The accurate evaluation of crop damage by wild animals is crucial for farmers when seeking compensation from insurance companies or other institutions. One of the game species that frequently cause crop damage in Europe is the wild boar, which often feeds on maize. Other game species, such as roe deer and red deer, can also cause significant crop damage. This study aimed to assess the accuracy of crop damage evaluation based on remote sensing data derived from unmanned aerial vehicles (UAVs), especially a digital surface model (DSM) based on RGB imagery and NDVI (normalized difference vegetation index) derived from multispectral imagery, at two growth stages of maize. During the first growth stage, when plants are in the intensive growth phase and green, crop damage evaluation was conducted using both DSM and NDVI. Each variable was separately utilized, and both variables were included in the classification and regression tree (CART) analysis, wherein crop damage was categorized as a binomial variable (with or without crop damage). In the second growth stage, which was before harvest when the plants had dried, only DSM was employed for crop damage evaluation. The results for both growth stages demonstrated high accuracy in detecting areas with crop damage, but this was primarily observed for areas larger than several square meters. The accuracy of crop damage evaluation was significantly lower for smaller or very narrow areas, such as the width of a single maize row. DSM proved to be more useful than NDVI in detecting crop damage as it can be applied at any stage of maize growth.

This study comprehensively analyzed the dynamic landscape of organic farming in the European Union (EU) from 2004 to 2021, investigating the shifts in dedicated agricultural areas influenced by evolving preferences and the priorities of farmers and consumers. Examining the impact of socio-economic factors, including gross domestic product (GDP) per capita, the human development index (HDI), and human population density, this study established multivariate relationships through country-level analyses based on correlations, principal component analysis, cluster analysis, and panel analysis. Despite a universal increase in the organic agriculture areas across all the EU countries during the study period, the production levels exhibited negative correlations with the human population density, GDP per capita, and HDI. Notably, the Baltic countries and Austria led in organic farming production, while Malta, the Netherlands, Belgium, Ireland, and Luxemburg formed a distinct group in the cluster analysis with less intensive organic agriculture per capita. These insights are crucial for supporting the resilience and sustainability of organic farming as it continues to evolve. Predictions of organic agriculture share for 2030 based on trends evaluated using linear regression in the years 2004–2021 estimated about 12% of utilized agricultural area, which was much lower than the target share of the European Commission at 25%. Predictions based on linear regression showed that achieving the European Green Deal target of a 25% share of organic agriculture in unlikely in most EU countries by 2030. The target is only highly probable to be obtained in Austria, Estonia, and Sweden. The EU countries varied significantly across various indices characterizing organic agriculture, including organic agriculture area share. It should be noted that the study was conducted on the data obtained prior to the outbreak of the war in Ukraine, which could potentially alter the previous trends in the development of organic agriculture in the EU.

The revitalization of small towns is connected with an attempt to find multidirectional solutions to numerous social, economic and spatial problems. It is possible to remove degraded areas and areas with a high risk of social exclusion through coordinated and skillfully planned activities consisting of corrective interventions within these areas and, indirectly, in the whole structure of a small town. There are many studies on improving the quality of life of inhabitants at risk of exclusion in large cities. At the same time, there is a gap in the analyses of this phenomenon in small towns. In this article, we present the results of our observations on changes in the quality and living conditions of residents as a result of social projects implemented as part of the revitalization of marginalized areas in cities associated with the Cittaslow movement. The starting point is to identify the main socioeconomic problems and relate them to the effects of the revitalization activities carried out under the Supralocal Revitalization Program (SLRP). The study analyzed all projects that were a response to social problems in fourteen cities in the Warmian-Masurian Voivodeship (Poland). It was based on a quantitative assessment of the selected socioeconomic indicators and a qualitative assessment based on interviews with local experts. The results of the research indicate a reduction in unemployment in all the cities covered by the study. On the other hand, the results of the expert interview show that it is not directly influenced by the implemented revitalization projects. According to experts, after revitalization, the crime rate decreased insignificantly and the educational and professional involvement of residents from marginalized areas is still low. The results may give rise to the creation of scenarios to deal with the socioeconomic problems of the analyzed examples and recommendations for the revitalization of other Cittaslow towns in the region as well as small towns in Europe and the world.

Sustainable agriculture and active collaboration between farmers are important concepts that have a significant impact on the development of sustainable agriculture, in striving for social and economic development, as well as supporting the reduction of impact to environment. Based on a systematic and comparative analysis, this study highlights the role of collaboration towards developing sustainable agriculture. The overall results imply that more active farmers collaboration requires more active sharing of experience, knowledge and information through meetings or seminars by creating an information portal or platform. These measures could lead to more qualitative communication, more open information sharing, mutual trust and risk reduction, which would ensure the development of sustainable agriculture.

Methane (CH₄) emissions from agricultural sources contribute significantly to the total anthropogenic greenhouse gas emissions, which cause climate change. According to the guidelines of the International Panel on Climate Change (IPCC) for calculating greenhouse gas emissions, agriculture is responsible for approximately 10% of total CH₄ emissions from anthropogenic sources. CH₄ is primarily emitted from livestock farming, particularly from cattle production during enteric fermentation and from manure. This article describes the results of multivariate statistical analyses carried out on data collected from 1961 to 2020 for thirty countries with the largest cattle populations. The study evaluated the trends in temporal changes in cattle populations and identified groups of countries with similar patterns during the study period. The global cattle population was highly correlated with CH₄ emissions from the enteric fermentation of cattle and their manure. The countries experiencing the largest increase in cattle population were primarily developing countries located in South America, Africa and Southeastern Asia. The cattle population in these countries showed a strong correlation with the human population. On the other hand, the countries where the cattle population remained stable during the study period were mainly highly developed countries. The correlations between most of the examined variables associated with cattle production and the cattle population in these countries were inconsistent and relatively weak. In the near future, further increase in the cattle population and the associated CH₄ emissions are expected, mainly in developing countries with high population growth.

The aim of the study is the evaluation of land cover changes in selected areas next to three lagoons (the Curonian Lagoon, the Vistula Lagoon and the Szczecin Lagoon) located on the southern coast of the Baltic Sea (in Lithuania, Russia, Poland and Germany) from 1984 to 2021. The changes are evaluated using multispectral (visible light—RGB and near infrared—NIR) satellite images from the Landsat 5 and Sentinel-2 sensors. Due to their high importance for ecosystem services, two main land cover types are evaluated, i.e., forest area and inland water reservoirs. The classification of the images is performed using a random forest algorithm. Areas of water bodies and forests are evaluated for the years 1984 and 2021. During period 1984–2021, positive changes in land cover are observed in all three regions included in the study. In almost all parts, with the exception of the Polish part of the area located next to the Szczecin Lagoon, of these regions, an increase in forest area is observed. The increase ranges from 0.1% (Poland, area next to the Vistula Lagoon) to 1.2% (Germany, area next to the Szczecin Lagoon). The area of inland water reservoirs has not changed significantly in the long term. Despite the global warming, no reduction in the area of these water reservoirs is observed, even new seminatural reservoirs have been created in some parts of the study area.