ZNVI 4.3 software: 
Canty and Nielsen, 
s reference image. 
egion of study area, 
with 30m spatial 
1 for all images for 
) ensure the specific 
: the requirement of. 
the same spectral 
d false colours was 
Landsat TM/ETM+ 
"tion 
image classification 
over scheme level I 
ter, (2) forest, (3) 
pan land. Anderson 
of the major land 
erences in spatial 
ndsat ETM+ and 
aximum likelihood 
lied for each image 
aximum likelihood 
considered to have 
e results than other 
, 2007, Reis, 2008, 
, training areas for 
009 were different 
raining areas were 
, post-classification 
| selected to detect 
dy area in order to 
tion of imagery of 
lassification results 
s created based on 
h type of from-to 
FRAGSTATS was 
rogram offers a 
This program was 
er and ecologists 
cape fragmentation 
mponents of those 
landscape patterns 
tionship of spatial 
ric alone (Ning ef 
strict level) and its 
ape metrics Were 
- of landscape, (3) 
(5) average size of 
ximity index, (8) 
and juxtaposition 
hannon's evenness 
je metrics used in 
ions could be also 
Garigal, 2002). 
  
  
Type of sensor Spatial Band Date Path | Row Average cloud coverage 
resolution (%) 
(m) 
Landsat-3 MSS 68 4-8 July 24, 1979 134 49 20 
Landsat-7 ETM+ 30 1-5, 7 March 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). 
Table 1. Characteristics of satellite data used in study area 
  
  
Index (unit) Description 
CA (ha) Class area 
PLAND Percentage of landscape 
NP Number of patches 
The percentage of the landscape 
0 
IRI CO comprised by the largest patch 
AREA MN Average size of patches 
(ha) . . 
SHAPE MN Mean patch shape complexity weighted 
(ha) by patch area, based on shortest edge-to- 
edge distance 
PROX MN Average proximity index for all patches 
(m) in a class 
ENN. MN(m) Mean Euclidean nearest neighbour 
= distance 
Interspersion and juxtaposition index 
I (%) measures the juxtaposition of a focal 
patch class with all other classes 
SHDI Shannon's diversity index is amount of 
patch per individual; 
Shannon's evenness index is the observed 
SHEI level of diversity divided by the 
maximum possible diversity for a given 
patch richness 
  
Table 2. Landscape pattern metrics description (McGarigal, 
2002, Keles et al., 2008) 
4. RESULTS AND DISCUSSION 
4.1 Land Use/ Cover Changes 
Before doing any other interpretations, thematic LULC maps 
(1979, 2003 and 2009) were assessed their accuracy through 
four measurable means of error matrix: overall accuracy, 
producer's accuracy, user's accuracy and Kappa coefficient. A 
total of 300 stratified random pixels was taken for each LULC 
map and then checked with reference data. According to the 
accuracy assessment results of classified maps, the overall 
accuracy for Landsat MSS 1979, Landsat ETM-- 2003 and 
ASTER 2009 was 92.15%, 84.44% and 89.00% respectively; 
the Kappa Coefficient of those maps reached at 0.9021, 
0.7534 and 0.8005, respectively. Collating with the minimum 
85% accuracy stipulated by the Anderson classification 
scheme for satellite-derived LULC maps, these statistics were 
adequate for continuously studying (Anderson et al., 1976, 
Kamusoko and AniYa, 2006). 
The LULC maps of study area were generated for all three 
years (Figure 3) and classification area statistics were 
Summarised in table 3. The classified areas were measured by 
multiplying the number of pixel with spatial resolution of 
remote data (i.e. 30m), in which the pixel number was 
determined after applying postclassification analysis. And then 
changes were defined based on the difference of pixel number 
between two dates. Based on Figure 2, forest and urban areas were 
the dominant LULC classes in spatial distribution pattern. 
Accordingly, forest area was counted for about 64%, 62.2% and 
59.8% of the total area in 1979, 2003 and 2009 respectively; 
meanwhile urban area was occupied 6.5%, 11.3% and 17.9% of 
the total area in 1979, 2003 and 2009 respectively. The surface 
water body covers about 2.5%, 3.3% and 3.1% of the total region 
study in 1979, 2003 and 2009, respectively. The results also 
showed that from 1979 to 2009 LULC units under shrub, 
agriculture and barren decreased from 10.1% to 9.9%, 12.4% to 
7.5% and 4.5% to 1.8%, respectively. 
70 
  
o 
o 
o 
o 
B 
o 
Ww 
o 
; 81979 
  
N 
o 
  
Percentage of land use (%) 
A 
o 
  
  
  
agriculture baren 
built-up 
  
  
forest shrub 
Land use type 
  
water 
Figure 2. Areas land use/cover classes of Danang city 
2003 
m 2009 
To provide a further comprehensive calculation in losing and 
gaining among the six LULC classes, the from-to change matrix of 
land use/cover in Danang city were created in three intervals, 
1979-2003, 2003-2009 and 
tabulation, unchanged pixels were located along the major 
diagonal of the matrix while conversion values of classes were 
arranged in descending order. As can be seen from the Tables 3 
and 4, there were small differences of area coverage of a particular 
class because of used different spatial resolutions for calculating 
LULC change from 2003 to 2009. In fact, the 2009 ASTER image 
was resampled to a spatial resolution of 30m. 
1979-2009(Table 
4) In 
Cross 
  
  
  
LULC z 1979 E 2003 z 2009 
class rea 0 rea à rea 3 
(ha) (76) (ha) (%) (ha) (%) 
Agri- 
12048.0 12.4 9512.0 9.8 7294.7 7.5 
culture 
Barren 4312.2 4.5 1771.0 1.8 1708.9 1.8 
Urban 6315.3 0.5 109007 113 172985 17.9 
Forest 61972.0 640 602330 622 579362 59.8 
Shrub 9785.2 101. - 111694 115 9575.8 9.9 
Water 2384.6 2.5 3231.2 33 3003.6 3.1 
Total 96817.2 100 96817 100  96817.7 100 
  
Table 3. Results of and use/cover classification for 1979, 2003 
and 2009 images