Search Results (8)

Land degradation, food and tenure insecurity are significant problems in the northern highlands of Ethiopia, particularly in the region known as the country’s famine corridor. Addressing these twine issues in the region has become a focal point for both local and international organizations, underscoring the significance of preventive measures. Since 2000, the Government of Ethiopia (GoE) has been implementing sustainable land management and certification programs. This study aims on households involved in these programs, specifically in Dessie Zuria and Kutaber Woredas, South Wello Zone (SWZ). The primary objectives of the research were to assess households’ current food security status, identify factors influencing their food security, and classify coping and survival strategies employed by households during food shortages. Primary and secondary sources have been used to collect both qualitative and quantitative data. Quantitative data were collected from surveyed households and analyzed USING SPSS software version 26, whereas qualitative data were transcribed, grouped, and interpreted in line with the aim of the research. Three food security models, namely the Household Food Balance Model, Months of Adequate Household Food Provisioning, and Household Dietary Diversity Score, were employed to evaluate food security. Consequently, a significant percentage of the surveyed households, amounting to 88.3%, 35.6%, and 93.8%, were found to experience food insecurity according to the respective models. Rainfall shortages and variability, crop pests and diseases, shrinking farm plots, and land degradation are among the identified food security determinants. During dearth periods, households deploy a variety of coping and survival strategies. To mitigate food insecurity stemming from both natural and socio-economic factors, the research suggests several recommendations. These include advocating for tenure policy reforms by the GoE, and the local governments should promote the adoption of efficient land management practices, instituting a land certification system based on cadasters, encouraging family planning, boosting investments in education and literacy, raising awareness and providing training in climate-smart agriculture techniques, educating communities on optimal grain utilization, saving, trade, and storage methods, facilitating opportunities for income generation through off-farm and non-farm activities, and offering support for crop and livestock diversification. Full article

Land requirements of wind power (WP) are often seen as a constraint to future broad-scale deployment. The aim of the study is to evaluate the eligibility of abandoned agricultural land (AAL) areas, covered with woody plants, for the development of wind energy (WE) in Lithuania. Agricultural land abandonment (ALA) has numerous negative aspects and its use for WE must be a profitable choice for the landowner, as for the energy developers also. A newly developed methodological approach, a multi-criteria decision-making (MCDM) method known as TOPSIS (the Technique for Order Preference by Similarity to Ideal Solution) was applied to select suitable areas for wind power plants (WPP). The authors have used various data sets, as follows: protected areas (reserves, parks) combined into one common geographic information system (GIS) layer, forest cadaster data, water (lakes, rivers) area layer; abandoned land area layer; buildings layer, taken from the Lithuania Georeferenced Data Base. The results were generated for the entire territory of Lithuania and separately for AAL using the algorithms of the open source QGIS program. The results showed that the central part of Lithuania is most suitable for the development of WE. However, ALA in this part is low, because of the high soil yield potential and suitable conditions for farming. According to the selection criteria, about 7% of AAL are suitable for WE, and more than 18% of AAL have an average suitability. Full article

The present study aims to provide a method for extending the scope of empirical landscape studies into the more distant past and to use it to contribute to the discourse on land degradation in the Mediterranean area. In many areas of the world, the lack of spatially explicit sources, such as historical land cover maps and cadasters, is an obstacle to extending the study of landscape dynamics in the past. Information mined from travelers’ texts can be used to overcome it. Landscape descriptions retrieved from W.M. Leake’s narration of his travels in Peloponnese, Greece, in 1805 and 1806, were georeferenced and used to test for the occurrence of land degradation by comparing historical to current landscapes. A widespread transition of natural vegetation to agricultural areas was found mostly in low altitudes. Limited rewilding occurred on steeper slopes. About a third of the historical Greek fir forests were degraded to open stands. A total of 40% of the locations covered by deciduous oak forests were converted to agricultural areas; most of the rest of these locations were converted to vegetation types characteristic of lower precipitation and soil fertility. Long-term dynamics can be efficiently assessed using narrations as a source of information. The comparison of early 19th century descriptions with the current condition suggests that limited land degradation did take place in the previous centuries in the study area. Full article

This research investigates the reasons of changing the agricultural land use to tourism in a developing country with different political, economic and social context (Iran). The method used in this research is qualitative, and unstructured interviews have been used to collect data. The target population of the research includes farmers who have sold their farmlands to investors in the tourism sector and experts from the agricultural department of the relevant county. The interviewees have been selected through using snowball method and after reaching theoretical saturation, the data collection process was stopped. The results showed that various macro and micro factors affected the process of changing the agricultural land uses to tourism, including the weakness of the agricultural sector in creating income and job opportunities compared to the tourism sector, the weakness of the land use laws and the lack of inter-organizational coordination in law enforcement, the weakness of the property registration system and the lack of a national cadaster, the lack of effective government support of the agricultural sector, the rapid rise in land prices and, ultimately, the change in the attitude of farmers both old and young once towards the agricultural activity and the level of welfare. Full article

Field mapping and information on agricultural landscapes is of increasing importance for many applications. Monitoring schemes and national cadasters provide a rich source of information but their maintenance and regular updating is costly and labor-intensive. Automatized mapping of fields based on remote sensing imagery may aid in this task and allow for a faster and more regular observation. Although remote sensing has seen extensive use in agricultural research topics, such as plant health monitoring, crop type classification, yield prediction, and irrigation, field delineation and extraction has seen comparatively little research interest. In this study, we present a field boundary detection technique based on deep learning and a variety of image features, and combine it with the graph-based growing contours (GGC) method to extract agricultural fields in a study area in northern Germany. The boundary detection step only requires red, green, and blue (RGB) data and is therefore largely independent of the sensor used. We compare different image features based on color and luminosity information and evaluate their usefulness for the task of field boundary detection. A model based on texture metrics, gradient information, Hessian matrix eigenvalues, and local statistics showed good results with accuracies up to 88.2%, an area under the ROC curve (AUC) of up to 0.94, and F₁ score of up to 0.88. The exclusive use of these universal image features may also facilitate transferability to other regions. We further present modifications to the GGC method intended to aid in upscaling of the method through process acceleration with a minimal effect on results. We combined the boundary detection results with the GGC method for field polygon extraction. Results were promising, with the new GGC version performing similarly or better than the original version while experiencing an acceleration of 1.3× to 2.3× on different subsets and input complexities. Further research may explore other applications of the GGC method outside agricultural remote sensing and field extraction. Full article

In recent decades, Russia has experienced substantial transformations in agricultural land tenure. Post-Soviet reforms have shaped land distribution patterns but the impacts of these on agricultural use of land remain under-investigated. On a regional scale, there is still a knowledge gap in terms of knowing to what extent the variations in the compositions of agricultural land funds may be explained by changes in the acreage of other land categories. Using a case analysis of 82 of Russia’s territories from 2010 to 2018, the authors attempted to study the structural variations by picturing the compositions of regional land funds and mapping agricultural land distributions based on ranking “land activity”. Correlation analysis of centered log-ratio transformed compositional data revealed that in agriculture-oriented regions, the proportion of cropland was depressed by agriculture-to-urban and agriculture-to-industry land loss. In urbanized territories, the compositions of agricultural land funds were predominantly affected by changes in the acreage of industrial, transportation, and communication lands. In underpopulated territories in the north and far east of Russia, the acreages of cropland and perennial planting were strongly correlated with those of disturbed and barren lands. As the first attempt at such analysis in Russia, the conversion of cadastral classification data into land-rating values enabled the identification of region-to-region mismatches between the cadaster-based mapping and ranking-based distribution of agricultural lands. Full article

The Mediterranean Basin is at the same time a region of stark social and ecological contrasts and a global biodiversity hotspot, where complex local evolving land use and land cover patterns compose the region’s landscapes. In this context, we aimed for a specific case study of the southeast of France, to assess land and farming systems’ dynamics, to identify their underlying drivers, and to propose possible shared future scenarios for local policies’ implementation. We based our analyses on a mixed approach and operated at downscale from territorial to local scale. First, we applied a quantitative statistical approach for the Vaucluse department. Then, we identified a subzone of the study area and pursued a local analysis through a qualitative and participative approach based on stakeholders’ knowledge. The study highlighted two main dynamics in land and farming systems that involve several changes. The first one is a process of land abandonment, strongly connected to a peri-urbanization process in some areas or to the loss of traditional farming systems in others. The second one is a process of specialization, at both territorial and farm levels, that corresponds to an intensification process and is linked to vineyards’ expansion dynamic with a landscape homogenizing effect. Full article

Urban agriculture in Global North cities is strongly promoted as a sustainable solution to achieve different goals, such as food production, quality of life, and well-being. Although several attempts have been made to evaluate urban agriculture production, few studies have investigated food production in a multitemporal geospatial way and considered per capita population needs, gender, and age strata consumption. This study presents a spatiotemporal quantification of urban agriculture in the city of Milan (Italy) for assessing food self-provisioning potential. We utilized high-resolution Google Earth images and ancillary data to create a detailed cadaster of urban agriculture for the years 2007 and 2014. Based on four scenarios of food production and statistical data on vegetables and cereals consumption, we estimated current total production and requirements for the city dwellers. Our results showed that the actual extension of vegetable gardens (98 ha) and arable land (2539 ha) in the best scenario could satisfy approximately 63,700 and 321,000 consumers of vegetables and cereal products, respectively. Overall, current urban agriculture production is not able to meet vegetables and cereal consumption for more than 1.3 million city residents. Scenario estimates suggest rethinking land use promoting horticultural production to achieve more sustainable food systems. Full article