occupies It BMR. the of landscape and in 14 spatial indices. Industry,Agri- land is and the dominated Area, Urban Density High and City Community, Gates and Village Urban Village, and five major types of land-use; Agriculture, Agriculture of land-use for the whole BMR. This study focuses on spatial configuration and composition in some types At the class level (Table 3), the study concerns only contrast and total edge length, edge total and contrast

Nakhara 19 Nakhara 20 2007 and2012landscapemetrics of9BMR2057developmentzones Figure 5: of terms in different is EA1 of composition spatial EAC, with compared hand, other the On density. edge and patch in average quite and patch domination single of terms in small quite is area This (10.03). average regional the than lower is least and the changed EA1 of score LPI the region, composition characteristics. On the east side of the 2057 BMR development zones the have unique spatial from derived areas study nine All 5) (Figure characteristics. landscape own its has zone Each The whole BMR landscape has not changed equally. land-use classes. of terms and other land-use between industrial relationships in change no also but class, the of size in change no only not is there that means It 2012, and 2007 between changed has land industrial of metric no data, raw the of revisions several After metric. diversity in decreased but increased also is village urban of metrics contrast of score the land, decreased only 5.45%. The same as the agricultural is IJI but 33.38% to % 25.25 increased are metrics and 58%. For the BMR agricultural land, all contrast 49% to expanded area urbanized density medium In contrast, urban villages or gated communities and PLAND, this metrics had been decreased to 574%. NP, PD, LPI, LSI, PARA, and CWED. Especially for PLAND, CA, metrics: class the of many in declined declined. From 8 in 14 metrics, the BMR Agri-villages and villages agricultural land-use, had rural a pattern of that significantly mix close a with area the or land, village agricultural the 2012, and 2007 Referring to the study of landscape change between Town istheareawhereIJIhighest. and City or landscape urbanized density medium metric, diversity the For number. edge-contrast in score highest the significantly has land industrial Komgrij Thanapet/Shiann-FarKung second highest PLAND is 71.78% in EA1 but LPI of WA1 and WA1 also has the highest LPI, 77.15%. The 2007, the highest PLAND of agri- land is 78.88% in In 4) (Table study. the of purpose significant a is the landscape composition of urban agriculture lands dominated by agricultural land (Agri-land), revealing 50% than more is landscape BMR Because in landscapeconfiguration. in many metrics. These affect the significant changes areas like MD and WA1 show recognizable changes change in terms of landscape shape complexity, the decreased in MD. Even though there is no significant dramatically is AREA_MN The ELD1. in increased significantly it but WA1 in decreased dramatically also LPI The zones. different the among change significant a generated landscape which indicate could that metrics the is LPI metrics, composition Referring to the changed percentage of all landscape decreased. LPI and AREA_MN the but percent 23 about increased is density patch landscape, BMR of time. (Figure 6) For an overall picture of the whole period particular a in landscape each of characters unique the reflect also composition of patterns changed the landscape, each of characteristics the represent composition spatial does only Not with others characteristics spatial same the shares that area quantity of spatial composition, there is no particular of ED and PD but low in LSI and LPI. Based on the number high the in character unique a has WAC2 However, area. this dominate patches agricultural a very high number in LPI. It means that some large also has its own spatial character. This WA1 area has of EA1 is simpler than EAC. At the same time, WA1 determine differentiation. The ecological landscape PD and ED. These are significant factors of study to 2007. Therefore, the changing pattern of agri-land of pattern changing the Therefore, 2007. in 23.29% only EI1, in agri-land of percentage small despite 14.48% increased is EI1 in agri-land the Only area). conservation WAC2(Agricultural in zone is decreased, such as 6.02% in WLD2 or even 4.23% each study in ofagri-land Most 7) figure (See: MD. in % 8.82 is agri-land of rate deceasing recognizably most The %. 2.42 to deceased is land agri- of picture overall the 2012, to 2007 From high percentageofagriculturalpatchdensity. PAFRAC. At the same time, WAC has a significantly or low score in any shape complex metrics, LSI and high noticeably a has module study complexity,no EA1 is significantly low, only 5.74%. In term of shape Table 4:Classmetricsof Agricultural LandsinBMRand9studyareas(2057-BMRdevelopmentzones) Percentage oflandscape-metricchangebetween2007and2012in9studyareas Figure 6: Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape mn ar-ace i M.Te ae s n the in as same The MD. in agri-patches among distance the as such distribution, equal of terms in ENN_SD. High ENN_MN score could be unreliable more is ENN_MN More openness. less or isolation BMR are close to one another,- thus meaning less the in patches agriculture meters, 280 to 125 from only figures, ENN_MN to According recognize. to AREA_MN score). The change of ENN_MN is hard 2012 are bigger than those in 2007 (this is related to big pieces of land. In EI1, the agricultural patches in to say that agri-land in EI1 has increased in terms of possible is It EI1. in except increased have zones study all in agri-lands of PD and NP correlation. positive noticeably a have PD and NP of changes The zones. other from different noticeably is EI1

Nakhara 21 Nakhara 22 area of one landscape, the areas in the case study case the in areas the landscape, one of area based onaratio between edgelength andthe whole in positive proportion. Because CWED is calculated between TECI and CWED in the class correlationmetrics is not The level. landscape the at CWED and TECI between correlations positive illustrate also graphs the Moreover, IJI. and SHDI between correlations positive 8 illustrate figure in graphs three first The level. class at diversity the measure for landscape diversity, but SHDI is not designed to levels because even SHDI is a well-known indicator class and landscape both for configuration spatial study selects IJI for studying the diversity pattern of The 2012. and 2007 of plans development BMR 2057 the on based study of areas nine and 2012 and 2007, 2001, in landscape BMR the of picture whole the comparing metrics landscape show left on the graphs three first The CWED). and TECI dissimilarity, (or metrics contrast two between and diversity indices (SHDI X 50), two aggregation index between (IJI), correlations all shows 8 Figure The (TECI and CWED) to study the Metricspatterns of conflict correlation. edge and (SHDI) index diversity approach of the study. significant This a study chose to is compare metrics diversity of change the on Based on Landscape diversity of the BMR, observing change becomesthemostrecognizableindicator. LPI landscape, the in patch largest the Observing a dominant patch or modified into a patchier pattern. or classes are transformed into a unified pattern with because the LPI change displays how oflandscapethe landscape groups the signifies simply metrics landscape metrics, the change pattern of LPI in class Percentage ofclass-metricchangebetween2007and2012inBMR9studyareas Figure 7: Komgrij Thanapet/Shiann-FarKung have thelowestscoreofIJI. to opportunity more is there high, significantly or indicate that when TECI score becomes the highest three. top the also to could rises it value Therefore, TECI when decreased dramatically are scores IJI correlates to the lowest IJI score. In six of the cases, of 10 area cases, the highest TECI score obviously strongly in the study of K module. (Figure appears 10) In also 9 out IJI and TECI between correlation could be decreased to the lowest point. The negative become significantly high or the highest, the IJI score score of TECI. It is highly possible when TECI scores highest the to related always is IJI of score lowest the 14, in cases 13 of that illustrates also 9 figure study. of othermodules in displayed is obviously The correlation negative this Furthermore, score. TECI highest the with associated always is scores IJI a negative correlation. In all cases one of the lowest show that the relationship between TECI and IJI has cases 14 of out 7 numbers), contrast edge highest first (the TECI of number highest last three the on Based IJI. and TECI of numbers three last the on focusing details 9 illustrates figure IJI, and TECI between correlation the 8, figure the in presented data Unlike contrast. edge and diversity between correlation the investigate to industry, and town, and city village, village, and agriculture agriculture, The study choose only five major land-use classes,- both landscapesandclasslevels. for IJI with compare to variation contrast-edge for Therefore, the study chose TECI as a major metrics do not indicate the size of all landscapes to be equal. figure 8) classes (Extrudedthelastthreenumbersfromgraphsin IJI, BMRand5land-use CWED, andTECIofthewhole Figure 9: graphs ontheleftofredline)and9studyareas(graphsright three first (the BMR whole the in level landscape at 50 x SHDI and IJI between CWED, and TECI between Correlation Figure 8: Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape

Nakhara 23 Nakhara 24 2007 and2012landscapemetricsofK-module7areas Figure 11: IJI, CWED,andTECIofagriculturalland-usein7areasonKarnchanaphisakeringroad(K-module) Figure 10: Komgrij Thanapet/Shiann-FarKung CONTAG, SHDI, PAFRAC, andPARA_MN. metrics: shape and diversity in stable quite are and most of areas have significantly increasedK1, in CWED for Except LPI. and ED metrics, two between change of percentage identical have areas studied the of Most LPI. ED, PD, in low significantly is and LPI in change of percentage high a has K1 time, in percentages same AREA_MN. decreased the At greatly has but score PD in increased significantly IJI changed dramatically only in the K6 area. K4 has percentage of in change in specific pattern indices. Obviously, unique a has area studied each 12), (Figure analysis percentage change to According change. landscape of pattern same the have to seem they and configuration and composition of patterns identical have on road modules ring Karnchanphisek landscape 7 of out 6 Even SHDI. This patternisobviously uniquein2012. and IJI both in lowest but LPI- and CWED, TECI, It has highest figures in many indicators- CONTAG, K6. Figure 11 illustrates that K6 has a unique pattern. area the for except configuration and composition landscape of pattern same the almost have K7, to and 2012, whole groups of sub-landscapes, from K1 According to the comparative graphs between 2007 Percentage oflandscape-metricchangetheareasinKstudymodule Figure 12: Spatial CompositionandConfigurationChangesintheBangkokMetropolitanRegionLandscape BMR in term of landscape ecology in 3-dimensions: composition and configuration. This study realizes the spatial patterns and significant changes in landscape a powerful application that could reveal and quantify and land-cover. The research considers Fragstats as piece of landscape with complex diversity in land-use this research considers Bangkok and vicinities as one Different from the approach of Nagasawa and et al., vicinities. (Nagasawa, Durina, & Patanakanog, 2011) the from different significantly was landscape Bangkok the that was conclusion Their vicinities. five and city Bangkok of boundaries administration land-use and made observations based on the 2009 of details the on focused study The bodies. water and vegetation, built-up, - classifications; three only compared They SHDI and Index), (Contagion CONTAG Index), (Connect CONNECT ENN, Index), (Proximity PROX PD, NP, metrics; during 1994, 2000 and 2009 with seven landscape made were that changes the discussed others and 2011, based on the same LDD database, Nagasawa Fragstats metrics to applies study the that change of the research BMR. In first the not is study This Findings and Conclusion

Nakhara 25 Nakhara 26 class-aggregation metrics(IJI). negative and (SHDI) metrics diversity landscape appears to be a positive relationship between It decreased. slightly are SHDI and IJI as such number of aggregation metrics and the diversity metrics 2007, in than complex more comparatively is whol the though Even when thediversityislost. Higher dissimilarityisillustrated patch. aggregated more a become now has it settlement was the target area of low-density gated community K1 Whereas, settlement. community gated low- density of area target the now is K6 peri-urban. the areas are not in BMA but in the city expansion area, significantly. These areas are K6 and K1. These two where spatial composition and configuration change ring road illustrates that there are two critical areas Kanchanaphisek the of study the infrastructure, by influenced landscape ecological of change the For metrics exceptIJI. all in increased significantly area community gated or village urban the landscape, BMR whole the with compared 2012, and 2007 during Therefore, decreased. dramatically was Residences” Density “Agricultural Land Mixed with Rural Villages or Low as class land-use transition usage. The in changes indicated landscape BMR whole the in class use For the detail of landscape composition, each land- complexity and the number of patches are increased. the sameareaandattime,thusshape aggregation patterns lead the same land-use theclass to because diversity, less with but complex, is landscape BMR the of tendency The aggregated. is patch class same the that reveals class, land agri- of ENN_MN decreased the from observed be could which patches, same-class the of score ENN declined The diversity. and patterns aggregation represent not could metrics shape and metrics area the on based landscape the of complexity the But 2007. in than complex more is 2012 in BMR of landscape whole the that noted be could it 2012, and 2007 during LPI decreased the and LSI and PD, NP, of number increased the to According complex thanin2007. landscape ofBMRin2012ismore Not onlytheBMA,whole Komgrij Thanapet/Shiann-FarKung e landscape of BMR in 2012 in BMR of landscape e

reveal BMRLULCC. Fragstats metricsworktogetherto with NP andPD. be the cause of change in class structure- indicated significant change indicator. The declined LPI could a as itself presents agri-land of LPI the zones, nine of level landscape the at happened what to Similar the whole BMR landscape and that of many zones. percentage of agri-land, it dominated the change of highest the to According zone. industrial east the one, for except general, in declined obviously has agri-land of PLAND the BMR, of 50% than more occupies it though even land-use, agricultural BMR the of patterns spatial and change the For observe thechangepattern. to data limited 3) and pattern, adaptation various 2) different background of landscape caused by the three factors: 1) improper zoning boundary defining, These unpredictable patterns could be due to these zone. agricultural the of that to changes of pattern landscape similar a have may zone industrial the time, same east. the the At in zones all of changes the to similar not are and landscape, of patterns locations. The west agricultural zones have different among similar development zones and the regional expected pattern changing the in correlation no is there that show zones nine all of patterns change significant changes of shape and area metrics. The the has (MD) zone urban density medium the and in LPI, change significant most the has (WA1) I zone agricultural west The zones. nine the among LPI, PD and ED indicate the different characteristics differenceless However,LSI. the in of changes the metrics PD, ED, basicLPI, and LSI, indicates 4 that there is only with plan, development BMR 2057 Comparisons among nine zones classified following agricultural conservationzone(WAC). west agriculture land 1 (WA1) are the and the west rural and areas contrast critical most The conflict. gain moredissimilarityandlead to future land-use to possible is it degrees, significant in diversity its loses landscape the when that said be could it modules) also have the same pattern. Therefore, (K road Karnchanaphisek the on cases landscape 10 of out 9 and lowest the is IJI the when highest is the zones from thenine agri-lands of 7out14 TECI the that obvious is It found. is IJI lowest the when score TECI highest the find to opportunities more are there that illustrates levels class and landscape the on analysis hand, other the On Planning. Ecological Concept and Metrics in LandscapeSustainable Landscape Applying (2002). J. Ahern, & B., A. Leitao, gravity modeling. and theory on graph based Identification conservation: biodiversity for development network space green Urban (2010).Y. Zong, & N., Nakagoshi, H., Yin, F., Kong, Journal ofPopulationResearch,19 REGIONS. MEGA-URBAN OF GROWTH THE AND Jones, G. W. (2002). SOUTHEAST ASIAN URBANIZATION Environment andUrbanSystems,30 metrics. landscape and images sensing remote multi-stage using sprawl urban (2006).Characterizing K. Underhill, & W., R. 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