Geography Reference
In-Depth Information
Table 5. Urbanized areas and population at risk by LGA
Extent of risk area by vulnerability class
(km
2
)
Urba-
nized
area
extent
(km
2
)
Population distribution
T
otal area
extent
(km
2
)
LGA
Total
popu-
lation
*
Popu-
lation
density
Popu-
lation at
risk
Very
high
Mode-
rate
Very
low
High
Low
Ajeromi/
I
felodun
11.82
11.56
0.004
0.020
0.030
0.041
0.113
856,869
74,103 3,020
Alimosho
150.38
120.11
0.000
0.000
0.000
0.005
0.038
1,645,094 13,696 69
Amuwo-
O
dofin
176.72
81.93
3.090
2.703
2.277
3.524
4.845
410,129
5,006
24,253
A
papa
42.31
29.07
2.089
1.951
1.735
1.612
2.881
277,994
9,563
15,415
B
adagry
502.15
135.80
1.170
1.076
0.850
1.736
3.069
296,378
2,182
3,788
E
pe
1,220.83
47.93
0.319
0.265
0.255
0.371
1.150
226,566
4,726
1,754
E
ti-Osa
184.19
106.38
3.066
2.857
2.521
2.867
4.966
353,799
3,325
16,514
Ibeju/
L
ekki
467.36
89.89
0.069
0.070
0.034
0.373
0.454
146,851
1,633
609
I
keja
46.46
42.12
0.000
0.000
0.000
0.359
0.073
395,966
9,400
3,373
I
korodu
375.32
139.16
0.417
0.435
0.398
0.400
0.834
658,148
4,729
1,895
K
osofe
75.28
38.55
1.131
1.113
0.965
2.003
2.214
851,204
22,077 44,227
Lagos
I
sland
242.65
25.33
2.199
1.917
1.645
1.805
3.133
265,171
10,469 18,896
Mainland
23.13
21.05
0.079
0.093
0.098
0.112
0.274
777,104
36,923 4,121
O
jo
182.94
57.02
0.634
0.484
0.403
0.902
1.331
759,449
13,318 12,017
S
homolu
18.588
17.654
0.323
0.334
0.348
0.789
0.973
503,124
28,498 22,493
Total
3,720.028 855.554 14.587 13.318 11.559 16.899 26.348 8,423,846
172,444
*
Projected population figures to 2013 from the 2006 national census data.
The fundamental strengths of this proposed method are simplification,
lesser modeling time, wide range of application, rapid mapping of vital flood
component and quick estimation of vulnerable population, infrastructures and
environmental layout. In addition, the classification of vulnerability into five
magnitudes offers a wide range of options for planners to explore and make
multi-level decisions pertaining to flood hazard mitigation.
Remarkably, the assessment of exposed population and settled areas by
grass root level will facilitate coordination between the tiers of government
regarding policy making and intervention. The prime limitation of this
framework is finding a suitable method with higher level of accuracy to
estimate endangered population especially in developing African cities where
population data is aggregated on large scale administrative elements; and
neighborhood-based demographic data is lacking.
Conventional density estimation method which assumes the homogenous
distribution of population over space often under-mine the fact that population
