Abstract:
Globally, wetlands occupy about 6% of the earth’s surface. Kenya’s wetlands cover about 3% to 4% of the land’s surface which is approximately 14,000km2 in area and fluctuates up to 6% in the rainy seasons. Most scientist have compared wetlands to “the kidneys of the landscape”, because of the functions they perform in the hydrological and chemical cycles, and as “biological supermarkets” because of the extensive food webs and rich biodiversity they support. Ondiri wetland is quite an essential ecosystem to the livelihoods of most residents of Kikuyu town in Kiambu county, as they obtain both economic and social benefits from it and also, as an important source of Nairobi river which passes through the city of Nairobi.
Despite the valuable functions wetlands offer, they are often referred to as “wastelands “and they are continually being degraded and being lost through various ways some of which have been mentioned in these research. Human kind has been draining, in-filling both coastal and inland wetlands for a long time. Ondiri being one of the wetlands is experiencing serious environmental problems due to anthropogenic and hydrodynamic driving forces which relate to the dumping of solid waste, over abstraction of water, encroachment of the wetland for commercial and residential use, wetland agriculture and many other forces which could disrupt the environmental balances. The lack of understanding of their linkages with community decision making mechanisms in the livelihoods web of the riparian human population is posing a major threat to the wetland.
Therefore, this study aims to demonstrate the use of GIS technology in examining, characterizing the changes, identifying the associated spatio-temporal links between social and ecological dynamics that are driving the changes. This study utilized both secondary and primary data. LANDSAT TM and ETM satellite images of 1988, 2000, 2010 and 2019 were used to determine the changes in land use using biotic vegetation cover types and indicators. Image analysis shall be done using ENVI 5.2 and ERDAS 9.3 software packages. A supervised classification was also carried out on the images and the kappa index of agreement estimated. Change in human population were also determined using human population census data projected to the time steps of the study and spatial renditions in a GIS environment. In addition, the dynamics of water level changes were also measured both from the satellite images. Soil moisture Index was also calculated to determine its relationship with the wetland.