Transcript LAND USE/LAND COVER CHANGE EARLY WARNING SYSTEM AND

LAND USE/LAND COVER CHANGE EARLY
WARNING SYSTEM AND CLIMATE
CHANGE IN THE QUA IBOE RIVER BASIN,
NIGERIA
EKPENYONG, Robert Etim
Department Of Geography and Regional Planning
University Of Uyo
Uyo, AKS
Nigeria
Introduction
• Studies have shown that information on land use/ land cover is
required for rational and sustainable allocation of land
resources for development [YANG and LO, 2003; EL-RAEY
et.al., 2000; BRONSVELD et. al., 1994].
• In the Qua Iboe River Basin, Nigeria, growing population
densities, urbanization and poverty is leading to widespread
changes in land use and land cover. The situation is so serious
that food security, socio-economic development and the
climate/microclimate of many areas are being threatened.
• To effectively address these problems and ensure that future
generations can enjoy the benefits of the earth’s resources,
there is need for an early warning system for land cover change
analysis and mapping.
LOCATION OF STUDY AREA
• The Qua Iboe River
basin is located within
Akwa Ibom State which
is situated in South
Eastern Nigeria.
• It lies between latitude
4°30” and 5°30”N and
long 7°30” and 8°15”E
(Fig.1)
• The catchment area of
the basin lies between
the Imo and Cross
Rivers and covers
about 3266sq.km.
Theoretical Considerations
•
•
Generally, urban areas are made up of buildings and pavements which
changes the natural landscape into townscape. The surface materials
are mostly hard. This implies that, the thermal conductivity and heat
capacity are greater than when the surface was mostly composed of
vegetation.
Studies have shown that, the modification of the environment through
the creation of cities represents a more extreme form of microclimate
alteration [ Ojo 1977].
•
Transpiration from vegetation causes higher humidity. However,
changes in vegetation cover from trees to grass usually decreases
evaporation and transpiration losses and reduces the amount of rain
and snow intercepted by foliage. Furthermore, temperature and wind
speeds are lower within forested areas than in the open. Cities tend to
have higher temperatures than the surrounding suburbs and they
produce more haze and smoke [MILLER et. al, 1970; OJO, 1977].
•
The foregoing underscores the importance of land use/land cover in
climate change.
Materials and Methods
Data Acquisition, Database creation and Data Analysis
• Maps of the area, mainly those showing relief and drainage, soils,
vegetation, rainfall and temperature distribution, land
capability/suitability, land resource development areas etc., published
in 1982 by Cross River basin Development Authority at a scale of
1:250,000 were scanned, geo-referenced and digitized to create the
early warning system baseline dataset.
•
Supervised classification was carried out to produce Land use/Land
cover maps for the different time periods [year 1984 and 2003]. These
are periods before the area was constituted into a State and the period
16years after State creation. Random test fields were located in the
original image and in the field to perform accuracy assessment. An
overall accuracy of 82.11% was estimated. For change detection, the
areas of the cover types were derived from the histogram of the
respective classified imagery. [YANG et al, 2002; SINGH, 1999;
JENSEN, 1995; LILLESAND et al, 1994]. The image processing
software used was ILWIS 3.3.
The Early Warning System
•
•
•
•
According to EWC 111 [2006], a complete and
effective Early Warning System comprises a chain of
four elements:
Risk knowledge-prior knowledge of the likely risk
scenarios communities are faced with;
Monitoring and warning services-monitoring
capabilities for these risks and rapid and reliable
decision mechanisms for early warning;
Communication-dissemination of understandable
warnings to those at risk;
Response capability-knowledge and preparedness
capacity to act by all partners of the information
chain.
The Land Cover Change Early
Warning System
• The land use/land cover change early warning system
comprised a personal computer system [with intel Pentium 4
processor 3GHz, 200GB HDD, 1024GB RAM and 21’ color
monitor], a variety of GIS and image processing software
[ILWIS 3.3, ArcGIS 9, GPS Utility 4.2, Global mapper, LCCS
2.4.5, SURFER 32, JT Maps etc] and database. It is located in
the Department of Geography and Regional Planning,
University of Uyo, AKS-Nigeria where it is used for capacity
building. To enhance its capabilities, the system is frequently
updated as new theory, models and/or data become available.
Also advantage is often taken of the free GIS/Image processing
software and landsat data available in the internet.
• The early warning system is capable of providing information
on the likely risk scenario that communities may face but the
challenge now is to build partnerships that can support its
monitoring, communication and response capabilities.
Manipulation and Analysis of
Data for Early Warning Purpose
• Fig. 2 and Fig 3 are land use/land cover maps of lower
Qua Iboe River Basin for 1984 and 2003. They were
produced using landsat TM. A summary of the changes
in land use/land cover is given in table 1.
Table 1 Qua Iboe Basin: Land
Cover Type Coverage Area
AREA IN
1984[ha]
AREA IN
2003[ha]
2,504.133
38.817
35.946
127.539
26,939.05
32,074.48
Mosaic farmland/oilpalm
forest
8,464.60
18,662.29
Freshwater swamp forest
9,922.95
7,545.29
Mangrove forest
3,739.45
3,644.91
Rivers/Natural water
bodies
8,192.99
10,721.20
Urban/Industrial/built-up
895.995
1028.115
LAND COVER TYPE
Bare soil
Beach sand
Fallow land/grassland
Source: Histograms of classified imageries for 1984 and 2003
A critical examination of the images reveals the facts that,
much of the farmland and fallow land were encroached upon
by urban centers. This has serious implications on
su stain abl e agri cul tu re/ food secu rity, cli mate etc.
Impact of Urbanization
•
•
•
•
Urbanization refers to the process in which an increasing proportion of
an entire population lives in urban and suburban areas. Historically,
this has been closely connected with industrialization and the
discovery of petroleum in Nigeria. New job opportunities in urban
areas spurred the mass movement of surplus population away from the
rural communities [Yang and Lo, 2003; El-Raey et.al., 2000].
In Akwa Ibom state where the Qua Iboe river basin is located; there
were only 10 urban centres as at 1987 when the state was created. Of
this number, five were within the river basin. With the creation of new
Local Government Areas, the number of urban centres in the State
increased to 31. Of this number, 16 are within the catchment of the
Qua Iboe River basin.
The population of people attracted to these urban centres continues to
increase because of the important industries and socio economic
activity centres located within and or close to them. For instance, Uyo
is a capital city and the sit of Government of Akwa Ibom State. It grew
in size as a result of urbanization from 125.595ha in 1984 to 242.262ha
in 2003[table 2].
Two other areas within the basin Eket and Mkpanak also expanded in
size. Eket expanded from 23ha to 27ha while Mkpanak expanded from
7ha to 33ha [table 2].
Table 2. Urban/Industrial/Built-Up Area Land
Cover type coverage Areas
PLACE NAME
AREA IN
1984[ha]
AREA IN
2003[ha]
Uyo
125.595
242.262
Eket
23.472
27.567
6.912
32.697
Mkpanak
A critical visual interpretation of the 1984 images of Uyo,
Eket and Mkpanak reveals the fact that, the settlements were
surrounded by agricultural land [i.e. mosaic farmland/oil
palm forest and bush fallowing/grassland land cover types].
This implies that, the growth of the urban areas in 2003 have
encroached on valuable agricultural land. This is a serious
threat to agriculture/food security in the area under study.
Images Showing Land Cover
Change in Uyo Capital City
Climate Change
• There is no doubt that a city modifies its own
climate. It is however difficult to separate the
influence of the city from that of other factors
such as relief, drainage, or water bodies
within or near the city, which independently
affect climate [ OJO 1977; MILLER et.al 1970].
• However, of all the climatic elements, the
only one that changes quite often within the
area is rainfall.
Table 3 Rainfall Pattern in Uyo Capital City
Years
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Total
(mm)
Dec
Ave
mm)
1984
0
0
147.8
100.6
217.6
400.2
244.2
170.2
225
223.7
149.4
0
1878.1
156.5
1985
63.5
0
157.5
191.2
281.7
213.6
274
392.7
226.4
239.8
84.6
7.6
2132.6
177.7
1986
1.05
63
207.9
99.8
198.8
154.4
313.6
107.8
399.3
296.3
63.2
0
2132.6
177.7
1987
0
42.9
225
165
419
205.8
188.6
300.9
329.4
289.7
26.6
58.5
2251.7
187.6
1988
5.5
3
143.9
228.5
198.4
233.4
310.9
251.3
475.1
213.6
18.3
33.1
1915.1
159.6
1989
0
0
39.1
200.7
261.6
223.8
553.2
331.6
453.7
442.8
82.2
0
2631.7
219.3
1990
22.6
1.5
27
158.7
308.6
113.1
456.2
417.9
152.3
204.5
124.3
41.1
2032.8
169.4
1991
0
29.5
41.2
395.3
207.9
319.6
383.8
405.2
78.2
239.9
69.4
76.7
2243.7
186.9
1992
7.5
0
113.3
115.9
248.5
307.6
470.8
383.1
322.8
116.9
165.7
4.7
2276.8
189.7
1993
2
0
121.8
130.4
141.4
339.9
352.5
468.4
324
252.1
97
0
2229.6
185.8
1994
7.2
6.2
153.3
167.6
300.5
315.4
456.6
380.9
463.6
294.8
122.6
0
2668.7
222.4
1995
4.4
26.1
168.9
82.4
316.8
221.4
428.6
313.7
234.7
339.5
122.9
5
2264.4
188.7
1996
34.8
112.4
124
240.9
398.2
295.2
275.5
407.9
409.6
220.4
1.8
0
2117.6
176.5
1997
17.5
0
113.4
120.8
195.2
237.5
345.4
326.6
151.7
314.7
81.2
17.3
1957
163
1998
26.5
1.8
81.5
131.9
144
303.2
302.7
253
300.4
178.6
241.7
68.5
2033.8
169.5
1999
60.4
85
224.2
275
177.2
154.9
211.1
327
468.6
420.9
95.1
9.1
2509.5
209.1
2000
31.5
0
106.5
125.3
320.4
146.2
254
262.7
281
172.5
95.1
45.6
1840.7
153.4
2001
0
8.6
229.9
219.3
339.7
503.2
219
182.6
270.6
225.6
118.3
0.4
2317.2
193.1
2002
0
10.8
135.1
261.4
312.4
255.8
205
347
320
414.9
30.1
9
2341.5
195.1
2003
20
43
104
223.5
235.6
181.6
202.4
218.6
340.6
207.8
116.7
1
1894.8
157.5
2004
2.1
57
24.2
165.8
218.1
363.8
357.1
288.9
362.3
280.9
79.4
22
2221.6
185
2005
22.4
97
156
284.8
186.7
325.6
637.7
325.1
279
505.5
207.1
3.6
3030.5
252.5
2006
3.7
60.8
277.8
296.8
370.8
592.7
419.3
360.5
566.8
374.9
49.6
0
3373.7
281.1
SOURCE: Department of Meteorological services, station Number 050705B, University of Uyo. Uyo,AKS, Nigeria
Climate Change
• Table 3 shows the yearly variations of rainfall
between 1984 and 2006 for Uyo Capital city.
• Relatively high rainfall of more than 2500mm
occurred in 1989, 1994, 1999, 1005 and 2006
whereas, unusually low rainfall of less than
1900mm was recorded in 1984, 2000 and
2003.
• Compared with the mean annual rainfall of
189.4mm for Uyo, the years 1989, 1994, 1994,
1999, 2001, 2002, 2005 and 2006 were years
with rainfall above the average.
Climate Change
• As can be observed from table 3, more than
80% of the annual rainfall occurs between
March and October of each year, while less
than 20% of the rain falls between November
and February.
• However, a lot of variations occur from year
to year in the monthly distribution of rainfall.
For example, the highest rainfall in 1984 and
2006 occurred in June whereas in 1985, 1987,
and 2002, it occurred in August, May and
October respectively.
Conclusion
• This study confirms reports of destruction of
vegetation cover in the Qua Iboe River Basin.
Since studies have shown that losing
vegetation cover in any area can affect
climate, there is need for the land use/land
cover Change early warning system.
• The results of this study shows that, with the
land use/land cover change early warning
system, it is possible to among other things,
monitor and manage urban growth to ensure
food security and a stable climate regime in
any area.