Geography Reference
In-Depth Information
The latter was complemented with Google data based on its resolution and
distinctiveness in displaying surface features. It is a better platform as a guide
for the analyst to assess the degree of accuracy with respect to the training data
collected and vulnerable features.
5.
R
ESULTS AND
D
ISCUSSION
In this section, the extracted flood risk mask were related to the suscep-
tible features with the aim of creating a comprehensive flood risk GIS-based
database system for the area. The susceptible features are the high-valued land
uses-urban and agricultural areas. The former includes the population and
infrastructures (roads and rail tracks) while the latter includes cultivated and
arable lands.
5.1. Spatial Assessment and Analysis of Land Use Vulnerability
The result of supervised land use classification (Figure 7b) revealed that
urban footprint extends as much as 1,092.7 km
2
covering 28.7 percent of the
total area of Lagos State, out of this, higher density urban area covers 7.4
percent, cultivated land use occupies 22.3 percent and forest land 31.5 percent.
The flood risk mask which has been classified into five levels of risk-very
high, high, moderate, low and very low was superimposed (applying spatial
intersect) on the land use map derived from remotely sensed data to visualize
and quantify features exposed to flood hazard. Figure 10 shows the spatial
distribution of vulnerability to flooding disaster on different land use classes.
The overall areal extent in the land use map potentially exposed to flood
hazard is roughly 296 km
2
. From the perspective of high-valued land uses,
such as urbanized area and arable area (which is basically the central focus of
this chapter), the potentially endangered valued land covers approximately 107
km
2
which is about 36 percent of the total vulnerable area. Additionally, more
than 7 percent of the overall urbanized area are susceptible to the hazard.
The results in Table 3 (extracted from the attribute table of the spatial
analysis in ArcMap) show that more than 48 km
2
of the higher density urban
land use is likely to be affected during flood scenario. Based on evidence from
this analysis, serious urban activities are concentrated close to water bodies
and in most cases, in extremely low lying terrain.
