Application of geospatial techniques and binary logistic regression model for analyzing driving factors of urban growth in Bahir Dar city, Ethiopia

Understanding the drivers of urban growth and spatiotemporal land use change is important for rational land use and sustainable urban development. Based on the land use data, GIS data of explanatory variables, experts' knowledge and field observation, the study used a binary logistic regression model (BLRM) to analyze factors that drive rapid urban growth in Bahir Dar city, Ethiopia, using the LOGISTICREG module in IDRISI Selva software. Nine factors were used to reflect the influence of proximity and physical factors on urban growth from 1984 to 2019. This model helped in quantifying and identifying the factors of urban growth, which includes topography (slope, elevation and aspect) and accessibility (Dis. to the main road, Dis. to international airport, Dis. to CBD, Dis. to existing built-up area, Dis. to forest land and Dis. to water body). Furthermore, urban growth probability maps were created based on LRM results, revealing that the biggest urban growth would occur around existing built-up areas along the main roads and near Bahir Dar international airport. The Relative Operating Characteristic (ROC) values of 0.85, 0.90 and 0.93 and PCP values of 96.72 %, 98.46 % and 98.51 % indicate the urban growth probability maps are valid and BLRM had an ideal ability to predict urban growth. So, the study highlighted the relation between urban growth and its drivers in Bahir Dar, giving a decision making framework for better land use management and resource allocation.

Watershed degradation and management practices in north-western highland Ethiopia

Watershed degradation in Ethiopia has become a major environmental threat and caused significant damages both in the natural environment and the development of human society. This paper assesses an overview of the extent, causes, and effects of watershed degradation and the management actions in north-western highland Ethiopia, taking the Rib watershed as a case study site. The data were collected from field observations, interviews, and questionnaire surveys administered to 210 farmers. The results show that watershed degradation is a serious and widespread problem in the study site. The major causes of watershed degradation include population growth, uncontrolled grazing, unsustainable land use and management practices, and weak land ownership system. Watershed degradation, mainly in the form of soil erosion, has adversely reduced agricultural production and worsened food insecurity and poverty in the study area. Various watershed management practices that combine structural and biological measures have been practiced to curb the problem. However, the farmers' decisions to adopt and implement the measures have been highly influenced by a range of socioeconomic, biophysical, and institutional factors. Access to support services, size of the farmland, educational level, and plot ownership were found to influence farmers' decisions positively at a statistically significant (P < 0.01) level. It needs efforts to create farmer environmental awareness and develop strong watershed management standards and guidelines. The watershed could benefit from hand in hand efforts of local farmers, concerned governmental agencies, and researchers.