Analysis Of Forest Cover Change Detection In Relation To Climate Change By Using Gis And Remote Sensing Technique : Case Of Kaffa Zone South Western Ethiopia

Abstract

The consumption of forest and forest products has been shown to be higher than the incremental yield (forest gain) of forests leading to deforestation and forest degradation in the country. A forest loss of 50% within the last 37 years has been reported for south western Ethiopia. The main focus of this study was the applicability of Geographic information systems to detect forest cover change in relation of climate trends during last 32 years (1986-2018) in Kaffa zone south western Ethiopia. Satellite images from USGS Landsat TM (1986, 1990), ETM+ (2010, 2016) and OLI 8 (2018) were used for forest cover change detection. Beside of these rainfall and temperature data were analysed to correlate the NDVI value with annual climate data. A supervised classification was made using maximum likelihood method in ERDAS imagine V 9.2 software. In order to examine the areal extent and rate of forest cover change post classification change comparison method were done using ArcGIS V 10.4.1. The major land use land cover types in the study area have been classified as settlement, farmland, wetland and forest. The statistical results show that the pattern of forest area was decreased from 10020.33 Ha to 9143.19 Ha between the year of 1986 and 2010. As well as it was reduced in to 8851.23 Ha in 2018 in the study area respectively and net change were 846.45 Ha and 322.2Ha in interval of the 1986-2010 and 2010-2018. In general, the result indicates that the overall vegetation is not in stable condition. In 1986 minimum value and maximum value of 0.06 and 0.64 respectively declined to 2010 (minimum 0 and maximum value 0.77) When we compared to 2010 and 2016 image NDVI value the minimum and maximum value ranges from 0 to 0.77 declined to minimum and maximum value of - 0.08 to 0.12 at 2016. The linear regression shows as there was continues fluctuation of rainfall and minimum temperature and increase of maximum temperature. These also indicates if the two parameter was fluctuates each other there was negative effect on the NDVI value; but the rainfall and temperature exceeds at the same time the NDVI does not decreased and there is no vegetation that were unhealthy. The information generated from these study area is expected to be of immense help in formulating policies and programmes required for sustainability of forest land and climate variability.