Land Use/Land Cover Changes in a disturbed River Watershed in Njoro, Kenya
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Abstract
Drivers of land use change were captured by the use of DPSIR model where Drivers (D) represented human needs, Pressures (P), human activities, State (S), the ecosystem, Impact (I) services from the ecosystem and Response (R), the decisions taken by land users. Land sat MSS and Land sat ETM+ (path 185, row 31) were used in this study. The Land sat ETM+ image (June 1987, May, 2000 and July, 2014) was downloaded from USGS Earth Resources Observation Systems data website. Remote sensing image processing was performed by using ERDAS Imagine 9.1. Two Land Use / Land Cover (LULC) classes were established as forest and shrub land. Severe land cover changes was found to have occurred from 1987-2000, where shrub land reduced by -19%, and forestry reduced by -72%. During 2000 – 2014 shrub land reduced by -45 per cent, and forestry reduced by -64 per cent. Forestry and shrub land were found to be consistently reducing.
References
Baldyga, T.J. (2003). Assessing Land cover Change Impacts in Kenya’s River Njoro Watershed using remote sensing and Hydrological Modeling. MSc Thesis (unpublished) submitted to the Department of Renewable Resources at the University of Wyoming. Laramie, U.S.A.
Demers, M. N. (2005). Fundamentals of Geographic Information Systems, John Wiley & Sons, Inc., New York, USA, 2005.
Dwivedi, R.S., K.Sreenivas, K.V.Ramana, (2005). Land-use/land-cover change analysis in part of Ethiopia using Landsat Thematic Mapper data. International Journal of Remote Sensing 2005, 26 (7), 1285-1287.
European Environment Agency (1999). Environmental Indicators: Typology and Overview. Technical Report No. 25, Copenhagen.
Fan, F., Weng, Q., Y. Wang, (2007). Land use land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery. Sensors 2007, 7, 1323-1342.
Fan, F., Weng Q., and Y.Wang, (2010). Land use and land cover change in Guangzhou, china, from 1998 to 2003, based on Landsat TM /ETM+ imagery Sensors 7, 1323-1342
Government of Kenya, Kenya National Bureau of Statistic (KNBS) (2009). Kenya National Population and housing census, 2009.
Guerschman J.P., J.M.Paruelo, C.D.Bela, M.C.Giallorenzi, F.Pacin, (2003). Land cover classification in the Argentine Pampas using multi-temporal Landsat TM data. International Journal of Remote Sensing 2003, 24, 3381–3402.
Giupponi C. (2002). From the DPSIR reporting framework to a system for a dynamic and integrated decision making process. International MULINO Conference on “European policy and tools for sustainable water management†Island of San Servolo, Venice, Italy, November 21-23.
Kristensen P. (2004). The DPSIR Framework. National Environmental Research Institute, Denmark. European Topic Centre, European Environment Agency.
Mainuri, Z.G., and J.O.Owino, (2013). Effects of land use and management on aggregate stability and hydraulic conductivity of soils within River Njoro Watershed in Kenya. International Journal of Soil and water conservation research. Vol.1 No.2 pp. 80 -87.
Muttitanon W. N.K. Tiýpathi, (2005). Land use/land cover changes in the coastal zone of Ban Don Bay, Thailand using Landsat 5 TM data. International Journal of Remote Sensing 2005, 26 (11), 2311- 2323.
Prenzel, B.(2004). Remote sensing-based quantification of land-cover and land-use change for planning.Progress in Planning 2004, 61, 281–299.
Rogan J, D.Chen, (2004). Remote sensing technology for mapping and monitoring land-cover and landuse change. Progress in Planning 2004, 61, 301–325.
Seto, K.C., C.E.Woodcock, C.Song, X.Huang, J.Lu, R.K. Kaufmann, (2002).Monitoring land use change in the Pearl River Delta using Landsat TM. International Journal of Remote Sensing 2002, 23, (10), 1985-2004
Tscherning K., K.Helming, B.Krippner, S.Sieber and Y.Gomez, S.Paloma, (2012). Does research applying the DPSIR framework support decision making? Land Use Policy, 29(1), 102– 110. United Nations (UN), 1996. Indicators of sustainable development: Framework and Methodologies. Report. 428
Wood A. and van Halsema G. (2008), Scoping agriculture–wetland interactions Towards a sustainable multiple-response strategy, FAO Water Reports No 33
Wu, Q., H. Q.Li, R.S.Wang, J.Paulussen, H.He, M.Wang, B.H.Wang, Z.Wang, (2006). Monitoring and predicting land use change in Beijing using remote sensing and GIS. Landscape and Urban Planning 2006, 78, 322–333.
Yomralýoglu, T. (2000), Coorafi Bilgi Sistemleri: Temel Kavramlar ve Uygulamalar, Seçil Ofset, Istanbul, Turkey, 2000.
Zsuzsanna, D., J.Bartholy, R.Pongracz, Z.Barcza, (2005). Analysis of land-use/land-cover change in the Carpathian region based on remote sensing techniques. Physics and Chemistry of Earth 2005, 30, 109-115. © 2008 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.