Geography Reference
In-Depth Information
Table 3. Vulnerability class by different land use categories
Parameters
Land use exposed to flood risk (km
2
)
Proximity
to source
of hazard
(
m)
Elevation
within buffer
distance (m)
Urbanized
area (higher
density)
Vulnerability
class
Urbanized
area
Agricultural
land
Forest
5
0
≤ 5
Very high
12.85
(4.4)
1.74
(0.6)
1.37
(0.5)
32.47
(11.0)
1
00
≤ 5
High
9.15
(3.1)
4.17
(1.4)
2.68
(0.9)
31.93
(10.8)
1
50
≤ 5
Moderate
6.28
(2.1)
5.28
(1.8)
3.26
(1.1)
30.00
(10.1)
2
00
6-10
Low
8.01
(2.7)
8.90
(3.0)
5.95
(2.0)
39.51
(13.3)
3
00
6-10
Very low
11.78
(4.0)
14.59
(4.9)
10.93
(3.7)
55.18
(18.6)
Total
48.07
(16.3)
34.68
(11.7)
24.19
(8.2)
189.09
(63.8)
Note:
values in parentheses are the corresponding percentage values.
This can be deduced from the result of supervised classification (Figure 7b)
which shows a pattern of intermediate or transitional relationship, where urban
land use is engulfing agricultural lands and the latter, in turn encroa-ching into
forest lands.
5.2. Spatial Analysis of Urban Infrastructural Vulnerability
Infrastructural vulnerability involves the road structure and rail track that
are exposed to flooding hazard because they are found in the flood prone area
of the region. These infrastructures have high economic value and are mostly
susceptible to the hazard. For example, the asphalting of roads involve huge
financial resources and it can easily be destroyed by insistent waterlogging.
On the other hand, road is the primary medium for accessibility in an
urban space and when it is flooded, it eventually obstruct economic activities.
Road infrastructure includes expressway, major and residential roads that are
paved, while rail infrastructure includes active rail tracks. This were further
group and reclassified as dual and single lane.
To map, visualize and estimate the length of road and rail track susceptible
to flood disaster, the generated flood risk map (Figure 9) was set to 60 percent
transparency and then converted to Keyhole Markup Language (KML) format.
KML is an excellent format for sharing geographic data because it has the
capability to compress graphic and non-graphic data either in raster, vector or
both including their respective spatial references, symbology, etc. into one file.
The flood risk data in KML format (major format acceptable by Google
earth) was entered into Google earth engine for progressive manipulation.
