We interviewed stakeholders in the land use planning process at the district level to get a clear understanding of urbanization and the process of formal and informal land use planning, as a complement to already existing data. Stakeholders are representatives of organizations which have been or should be involved in land use planning at different levels of statutory planning. Examples are public authorities on different levels, non-governmental organizations, traditional heads and residents. Interviewees were asked to present: - their understanding of land use planning and urbanization, - the different stages of the planning process, - the roles of different institutions, - how land use priorities were considered in the planning process, - the inclusion of environmentally sensitive areas in planning, - the level of local participation in land use planning, - key spatially explicit determinants of spatial growth in the districts, and - the internal and external hindrances to successful planning.

Land use / land cover classification of the districts Bolgatanga and Bongo in Ghana based on very high resolution remote sensing data (5m). Focus of the classification is on the agricultural class, where single crop types are discriminated. Remote sensing base: RapidEye, TerraSAR-X, Landsat.

Innovation is essential for agricultural and economic development, especially in today’s rapidly changing global environment. While farmers have been recognised as one of the key sources of innovation, many studies on agricultural innovations continue to consider farmers as adopters of externally-driven technologies only. This thesis, in contrast, analyses the innovation-generating behaviour among rural farmers. Specifically, the study looks at the determinants, impacts and identification of farmer innovation. The study is based on primary data obtained from a survey of 409 smallholder farm households in the Upper East region of northern Ghana. Additional data were collected through an innovation contest and a stakeholder workshop conducted in the region. Employing recursive bivariate probit and endogenous treatment-regression models which control for selection bias, it was found that participation in Farmer Field Fora − a participatory extension approach with elements of the innovation systems perspective − is a key determinant of innovation behaviour in farm households. Other important determinants are education, climate shocks and risk preferences. These results are robust to alternative specifications and estimation techniques. The study also found no spillover effect of FFF on farmers’ innovation capacity and discussed its implications. Using endogenous switching regression and propensity score matching techniques, the effect of farmer innovation on household welfare was analysed. The results show that farmer innovation significantly improves both household income and consumption expenditure for innovators. It also contributes significantly to the reduction of food insecurity among innovative households by increasing household food consumption expenditure, reducing the length of food shortages, and decreasing the severity of hunger. However, the findings show that the positive income effects of farmer innovation do not significantly translate into nutritious diet, measured by household dietary diversity. The results also indicate that though households innovate mainly to increase production, their innovations indirectly contribute to building their resilience to climate shocks. Overall, the results show positive and significant welfare effects of farmer innovation. Through an innovation contest that rewards farmers’ creativity and a household survey, 48 outstanding innovations developed by smallholder farmers were identified in the study region. The innovations are largely extensive modification of existing practices or combination of different known practices in unique ways to save costs or address crop and livestock production constraints. While some of the identified innovations can be recommended or disseminated to other farmers, most of them may require further validation or research. The multi-criteria decision making analysis − based on expert judgement ¬− is proposed as a simple and useful method that can be applied in prioritising high-potential innovations. Using this method, it was found that among the most promising innovations involve the control of weeds, pest and diseases using plant residues and extracts, and the treatment of livestock diseases using ethnoveterinary medicines. In conclusion, this study provides empirical evidence that smallholder farmers develop diverse and spectacular innovations to address the myriad challenges they face. These innovations also contribute significantly to household well-being, hence, need to be recognised and promoted. An institutional arrangement that permits interactions and learning among stakeholders may be a potential option for strengthening farmers’ innovation capacity.

The dataset consists of socio-economic data obtained from the survey of 409 farm households in the Bongo, Kassena Nankana East and Kassena Nankana West Districts in Upper East Ghana. It also includes constructed data from the main dataset for the analysis of the drivers and impacts of farmer innovation. A description of all the variables in the data is also included.