Map is the basic language of geography and an indispensable tool for spatial analysis. But for a long time, maps have been regarded as an objective and neutral scientific achievement. Inspired by critical geography, critical cartography/GIS came into being with the goal of clarifying the discourse embedded in cartographic practice. Power relationship challenges the untested assumption in map representation that is taken for granted. After more than 40 years of debate and running in, this research field has initially shown an outline, and critical cartography/GIS has roughly formed two research directions: the deconstruction path mainly starts from the identity of cartography subject and the process of map knowledge production, and analyzes the inseparable relationship between cartography and national governance and its internal power mechanism respectively; the construction path mainly relies on cooperative mapping and anti-mapping to realize the reproduction of map data. Domestic critical cartography/GIS research has just started, and it is necessary to continue to absorb the achievements of critical geography and carry out research in different historical periods. The deconstruction research of different types of maps also needs to strengthen the in-depth bridging between the construction path and the deconstruction path, and to be more open to the public. Impartial map application research, and actively apply the research results to social practice.

Malaria is a mosquito-borne infectious disease that affects humans and poses a severe public health problem. Nigeria has the highest number of global cases. Geospatial technology has been widely used to study the risks and factors associated with malaria hazards. The present study is conducted in Ibadan, Oyo State, Nigeria. The objective of this study is to map out areas that are at high risk of the prevalence of malaria by considering a good number of factors as criteria that determine the spread of malaria within Ibadan using open-source and Landsat remote sensing data and further analysis in GIS-based multi-criteria evaluation (MCE). This study considered factors like climate, environmental, socio-economic, and proximity to health centers as criteria for mapping malaria risk. The MCE used a weighted overlay of the factors to produce an element at-risk map, a malaria hazard map, and a vulnerability map. These maps were overlaid to produce the final malaria risk map, which showed that 72% of Ibadan has a risk of malaria prevalence. Identification and delineation of risk areas in Ibadan would help policymakers and decision-makers mitigate the hazards and improve the health status of the state.

 Distance education (DE) has recently become a noteworthy study topic in the public education system. From the Web of Science database, 5719 articles discussing DE and published in the period of 2011–2023 were acquired. By analyzing the overall characteristics, co-citation, and keyword co-occurrence of the selected articles, which utilized Cite Space software, the history of DE could be systematically grasped, thereby reasonably predict the emphases of future development. We found that the number of papers relevant to DE had been rapidly growing since 2018. USA, China, and Turkey are the top three countries where most authors or teams were located. The map of keyword cooccurrence showed that the previous DE research mainly focused on telelearning, adult learning, and distributed learning environment. The recent burst words emerging are used to determine that distance education will continue to be studied in the field with high explosive keywords such as visual tracking, technology acceptance model, and user interface. This will provide suggestions and directions for the development of distance education.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

Creative cities as a study discipline have garnered extensive attention and research in theory and practice as a practical approach to urban revitalization and sustainable development. This study conducted a systematic review of academic research on creative cities. Utilizing the visual analysis tools Citespace and VOSviewer, a comprehensive analysis was performed on 570 relevant articles from the Web of Science database. This study analyzed the most influential publications, authors, journals, institutions, and countries within the sample. The investigation spans various disciplinary domains, including geography, environment, culture, and others. Additionally, an exploration of the structure and characteristics of co-cited references was undertaken to enhance our understanding of the theoretical foundations of creative cities research further. Among these, the focal points of the study encompass urban development, urban policies, and the challenges faced. Finally, through co-occurrence analysis of keywords and examining the evolutionary process, the study forecasted that future trends will focus on the practical application of cities to enhance the urban image and improve urban governance from multi-dimensional perspectives such as creativity-related cultural places, public art, and so forth, exploring novel models of creative cities from case to universal. The results of this study can support scholars in grasping the development trends and exploring focal points.

This study analyses the dynamic development of soybean (Glycine max (L.) Merr.) breeding in Russia, particularly examining its historical development, status, and future predictions. With the global demand for vegetable protein rising, understanding Russia’s potential contribution becomes crucial. This research provides valuable insights, offering precise data that may be unfamiliar to international researchers and the private sector. The authors trace the history of soybean selection in Russia, emphasizing its expansion from the Far East to other regions in Russia. The expansion is primarily attributed to the pioneering work of Soviet breeder V. A. Zolotnitsky and the development of the soybean variety in the Amur region in the 1930s. The study highlights the main areas of soybean variety originators, with approximately 40% of foreign varieties registered. The Krasnodar and Amur regions emerge as critical areas for breeding soybean varieties. In Russia, the highest yield potential of soybeans is in the Central Federal District. At the same time, the varieties registered in the Volga Federal District have higher oil content, and the Far Eastern Federal District has high protein content in the registered soybean varieties. The research outlines the state’s pivotal role in supporting soybean breeding and fostering a competitive market with foreign breeders. The study forecasts future soybean breeding development and the main factors that can influence the industry.