• No results found

This study has successfully investigated the urban development dynamics of Awka Capital Territory, and based on the experience and results obtained, the following recommendations are hereby proffered:

1. Thisresearch work was able to generate landcover and landuse maps of Awka Capital Territoryfor the years 1990, 1999, 2008, 2017 and 2018. It is recommended that the data obtained here be used as an addition to the spatial data availability for the study area.

This will take care of the lack of landcover/landuse maps of Awka Capital Territory between 1990 and 2018.

180 2. The study was able to determine the trend of change, annual rate of change, transitions of landcover/landuse classes and the pattern of growthwithin the study area. The result obtained from the trend and annual rate of change, the transitions of landcover/landuse and pattern of growth in the study area is recommended as it provides data on what landcover/landuse class are changing, what they are changing into, their rate of change and the pattern at which the urban patches in the study area are growing. This will enable relevant authorities plan and manage landcover/landuse changes in the study area.

3. The study was able to analyze the relationship between LST and Landcover/landuse classes in Awka Capital Territory, this indicateda consistent increase in surface temperature in urban areas between 1990 and 2017, it also identified a growing trend of deforestation during said period, the results obtained here is recommended as it provides relevant data that will help with the effortstowardsa planned reforestation, advocating tree planting as part of landscaping activities and development of parks and botanical gardens on open spaces within the Awka Capital Territory to reduce thedeforestation and hence lower the expansion of urban heat islands in the study area.

4. The study has successfully demonstrated and predicted the future urban development dynamics of Awka Capital Territory using Prescott spatial growth model, so therefore the approach, is hereby recommended to be used as tool for planning and decision making in urban development in the study area. This will guide relevant authorities on how to manage and monitor urban development to ensure a habitable environment in the near future

181 Reference

Adah, H.C., Obienusi, E.A., and Ezenwaji, E.E (2014). Evaluation of urban forestry and housing patterns in Awka Metropolis of Anambra State, Nigeria. Journal of Environmental and Earth Science, 4(14), 32-46

Adeboboye, A.J. Ojiako, J.C. and Eze, C.G. (2012). A GIS approach to management of financial institutions spatial distribution and location in Awka, Anambra State, Nigeria.

International Journal of Environmental Science, Management and Engineering Research, 1(2). 114-122

Adedayo, A. (2007). Socio-Spatial Transformations and the urban fringe landscape in Developing Countries, United Nation University Institute for Environment and Human Security (UNU-UHS) Summer Academy on Social Vulnerability and Resilience Building in Mega city. Munich, Germany

Adewale, O.M., Ajala, O.A. andSangodipe, J.A. (2014) Physical Growth Pattern of Settlements in a Traditional Region, Southwest Nigeria. International Journal of Geosciences, 5, 1345-1360. http://dx.doi.org/10.4236/ijg.2014.511110

Aniekan, E., Dupe, N., Nwilo, P., Onuwa, O., Mfon, I., and Daniel, U. (2012). Modeling and Predicting Future Urban Expansion of Lagos, Nigeria from Remote Sensing Data Using Logistic Regression and GIS International Journal of Applied Science and Technology,Vol. 2 No. 5

Alberti, M. and Waddell, P. (2000). An Integrated Urban Development and Ecological Simulation Model, Integrated Assessment,

http://www.odot.state.or.us/tddtpau/papers/P2T2.4.2fnl.pdf, access: April 2001

Abebe, G. A. (2013). Quantifying Urban Growth Pattern in Developing Countries Using Remote Sensing and Spatial Metrics. A Case Study in Kampala, Uganda.M.Sc Thesis of Faculty of Geo-information Science and Earth Observatory of the University of Twente.

Agada, H. C., Obienusi, E. A. and Ezenwaji, E. E. (2014). Evaluation of Urban Forest and Housing Patterns in Awka Metropolis of Anambra State. Nigeria. Journal of Environmental and Earth Science. Vol 4, No 14

Aguayo, M. I., Wiegand, T., Azócar, G. D., Wiegand, K. and Vega, C.E. (2018). Revealing the driving forces of mid-cities urban growth patterns using spatial modeling: a case study of Los Ángeles, Chile. Ecology and Society, 12(1): 13

Anderson, E. (1976). A Landuse and Landcover Classification System for Use with Remote Sensor Data. Geological Survey Professional Paper No. 964, U.S. Government Printing Office, Washington, D.C. p. 28.

Anigbogu, S.O. (2000). Computer Applications and Operations. Optimum press, Awka

182 Atef, M.A., Adamat, R, and Al-Amoush, H. (2012). GIS and Remote Sensing to Investigate Urban Growth in Mafraq City/Jordan between 1987 and 2010. Journal of Geographic Information System. 4. 377-382. 10.4236/jgis.2012.44043.

Batty, M. (1994). A chronicle of scientific planning: The Anglo-American modeling experience, in Journal of the American Planning Association, 60, 1, pp. 7-12.

Bayes, A., (2013). Remote Sensing for Urban Land Cover Mapping and Change Detection Analysis. Geospatial World Weekly Publication.

Beimborn, E., Kennedy, R. and Schaefer, W. (1996) Making Transportation Models Work for Livable Communities, Inside the Blackbox (Milwaukee: Centre for Urban Transportation Studies, University of Wisconsin).

Carmelo, R. F., Modica, G.,andPollino, M. (2012). Land CoverClassificationand Change-Detection Analysis using Multi-Temporal Remote Sensed Imagery and Landscape Metrics. EuropeanJournalofRemoteSensing,45: pp 1-18 http;

www.10.5721/EuJRS20124501.com Retrieved 25th April, 2014.

Cohen, J. A (1960). Coefficient of agreement for nominal scales. Educ. Psychol. Meas. 20, 37–

46.

Courage, K.., and Jonah, G. (2013) Simulating Urban Growth Using a Random Forest-Cellular Automata (RF-CA) Model, International Journal of Geo-Information ISSN 2220-9964 www.mdpi.com/journal/ijgi/

CTSDF overview (2012). City Space Cape Town spatial development framework Statutory report, South Africa.

Danson, F. M., Plummer, S. E., and Briggs, S. A. (1995). Remote Sensing and the information extraction problem. In: DANSON, F. M. and PLUMMER, S. E. (eds.) Advances in environmental remote sensing. Chichester: John Wiley and Sons Ltd.

Deakin, E. (1995). Land Use Model Conference Keynote Address. In Travel Model Improvement Program Land Use Modeling Conference Proceedings. Travel Model Improvement Program. DOT-T-96-09. U.S. Department of Transportation, U.S.

Environmental Protection Agency, and U.S. Department of Energy.

Deng, J.S., Wang, K., Hong, Y. and Qi, J.G. (2018). Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and Urban Planning, 92, 187-198.

Dirim S., Ertuğrul, A., andGökhan, O. (2009) Remote Sensing and Gis Applications For Monitoring Multi- Temporal Changes of Natural Resources in Bursa-Turkey J. BIOL.

ENVIRON. SCI., 3(8), 53-59

183 Dimitrios, T., andGiorgos, M. (2012) Urban Growth Prediction: A Review of Computational

Models and Human Perceptions, Journal of Geographic Information System, 4, 555-587 http://dx.doi.org/10.4236/jgis.2012.46060 Published Online December 2012

Dimitrios, P., (2012), urban growth prediction modeling using fractals and theory of chaos Open J. Civ. Eng.

Douglas, W., Stuart, R. P., and Alan, T. M. (2000) Monitoring Growth in Rapidly Urbanizing AreasUsing Remotely Sensed Data, Professional Geographer, 52(3), pages 371 –386 © Copyright 2000 by Association of American Geographers.

Eric, V., and Jamal, J. A. (2015). Predicting Urban Growth of the Greater Toronto Area - Coupling a Markov Cellular Automata with Document Meta-Analysis. Journal of Environmental Informatics. 25. 10.3808/jei.201500299.

Estes, J. M., Crosson, W.L., Al-Hamdan, M., Quattrochi, D., and Johnson, H. (2009). Watershed and hydrodynamic modeling for evaluating the impact of land use change on submerged aquatic vegetation and seagrasses in Mobile Bayieeexplore.ieee.org

Estes, J. M., Crosson, W.L., Al-Hamdan, M., Quattrochi, D., and Johnson, H. (2010). Validation and demonstration of the Prescott Spatial Growth Model in metropolitan Atlanta, Georgia. URISA Journal. 22. 5-21.

Ezeomedo, I. C. (2012). Urban Sprawl Identification, Analysis and Modelling Using Remote Sensing and GIS. Unpublished M.Sc. thesis of the Department of Surveying and Geoinformatics, Nnamdi Azikiwe University, Awka.

Foody,G.M.(2002).Statusoflandcoverclassificationaccuracyassessment.RemoteSensingofEnviron ment,80(1),185-201.doi:10.1016/s0034-4257(01)00295-4

Fung, T. andLedrew, E. (1988). The Determination of optimal threshold levels for change detection using various accuracy indices. Photogrammetric Engineering and Remote sensing Journal 54 (10), 1449 – 1454.

Gabriele, N., Rosa, L., and Beniamino M. (2013). Applying Spatial Autocorrelation Techniques to Multi-Temporal Satellite Data for Measuring Urban Growth, International Journal of Environmental Protection, Vol. 3 Issue. 7, Pp 11-21.

Gavier-Pizarro, G.I., V.C. Radeloff, S.I. Stewart, C.D. Huebner, and N.S. Keuler. 2010. Housing is positively associated with invasive exotic plant species richness in New England, USA.

Ecological Applications, 20(7):1913-1925.

Haack, B., and Rafter, A. (2006). Urban Growth Analysis and Modeling in the Kathmandu Valley, Nepal. Habitat International, 30, 1056-1065.