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