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Landuse - landcover change detection and associated climatic responses in Akure, Nigeria

Ifeoluwa A. Balogun, Z., Ahmed A. Balogun & Z. Debo. Adeyewa

Department of Meteorology, Federal University of Technology, Akure, PMB 704, Akure, Ondo State, Nigeria

INTRODUCTION

The UN Predicts that 60% of the world's population (~ 5 billion people) will be living in cities by 2030 and that nearly all the population growth will be in the cities of developing countries This rapid population growth will largely drive the extent and rate of global environmental changes and many of these changes are related to the climate of cities, including the canopy layer urban heat island (UHI); the observed warmth of the urban core compared to its rural surroundings. Akure (Lat: 7.25 °N; Lon: 5.20 °E), in south-western Nigeria has seen remarkable growth in its urbanization in recent years, and its population during the past few decade has more than more than tripled from157, 947 in 1990 to ~500, 000 in 2006. Multi temporal remote sensing data and GIS techniques were used to detect landuse landcover changes that have occurred over the years and the urban modifying effect on the city's climate was investigated using data obtained from 2-years in situ simultaneous measurement of air temperature and relative humidity within the city, extending to rural reference outskirts of the city We found changes in landuse landcover of Akure through our different classification scheme (arable land, bare-surface land, built-up/settlement, dense forest and water bodies with a percentage change of 11.24, -5.86, 28.36, -23.87, 0.13 respectively between 1986 and 2007). Results further revealed the modifying effect of urbanization on the city's climate, resulting in the urban heat island phenomenon and urban humidity deficits. Also, the economic implication on energy demand for cooling with associated air quality degradation and climate change were discussed.

RESULTS

METHOD

The analysis of LULCC is predicated basically on the use of remote sensing and GIS techniques. Ilwisi 3.1 was used in carving out Akure and its environs out of the whole image within the path/row. Also, for the classification of imagery and other image processing and enhancement. ArcView3.2a was also used in displaying, subsequent processing and enhancement of the image. Data from the in situ measurements were analysed and presented using Surfer and Matlab program. Fig.2 (a, b & c): Landuse landcover map of Akure in 1986, 2002 & 2007 respectively

STUDY AREA

7.32

Fig 1: Location map of Nigeria and Akure (7.25 °N, 5.20)

7.3

Oja-Oba (Urban)

7.28

Northing, Latitude

Airport (Rural)

Fig.3a:

7.26

Airport

Fig.4 (a, & b): Diurnal variation of mean monthly urban ­ rural differences in air temperature and relative humidity respectively

7.24

2km

CONCLUSIONS

Potential use of Remote sensing data and GIS techniques in investigating LULCC of Akure has revealed some interesting findings. The five classes were distinctly produced for each study year and results indicated a rapid change in built up and arable land as they have increased tremendously and the dense forest terribly depleted. Results further revealed the modifying effect of urbanisation on the city's climate, resulting in the urban heat island phenomenon and urban humidity deficits. It also indicated the potential economic impact of the urban growth on the city's energy demand for cooling and air quality degradation in such processes that are capable of contributing to climate change Findings from this research calls for improved urban planning, agricultural enhancement to improve food security, urban greening and afforestation considering the mitigating roles of urban trees on heat island and forests on global warming and climate change.

7.22

7.2 5.1 5.12 5.14 5.16 5.18 5.2 5.22 5.24 5.26

5.28 5.3 5.32 Easting, Longitude

Fig 1: Google Earth aerial image of Akure, numbered circles represent some of the measurement sites (city centre and rural reference airport) with corresponding photo and sky view shown as inset.

ACKNOWLEDGEMENT

Landcover/Landuse Categories Approx. Rate of 1986/2007 Difference in Area % Difference Change between 1986 (m 2 ) in Area & 2007 2.42 18224.23 11.24 -3.2 -9501.24 -5.86 13.7 45982.13 28.36 -3.6 -54915.90 -33.87 1.5 210.78 0.13

Fig.3b: The authors wish to acknowledge the Global Land Cover Facility (University of Maryland) for the provision of free Landsat data which was very useful for this project.

REFERENCES

BREST, C. L., 1987, Seasonal albedo of an urban/ rural landscape from satellite observations. Journal of Applied Meteorology, 26, pp. 1169- 1187. CARNAHAN, W.H AND LARSON, R.C., 1990, An analysis of an urban heat sink. Remote Sensing of Environment, 33, pp. 65-71. ELLIS, E.C., WANG, H. and XIAO H.S., 2006, Measuring long-term ecological changes in densely populated landscapes using current and historical high resolution imagery. Remote Sensing Environment, 100, pp. 457­73. HAFNER, J and KIDDER, S. Q., 1999, Urban heat island modeling in conjunction with satellite-derived surface/soil parameters. Journal of Applied Meteorology 38, pp. 448-465 ROTH, M., OKE, T.R. AND EMERY, W.J., 1989, Satellite derived urban heat islands from three coastal cities and the utilisation of such data in urban climatology. International Journal of Remote Sensing 10 (11), pp. 1699­ 1720. VOOGT J. A and OKE T.R., 2003, Thermal remote sensing of urban climates, Remote Sensing of Environment, 86, pp. 370-384.

Arable land Bare surface/Land Built-up/settlement Dense Forest Water bodies

Table 1: LandUse LandCover Distribution (1986 & 2007)

Part of PhD research presented at the ISP- NCAR Summer Colloquium on African Weather and Climate , 24th July ­ 5th August 2011. Boulder, Colorado, USA

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