V N U Journal of Science, E arth Sciences 28 (2012) 251-263
Spatio-temporal dynamics and evolution o f landscape pattern in coastal areas o f central region, Vietnam
M. Kappas'’*, Nguyen Hoang Khanh Linh'’^
^Dept. o f Cartography, GĨS & Rem ote Sensing, Georg-August-University Goettingen, Goldschmidtstr 5, 37077 Goettingen, Germany
^Faculty o f Land Resources ẵ. Agricultural Environment, H ue University o f Agriculture & Forestry, Ỉ02 Phung Hung, Hue City, Vietnam
Received 05 October 2012;
Revised 26 Octobcr 2012; accepted 02 December 2012
A b stract. Studying temporal changes o f land use and land cover from satellite images has been conducted in Vietnam several years. However, few studies have been done to consider seriously the changes and landscape fragmentation, especially in coastal region, one o f the ecologically vulnerable regions due to the intensive human activities and urbanization processes. Hence, analyzing the changes o f landscape pattern helps revealing the interactions between anthropogenic factors and ứie environment, through which planning actions could be effectively supported. The present study aimed to examine these changes in the suưoundings o f Da Nang City, Vietnam from 1979 to 2009 based multi-temporal imagery viz. LANDSAT MSS, TM, ETM +, and ASTER satellite images. The IR-MAD (iteratively re-weighted M ultivariate Alteration Detection) transformation approach was employed for processing. Land cover change maps with six classes including agricultural land, urban, baưen land, forest, shrub and water body were created by the supervised classification method based on maximum likelihood algorithm. Post-classification comparison was chosen as change detection method for four periods as 1979-1996, 1996-2003, 2003-2009, and 1979-2009. From which key landscape indices were applied by using FRAGSTATS software. The results showed that during the whole study period, there was a notable decrease o f forest, shrub, agricultural land and baư en land while urban areas expanded dramatically. Further spatial analysis by using landscape metrics underlined the evidence of changes in landscape characteristics with an increase in values o f num ber o f patches and patch density while the value o f m ean patch size decreased during the span o f 30 years which indicated landscapes o f Da Nang city have been becoming more fragmented and more heterogeneous.
Keywords: landscape pattern, change detection, coastal region, Vietnam.
Ỉ. Introduction urbanization is a global phenom enon and is
expected to continue for the n ext decades.
As stated in C om petitive C ities in the A ccording to the U nited N ations, roughly h a lf G lobal Econom y [1] and State o f the W o rld ’s o f the w o rld ’s population lives in urban areas, Cities 2008/2009: H arm onious C ities [2], and in 2030 it w ill be reached at 60% .
________ D eveloping countries are believed w here the
Coưesponding author: urbanization grow th sừ ongly happens up to
E-mail: mkappas@uni-goettingen.de
251
252 M. Kappas, N.H.K. Link / V N U Journal of Science, Earth Sciences 28 (2012) 25Ĩ-263
2030 [3]. U rban areas concentrate not only people but also econom ic density and productivity [4]. This is often the reasons o f changing in lifestyles, high consum ption o f energy, fransportation, infrasừiicture, and production o f w aste, etc. [5-12]. U rbanization is believed one o f the m o st prevalent anthropogenic causes o f the losing arable land, devastating habitats, and the decline in natural vegetation cover [13]. As a consequence, rural areas have been converted into urban areas w ith an unprecedented rate and m aking a noted effect on the natural functioning o f ecosystem s [14]. Consequently, a profound understanding o f land use change is very im portant to have a prop er land use planning and sustainable developm ent policies [15].
A ccording to M yint and W ang [16], such a sustainable urban developm ent m ust be sum m arized from num erous decisions, which ex ừ acteđ based on huge data sources, viz.
physical, biological and social param eters o f urban areas in the continued specừ um o f spatial and tem poral dom ains. T herefore, to understand urban land-use and land cover change (LU LC) and to predict the change o f L U L C in future, it is im portant to have an effective spatial dynam ic tool. N ow adays, rem ote sensing technologies have proven its capacity in providing accurate and tim ely inform ation on the geographic disừ ibu tion o f land use, especially for region areas [17]. W ith the support o f G eographical Inform ation System s (G IS), satellite im ages can be used effectively for estim ating and analyzing changes and L U L C trends [18].
D ue to the fact that the rapid LU LC change o f one certain area is considered as the driving force o f environm ental and /o r ecological changes, w hich is continuously transform ing landscape pattern, thereby a need for
com prehensive assessing and analyzing the change in landscape at broad scales is required.
Im portantly, understanding the changes in spatial contribution o f landscape p attern helps revealing the critical im plication o f com plex relationship betw een anthropogenic factors and environm ent [19]. T o describe fragm entation and spatial disừ ib utio n, a range o f landscape m eừ ics w as calculated for each land use/cover class from satellite classification results by FR A G STA TS [20].
The Earth's coastal zone is know n as home o f diverse ecosystem s, such as estuaries, sea- grass, coral reefs, lagoons, bays, tidal flats, e tc .... It plays a crucial part for socio
econom ic developm ent and national security.
This zone is quite sensitive and vulnerable because o f hum an developm ent activities, especially, the tropical coast. As consequcnces, these activities causes loses o f living environm ent o f sea species, degradation o f drinking w ater, changes o f hydrological cycles, depletion o f coastal resources and m any other im pacts to the global clim ate change. Therefore, the m anagem ent o f m arine and coastal zone has particularly received great attention from m anagers as w ell as scientists all around the world. The urgent dem ands should be set as lop national sừ ategic m issions and should be caư ied out w ith scientific fundam entals.
A fter the adoption o f the D oimoi (R enovation) p olicy in econom y o f the national assem bly since 1986, D a N ang city has developed in m any aspects. In addition, it was separated from Q uang N am Province m 1997 and has officially becom e an adm inistration unit that directly belongs to the governm ent.
Since then, D a N ang city has asserted as the im portant position at nation level and the crucial factor o f the key area econom y o f Central region. This has caused the incessant
M. Kappas, N.H.K. Link / V N U Journal of Science, Earth Sciences 28 (2012) 251-263 253
land use/cover change in D a N ang for over past 20 years. Through exploring the land use map extracted from satellite data o f different periods, the aims o f the present study w ere to detect, quantify and characterize the changes o f land use/cover and landscape fragm entation in Da N an g city.
2. S tudy area
D a N ang city is located in Central region o f V iet N atn, betw een the 15°55’ 19” to 16°13’20 ”N and 107°49’ 11” to 108°20’20”E (F igure 1). It is a long-stretching narrow region and w ell know n as a dynam ic city o f the Key E conom ic Zone in central V iet N am . The area consists o f hiils and m ountains in the northw est and the Eastern Sea in the east. The altitude varies from 400 m eters to 1,524 m eters above
sea level; next to is the upland with low m ountains and the delta takes 'Á areas in the southeast; it covers an area o f 1,283.42 square kilom eters, including H oang Sa archipelago district o f 305 square kilom eters.
D a N ang city has typical tropical m onsoon clim ate. The average annual tem perature is about
26°c,
average rainfall is about 2,505 mm per year and average hum idity is 83.4%. T here are two main seasons annually: the w et (A ugust-D ecem ber) and the dry (January-July).In 2009, the total population is about 887,070 and the population density is 906.7 persons per square kilom eters. D a N ang city is know n as one o f the m ost densely populated and urbanized area in V ietnam . W ith the econom y developm ent and population increasing, the local LULC in Da N ang city has changed seriously.
Figure 1. Location o f Da Nang city in Vietnam.
2 5 4 M. Kappas, N.H.K. Link / V N U journal o f Science, Earth Sciences 28 (2012) 251-263
3. D ata and m ethods
3.1. D ata so u rces and Im age p rep ro cessin g L A N D S A T and A S T E R satelliteim ages w ere chosen for this study. The follow ing criteria w ere considered for choosing proper data: (1) the im ages should be long tim e enough for detecting th e land use change; (2) study area should not h av e cloud cover. U nfortunately, the study area is located near coastal. D ue to the influence o f clim ate, there are not m any data satisfied b o th conditions. T he im ages alw ays have som e th ick cloud cover or haze. In addition, the study area is not entirely contained w ithin one scene o f L A N D S A T either A STER.
T herefore, h av in g acquisition im ages near anniversary d ates for changing detection as Jensen m entioned [21] w as unavailable. In this study, three periods o f satellite im ages were selected to classify study area: LA N D SA T-3 M SS July 24, 1979; LA N D SA T-7 ETM + M arch 04 and A pril 14, 2003 (dow nload free at h ttp ://earth ex p lo rer. usgs.gov/ and h ttp ://gloviS.usgs.gov/); and A S T E R A pril 02, 2009. T he details o f data w ere described in T able 1. F or th is study, the reference data were also used, included: (1) topographic m ap at scale o f 1/50.000 conducted in 2001; and (2) land use m aps at scale o f 1/25.000 conducted in 1997, 2003 an d 2010.
B ecause L A N D S A T and A ST E R im agery w ere collected at level IT and IB respectively,
im ages w ere acquired at different spatial resolution and pro jectio ns. T h erefo re, all im ages w ere first rectifie d to U niversal T ransverse M ercator (U T M ) coo rdin ate system , D atum W G S 84, Zone 48 N o rth for m atching the geographic pro jection o f th e referen ce data.
Im ages w ere also co -reg istered to g eth er w ithin 25 well distributed G C P s (ground control points) and polynom ial Is d by m eans o f O rthoEngine provided b y P C I G eom atica 10.3 software. RM S < 0.5 w as receiv ed . In addition, N earest N eighbour resam p lin g w as set for not changing heavily the rad io m etric characteristic o f image.
In this study, the iterativ ely re-w eighted
multivariate alteration detection (IR-
M AD ) fransfonnation w as u sed for autom atic radiom etric n o m a liz a tio n for all im ages by m eans o f E N V I 4.7 so ftw are; see [22-24J.
A ST ER 02/04/2009 w as ch o sen as reference image. H ow ever, this im age d o es not cov er all the region o f study area, th erefo re a subset o f 1800 X 1100 pixels w ith 30m spatial resolution including 968.17 square k ilo m eters w as created for all im ages for fu rth er studying. This territory w as chosen to ensu re the specific study area w as in the an alysis im age. B esides the requirem ent o f the sam e d im en sio n, im ages m ust have the sam e spectral reso lu tion . H ence, the com posite o f stand ard false colours was used for this study: L A N D S A T M SS (754);
L A N D SA T T M /E T M + (4 32); A S T E R (321).
geom etric co rrection do n ot require. H ow ever,
Table 1. Characteristics o f satellite data used in study area
T ype o f sen so r Spatial resolution (m) B and D ate P a th Row A v erag e cloud coverage (% )
LANDSAT-3 M SS 68 4-8 July 24, 1979 134 49 20
LANDSAT-7 ETM + 30 1-5,7 M arch 04, 2003 125 49 34.65 *
30 1-5,7 April 14, 2003 124 49 0.34
ASTER 15 1-3 April 02, 2009 - - 4
Although the average cloud coverage of LANDSAT-7 ETM+ is very high, there is almost no cloud in study area at that time.
M . Kappas, N.H.K. Linh / V N Ư Journnl o f Science, Earth Scienccs 28 (2012) 251-263 255
3.2. L U L C c la ssific a tio n a n d C h a n g e d etectio n Six land u se/co v e r classes w ere defined for image classification based on the m odified A nderson land use/co v er schem e level I [25], included; (1) w ater, (2) forest, (3) shrub, (4) agriculture, (5) barren and (6) urban land.
A nderson classificatio n schem e w as chosen because o f the m a jo r land use/cover classes using im ages w ith differences in spatial resolution, w h ich are L A N D S A T M SS, LA N D SA T T M , L A N D S A T ETM + and ASTER. S u p erv ised classification using m axim um lik elih o o d approach in EN V I 4.7 was individually ap p lied for each im age o f study area to classify land use/cover. M axim um likelihood alg o rith m w as p refeư ed because this rule is con sidered to have accurate results because it h as m o re accurate results than other algorithm s [26-28].
B ecause o f v ario u s im age acquisition dates, training areas for the im ages o f the years 1979, 1996, 2003 and 2009 w ere different during the classification. In addition, the iTaining areas w ere verified by references data. A s the next step, post-classification com parison change detection alg o rith m w as selected to detect changes in L U L C from 1979 to 2009 in study area in order to m inim ize the problem in radiom etric calib ratio n o f im agery o f two different dates. F o r com parison o f the
classification results o f two dates, a change detection m atrix w as created based on pixel-by- pixel [21]. T hereby, each type o f from -to LU LC change is identified.
3.3. L a n d sc a p e fra g m e n ta tio n
For quantifying landscape pattern and landscape fragm entation, FR A G S T A T S w as applied because this spatial statistic prog ram offers a com prehensive choice o f landscape m etrics. This program w as created by decision maker, forest m anager and ecologists therefore it is appropriate for analyzing landscape fragm entation or describing characteristics o f landscape, com ponents o f those landscapes [29]. H ow ever, landscape pattern s w ere com plicated; hencc, to clarify the relationship o f spatial pattern and process it cannot use single m etric alone [19, 30].
B ased on the scale o f study area (i.e. the district level) and its characteristic as w ell, six related landscape m etrics w ere selected: (1) Percentage o f landscape (PLA N D ), (2) N um ber o f patches (N P), (3) Largest patch index (LPI), (4) M ean patch area (A R E A _M N ), (5) Patch density (PD ), and (6) P roxim ity index (PR O X _M N ). A b rie f description o f those landscape m etrics used in study w as given in Table 2. T hose descriptions could be also found at u ser’s guide o f FR A G ST A T S™ [31].
Table 2. Landscape pattern m eừics description [29, 31].
In dex D escription U nit R ange
PLAND
NP
P ercentage o f landscape-equals the sum o f the areas (m^) o f all patches o f the corresponding patch type, divided by total landscape area (m^), multiplied by 100 to convert to a percentage
N um ber o f patches-equals the number o f patches of the coưesponding patch type (class).
Largest patch index-equals the area (m^) o f the largest patch o f
percent
none
0<PLAND<100
NP>1, no limit LPI the corresponding patch type divided by total landscape area
(m ), m ultiplied by 100 to convert to a percentage
percent 0<LPI<100
256 M. Kappas, N.H.K. Link / VNU journal of Science, Earth Sciences 28 (2012) 251-263
Index D escription U nit R ange
AREA_M N Mean patch area-Average size o f patches hectares AREA_MN>0, no limit PD
Patch density equals the num ber o f patches o f the
coưesponding patch type divided by total landscape area (m),
num ber per
100 PD >0
no limit
PROX_M N
multiplied by 10,000 and 100 (to convert to 100 hectares).
Mean proxim ity equals the sum o f patch area (m^) divided by the nearest edge-to-edge distance squared (m^) between the patch and the focal patch o f all patches of the corresponding patch type whose edges are within a specified distance(m) o f the
focal patch; Average proxim ity index for all patches in a class
hectares
meters PROX_MN>0, no limit
4. R esults and discussion 4.1. L a n d U se/ C over C hanges
B efore doing any other interpretations, th em atic LU LC m aps (1979, 1996, 2003 and 2009) w ere assessed their accuracy through four m easurable m eans o f error m atrix: overall accuracy, p rod ucer’s accuracy, u se r’s accuracy and K appa coefficient. A total o f 300 sfratified ran do m pixels w as taken for each LU LC m ap and then checked w ith reference data.
A ccording to the accuracy assessm ent results o f classified maps, the overall accuracy for L A N D S A T M SS 1979, L A N D S A T ETM + 2003 and A ST ER 2009 w as 92.15% , 80.33% , 84.44% and 89.00% respectively; the K appa C oefficient o f those m aps reached at 0.9021, 0.6921, 0.7534 and 0.8005, respectively. The results showed that LU LC m ap derived from A S T E R has higher accuracy than the others.
T his could be explained by the better spatial, specừal and radiometoic resolution o f ASTER data.
T h e LU LC m aps o f study area w ere generated for all four years (Figure 2) and
classification area statistics w ere sum m arized in Table 3. T he classified areas w ere m easured by m ultiplying the n um b er o f pixel w ith spatial resolution o f rem ote data (i.e. 30 m eters), in w hich the pixel nu m ber w as determ ined after applying post-classification analysis. And then changes w ere defined based on the difference o f pixel num ber betw een tw o dates. Based on Table 3, forest and urban areas w ere the dom inant LU LC classes m spatial distribution pattern. A ccordingly, forest area w as counted for about 64.0% , 60.0% , 61.4% and 59.8% o f the total area in 1979, 1996, 2003 and 2009 respectively; m eanw hile urban area w as occupied 6.5% , 8.0% , 12% and 17.9% o f the total area in 1979, 1996, 2003 and 2009 respectively. T h e surface w ater body covers about 2.5Vo, 2.6% , 2.9% and 3.1% o f the total region study in 1979, 1996, 2003 and 2009, respectively. The results also show ed that from 1979 to 2009 LU LC units under shrub, agricultiưe and barren decreased from 10.1% to 9.9% , 12.4% to 7.5% and 4.5% to 1.8%, respectively.
M. Kappas, N.H.K. Linh / V N U Journal of Science, Earth Sciences 28 (2072) 257-263 257
Legend
i m m water H urban
m
forest^ 9 shrub ,__ _! barren
agncuiture
Figure 2. Land use/cover maps o f Da Nang city area.
Table 3. Results o f and use/cover classification for 1979, 1996, 2003 and 2009 images
LU LC class 1979 1996 2003 2009
A rea (ha) (% ) A rea (ha) (% ) A rea (ha) (% ) A rea (ha) (% )
Agriculture 12048.0 /2.4 10416,7 10.8 8118.1 8.4 7294.7 7.5
Barren 4312.2 4.5 3680.9 3.8 24ỉ,1.2 2.6 1708.9 1.8
Urban 6315.3 6.5 7791.5 8.0 11630.0 12.0 17298.5 17.9
Forest 61972.0 64.0 58126.7 60.0 59467.1 61.4 57936.2 59.8
Shrub 9785.2 10.1 14253.2 14.7 12335.9 12.7 9575.8 9.9
W ater 2384.6 2.5 2548.3 2.6 2779.0 2.9 3003.6 Ì .Ì
Total 96817.2 100 96817.2 100.0 96817.2 100 96817.7 100
To provide a further com prehensive calculation in losing and gaining am ong the six LU LC classes, the from -to change m afrix o f land use/cover in D a N ang city w ere created in three intervals, 1979-1996, 1996-2003, 2003-
2009 and 1979-2009 (Table 4). In cross tabulation, unchanged pixels w ere located along the m ajor diagonal o f the m afrix w hile conversion values o f classes w ere aư an g ed in descending order. As can be seen from the
258 M . Kappas, N.H.K. Link / V N U Journal of Science, Earth Sciences 28 (2012) 251-263
T ables 4, there w ere sm all differences o f area coverage o f a particu lar class because o f used different spatial resolutions for calculating L U LC change from 2003 to 2009 (e.g., forest coverage in 2009 is 57936.2 hectares in T able 3 and 57935.79 h ectares in T able 4c). It resulted because o f using different spatial resolutions for calculating L U L C change from 1979 to 2009.
In fact, the 2009 A S T E R im age w as re-sam pled to a spatial reso lu tion o f 30 m eters.
D uring the first period (1979-1996), results show ed that forest, agriculture, and barren decreased strongly w hile urban area, shrub and w ater body increased, notably the raising o f shrub area. T ab le 4(a) indicated that the expansion o f shrub area w as the m ost dram atic changes in the region w hereas forest area decreased, w hich w as the result o f deforestation
m ainly caused by the increasing dem and o f tim ber products. U rban area grew up ju st
1476.2 hectares, representing 13.4% o f net increase o f urban area.
In 1990, the policy no tim ber exploitation o f natural forests w as prom ulgated by governm ent, w hich could help to continue supplying m aterials for tim bers and paper industry. C onsequently, forestry productions w ere exploited from forest plantation [32], Therefore, in the second period (1996-2003) forest cover extent had been slightly increased by reforestation program s w ith 1340.01 hectares. As can be seen from Table 4b, urban area prom ptly grew up 3838.5 hectares after separating from Q uang N am province and becam e a cenfrally governed city.
Table 4. Land use/ land cover ừansform ation mafrices o f study area from 1979 to 2009
(Unit: hectares) 1979
Agriculture B aưen Urban Forest Shrub Water 1996 Total
Agriculture 2910.96 1062.45 202,32 3865.05 2238.21 125.1 10416.69
Barren 657.81 481.5 573.84 986.49 832,23 142.56 3680.91
Urban 486.54 834.48 4280.67 1408.77 577.62 189 7791.48
Forest 2797.47 711.99 324,81 52197.03 1878.3 118.62 58126.77
Shrub 5016.06 984.69 655.65 3294.27 4084.56 201.69 14253.21
Water 179.19 237.06 97.02 220.41 174.24 1607.58 2548.26
1979 Total 12048.03 4312.17 6314.85 61972.02 9785.16 2384.55 Change 1979-1996 -1631.34 -631.26 1476.63 -3845.25 4468.05 163.71
(a) 1979-1996
2003 1996
Agriculture Barren Urban Forest Shrub W ater 2003 Total
Agriculture 2244.51 282.87 575.01 2165.76 2782.44 61.2 8118.09
Barren 325.98 532.08 414.09 360.45 803.7 44.91 2487.15
Urban 1127,07 985.5 5867.1 1090.71 2187.63 310,86 11629.98
Forest 4389.66 538.29 120.78 51701.94 2610.18 34.29 59466.78
Shrub 2235.96 1169.46 578.43 2572.11 5698.53 74.79 12335.94
W ater 80.91 166.23 221.67 137.25 154.44 1989.45 2778.84
1996 Total 10416.69 3680.91 7791,48 58126.77 14253.21 2548.26 Change 1996-2003 -2298.6 - 1193.76 3838.5 1340.01 -1917.27 230.58
(b) 1996-2003
M. Knppns, N.H.K. Link / V N U joiirm l o f Science, Earth Sciences 28 (20Ĩ2) 251-263 259
2009 2003
Agriculture B aưen Urban Forest Shrub Water 2009Total Agriculture
Baưen Urban Forest Shrub Water 2003 Total
1858.68 86.76 3188.7
1036.17 1833.21 108.27 8118.09 Change 2003-2009 -823.41
177.66 121.86 1188.27 231.93 656.01 105.48 2487.15 -778.23
711 148.14 9025.29 414.99 808.56 460.89
11629.98 5668.56
2880.63 860.58 739.35 52503.66 2364.21 46.71 59466.78 -1530.99
1645.38 464.04 2673.81 3556.26 3851.46 138.33 12335.94 -2760.12
15.03 24.93 458.55 95.85 51.3 2104.29 2778.84 224.73
7294.68 1708.92 17298.54 57935,79 9575,82 3003.57
(c) 2003-2009 2009
Agriculture B aưen Urban Forest Shrub Water 1979 Total
1979
Agriculture B aưen Urban Forest Shrub Water 2009 Total 1779.21
353.07 2975.04 3787,38 2895.48 257.85
12048,03 Change 1979-2009 -4753.35
991.26 78.3
1933.56 227.52 747.45 334 08 4312.17 -2603.25
110.79 91.8 5096.7 221.58 430.47 182.97 6314.85 10983.69
2394.99 933.93 3898.26 51584.22 2834.19 326.43 61972.02 -4036.23
1950.3 240.48 2789.37
1928.79 2589.48 286.74 9785.16 -209.34
61.83 8,73 581.04 89.37 67.68 1575.9 2384.55 619.02
7294.68 1708.92 17298.54 57935.79 9575.82 3003.57
(d) 1979-2009
W hich w as 35% o f n et increase o f urban area. W hereas from 1996 to 2003, w ithin ju st seven years, agriculture area reduced 2298.6 hectares, thus representing o f 19.1%.
In the third period, from 2003 to 2009, forest area decreased once again (1.6% o f total area in D a N ang City) due to the rapid urbanization. A griculture area reduced 823.41 hectares w ithin six years, w hich represented o f 6.8%. C onversely, urban area incessantly increased and gained 5668.5 hectares, w hich contributed 51.6% to net increase o f urban area, experienced a rem arkable change o f urban area w ith a rapid scale.
A ccording to Table 4d, for 30 years, although forest extent fluctuated variously in d ifferent periods, this area decreased in general.
R esults show ed that the forest area lost 10387.8 hectares o f Its 1979 area to other classes, in
w hich 37.5% (3898.26 hectares) converted to urban, 27.3% (2834.19 hectares) to shrub and 23.1% (2394.99 hectares) to agriculture. From 1979 to 2009, agriculture area strongly decreased 4753.35 hectares (Table 5d), representing a net decrease o f 39.5% , the change o f agriculture area altered considerably in different periods o f tim e. T h e loss o f agriculture from 1979 to 2009 w as m ainly caused by the encroachm ent o f urban and forestation. A ccording to Table 5d, agriculture area lost 2975.04 hectares to urban area and 1392.39 hectares to forest, rep resen tin g 60.3%
and 29.3% o f total decrease in agriculture land use, respectively. B ased on statistic, 10983.69 hectares o f urbanized area in this p eriod w as calculated, w hich w as nearly tw ofold the coverage o f urban area in 1979, thus representing an increase o f 140% (10983.69 hectares). A nalyzing the com ponent o f the
260 M . Kappas, N,H.K. Link / V N U Journal of Science, Earth Sciences 28 (2012) 25Ĩ-263
conversion o f grow th in urban area, 33.5% was converted from forestry, 26.1% from agriculture an d 21.5% from shrub. This also resulted because o f the grow th o f econom ic after applying D oim oi policy. As can be seen in Figure 5. gross dom estic product (G D P) o f Da N ang city increased steadily from 1990 to 2009, w ith an annual grow th o f G D P o f 10.3%
(h igher than n a tio n ’s annual grow th o f GDP 7.2% ). In addition, the increase o f population in D a N ang city could be seen as another reason for urban expansion, in w hich population
increase from 679.7 thousand in 1997 to 890.5 thousand in 2009, representing an increase o f 31%. Based on Figure 3, the difference o f spatial distribution o f urban area could be clearly observed by the years. In 1979, the urban area dispersedly located along the costal line. By 2003, this area w as expanded more concentrated along coastal zone and moved tow ard Sontra peninsula. From 2003 to 2009, the urban expansion changed the direction from costal tow ard in land.
□ GDP %GDP
^ rỹ> rỹ rỹ rỹ fỹì rỹ> rỹì rỹ
Y ears
Figure 5. Gross domestic product and its growth in Da Nang city from 1990-2009.
4.2. F ragm entation A nalyses
From L U L C m aps in 1979 and 2009, three m ost changing classes (agriculture, urban and forest) were chosen to com pute spatial landscape m atrices at class level b y m eans o f FR A G ST A T S softw are (Table 5). In D a N ang city, forcsừy area presented as the dom inance
class o f landscape. T his could be identified by the largest patch index (LPI), a specific m easure used for observing the dom inance o f a land cover type. C om pared to agriculture and urban area, the largest patch index (LPI) o f forest area is highest at rate o f 29.4% and 29.5% in 1979 and 2009, respectively. T he statistic o f forestry show ed that the percentage o f landscape
M . Kappas, N.H.K. Link / V N U Journal o f Science, Earth Sciences 28 (2012) 251-263 261
(PLAND) index decreased from 36% to 33.2%
and the num ber o f patches (N P) decreased from 2,180 to 1,554 during the w hole period from 1979 to 2009. W hereas the m ean patch area index (A R EA _M N ) increased from 28.4 hectares to 38.0 hectares, w hich is supported by the increasing o f the m ean p roxim ity index (PROX _M N) from 2670.1 m etersto 17985.4 meters. In this case, those forested patches have been low er isolation and m ore contiguous in the domain o f spatial disfribution.
In regards to agriculture area during the period 1979-2009, the num ber o f patches (NP) increased from 1,240 to 3,051, the m ean patch area (A R EA _M N ) decreased from 10.0 hectares to 2.1 hectares and the m ean proxim ity (PRO X _M N ) decreased strongly from 491.2
m eters to 24.2 m eters. T hese values revealed that agriculture class in 2009 w ere m ore isolated than it in 1979.
The spatial analysis o f urban areas show ed the significant increasing o f the percentage o f landscape index (PLA N D ) from 3.7% to 10.1%, the num ber o f patches (N P) from 682 to 1771, the largest patch index (LPI) fro m 1.0% to 4.6% . T hese indexes evidenced that the expansion o f urban areas also concentrated on existent urban. Finally, the gro w th o f m ean proxim ity (PR O X _M N ) from 67.1 m eters to 1728.6 m eters and o f the patch density from 0.4 to 1.0 patches p er 100 hectares indicated that urban class distributed in landscape configuration in 2009 m ore clear th an in 1979.
Table 5. M eữics o f landscape structure for selected indices at the class level, 1979 and 2009.
Class P L A N D (% ) N P (#) L P I (% ) A R EA M N (ha) PD (#/100ha) P R O X M N (m) 1979
Agriculture 7.0 1240 2.7 10.0 0.7 491.2
Urban 3.7 682 1.0 9.2 0.4 67.1
Forestry 36.0 2180 29.4 28.4 1.3 2670.1
2009
Agriculture 3.6 3051 0.3 2.1 1.7 24.2
Urban 10.1 1771 4.6 10.2 1.0 1728.6
Forestry 33.2 1554 29.5 38.0 0.9 17985.4
5. C onclusions
By using the rem ote sensing and fractal analysisa, this paper describes the analysis o f LƯ LC and landscape change in the D a N ang city, V ietnam in the period 1979-2009. T he analysis carried out found that a notable decrease o f agriculture and forest because o f conversion to urban land during the span o f 30 years has taken place. F or further understanding, key landscape indices w ere set for three m ain classes to p erform the different changes in landscape sfructure in the
surroundings o f D a N an g city. T h e dynam ic change o f class indices revealed th e break-up o f this area into sm aller patches. H ow ever, except agriculture, patches o f forestry and urban tended to have a u niform landscape configuration. A ccordingly, urban area show ed the expansion in a concentrated w ay. The study explored the changes o f land u se/ land cover and spatial disfribution o f landscape in D a N ang city. T his w ould help the decision m aker and local authority having an overlook in th is area, from w hich strategies in land use planning could b e considered.
26 2 M. Kappas, N.H.K. Link / V N U Journal of Science, Earth Sciences 28 (2012) 251-263
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