Investigating the impact of urban growth on land use using spatial autocorrelation methods in Konya/Türkiye.

Land use land cover (LULC) change, global environmental change, and sustainable change are frequently discussed topics in research at the moment. It is important to determine the historical LULC change process for effective environmental planning and the most appropriate use of land resources. This study analysed the spatial autocorrelation of the land use structure in Konya between 1990 and 2018. For this, Global and Local Moran's I indices based on land use data from 122 neighbourhoods and hot spot analysis (Getis-Ord Gi*) methods were applied to measure the spatial correlation of changes and to determine statistically significant hot and cold spatial clusters. According to the research results, the growth of urban areas has largely destroyed the most productive agricultural lands in the region. This change showed high spatial clustering both on an area and a proportional basis in the northern and southern parts of the city. On the other hand, the growth in the industrial area suppressed the pasture areas the most in the north-eastern region of the city, and this region showed high spatial clustering on both spatial and proportional scales.

Prioritization of land consolidation projects using the multi-criteria Best-Worst Method: a case study from Poland.

In order to balance the needs of ecology, environment, and agricultural productivity with the aim of revitalizing rural areas, every local government unit that plans to implement a land consolidation (LC) project should decide where to start these projects as a priority. Traditionally, some of these decisions are made by groups of people connected to the consolidated area, while the others are made by groups of people from government departments, all trying to make the best possible decision. However, one of the most important conditions for the successful implementation of these projects, requiring large investment costs is, determining the priority areas for LC projects and allocating the investments to the appropriate areas meticulously. This study proposed a new model for determining priority areas for LC projects. In this study, by determining a set of criteria according to the parameters taken from 75 villages (Malopolska region, Poland), a model was developed for prioritizing LC projects using the Best-Worst Method (BWM), a multi-criteria decision-making (MCDM) method. The proposed model enables the transparent identification and prioritization of villages for land consolidation by national and local authorities, effective management of resources, and equitable allocation of financial assistance.

Impact of land consolidation on agricultural decarbonization: Estimation of changes in carbon dioxide emissions due to farm transport.

Areas used for agriculture are a large source of carbon emissions, but there is great potential for reducing them. Land consolidation, through the comprehensive reorganization of the spatial arrangement of farms, can reduce emissions as a result of reducing fuel consumption. The subjects of this study are the veracity of this statement and the scope of variation in the potential reduction of carbon emissions. The analysis covered six land consolidation projects in Poland and Turkey, for several agricultural models that differ in the level of fuel consumption. Changes in agricultural road layout resulting from the implementation of land consolidation projects and changes in the number of farm plots and their spatial distribution were considered. The study considered several different levels and structures of fuel consumption on farms. The applied methodology is based on analysis of changes in distance to fields resulting from land consolidation projects, which are then expressed as changes in fuel consumption. The obtained emission reduction results for the studied land consolidation projects were diverse and range from 0.3 to 170 kg CO2/ha/year. The reduction in fuel consumption on farms at the level of individual villages reached a maximum of 32 %, while the average value of this reduction in the entire surveyed set was 12.5 %. The proposed approach increases the accuracy of existing methods for estimating the long-term balance of carbon emissions and carbon accumulation related to the implementation of land consolidation projects. The observed emission reduction values can be considered a significant economic and ecological effect because the effects of these projects persist for at least several decades.