Drivers of Land Use-Land Cover Changes in the Central Rift Valley of Ethiopia

Abstract

Land use-land cover change (LULCC) is driven by the interplay of forcing factors that act at global, regional, and local levels. Previous studies investigated mainly the basic socioeconomic drivers of LULCC. However, these studies less considered climate change vulnerability as a potential driver. Hence, this study is aimed to assess LULCC drivers in more fragile and dynamic landscapes of the East African Rift Valley region for the period of 1986-2016. We used a combination of Remote Sensing, Geographic Information System, logistic regression, and descriptive statistics to quantify and analyze the data. Image analysis results indicated that during the overall study period (1986-2016), grass/ grazing land, agricultural land, and bare land have increased by 124%, 42%, and 34% respectively, whereas scattered acacia woodland, bush/shrubland, and swampy/marshy land have declined by 52%, 50%, and 31%, in that order. This image-derived change trend is in line with farmers' perceived results. The top most influential drivers of LULCC includes population growth (95%), fuelwood extraction (93%), agricultural land expansion (92%), charcoal making (92%), climate change/recurrent drought (79%), and overgrazing (71%) in descending order of percentage of respondents. Education level and age of farmers significantly (p<0.05) affected their perception towards less perceived drivers. Hence, in order to reduce the adverse socio-environmental impacts of spectacular LULCC in the region, policy and decision makers need to take into account such principal drivers, particularly population growth and climate change.

Seasonal land use land cover change and the drivers in Kafta-Sheraro National Park, Tigray, Ethiopia

“…As stated by focus group discussion and key informant interview the woodland of the park is not only used as source energy but also used as generating alternative income by the local communities. This result is in line with Central RiftValley [85] and Malawi [115] they revealed fuelwood collection and charcoal making were the main drivers of LULC change. Resettlement program, expansion of farmland, human-induced fire, lack of land use plan, and unwise utilization were the top significant drivers of change [110].…”

“…Farmland expansion as the expense of forest and woodland decline was also reported [105,106]. More studies from the central Rift Valley of dryland revealed areas of cropland doubled, grass/grazing land and bareland increased as the cost of woodland destructed between 1986 and 2016 [85,99,107]. In advance to cultivated land, a remarkable increasing trend was showed mainly at the expense of forest cover [108].…”

“…A negative value presents a decrease in LULC size while a positive value indicates an increase in the size of LULC class [84].The percent rate of LULC change between periods were computed following equation ( 6) [46,[85][86][87].…”

Seasonal land use/land cover change and the drivers in Kafta Sheraro national park, Tigray, Ethiopia

“…The percent rate of LULC change was computed by Eq. (7) ( Duraisamy et al., 2018 ; Bekele et al., 2019 ; Asmame and Abegaz, 2017 ; Esa and Assen, 2017 ). …”

Land Use/Land Cover Change and Their Driving Factors in the Yellow River Basin of Shandong Province Based on Google Earth Engine from 2000 to 2020

“…The qualitative analysis method can only analyze the impact of various influencing factors on LULC change, but cannot quantitatively express the impact degree of various factors on LULC change [27,28]. Although the quantitative method can clarify the influence degree of various influencing factors on land use change, both methods ignore the relationship between influencing factors and land use change in spatial location [29,30], so it is difficult to accurately analyze their internal change potential mechanism. The geographic detector is a statistical method based on the statistical principle to detect spatial differentiation and reveal driving factors [31,32].…”