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Summary: Accurate acquisition of cultivated land information is important for agricultural management, agro-ecological environment monitoring, and national food security. This study uses the U-Net semantic segmentation model in deep learning to extract cultivated land information by designing different model training experiments with various parameter combinations. The results show that the patch size has the greatest influence on classification accuracy, and selecting reasonable combinations of bands, backbone models, patch size, epoch, and sample categories can improve the accuracy of predicted results. Additionally, the appropriate patch size for cultivated land extraction is between 224 x 224 pixels and 256 x 256 pixels, and multi-classification is more effective than binary classification.
ECOLOGICAL INDICATORS
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Amy Phillips et al.
Summary: As cities become more populated, the importance of urban green spaces (UGS) is increasing. In this paper, the researchers use spatial analysis to explore the differences in UGS usage, choice, and satisfaction based on usage patterns and place of residence. They also identify the factors that attract or repel individuals from using UGS. The findings reveal the relationship between usage patterns and UGS choice and experience, as well as the impact of disadvantaged groups on UGS usage and satisfaction.
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Zhiming Li et al.
Summary: Evaluating park equity can help guide the advancement of sustainable and equitable space policies. Previous studies focused mainly on accessibility, ignoring selectivity, convenience, and residents' recognition. This study integrated spatial and social equity, developing a multidimensional framework to evaluate park equity and reduce inequality in park access.
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George Halkos et al.
Summary: This study assesses the factors influencing the economic value of visitor experience in urban parks in Attica, Greece. The results indicate that age, education level, wage, and employment status have an impact on people's willingness to pay for park visits. Additionally, motivations for visiting, expenses, and previous experiences with entry tickets also play a significant role in decision making. The average willingness to pay for entry into urban parks is 3.56 Euros.
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Summary: Urban green space planning and design have a significant impact on economic development, ecological environment, and urban public health. Promoting environmental justice in urban green space and improving the health and well-being of urban residents are critical issues to be addressed within the context of global urban sustainable development goals.
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LANDSCAPE AND URBAN PLANNING
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Chao Xu et al.
Summary: The study finds that increasing the amount of urban green space (UGS) can help reduce the average land surface temperature (LST) in cities, and promoting the spatial equity of UGS distribution can reduce the spatial aggregation of LSTs within urban areas, thereby improving the urban thermal environment.
SCIENCE OF THE TOTAL ENVIRONMENT
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Ylenia Casali et al.
Summary: This paper conducts a scoping review of machine learning studies that utilize geospatial data to analyze urban areas. It identifies the most prominent topics, data sources, ML methods, approaches to parameter selection, patterns, and challenges in the use of machine learning. Furthermore, it highlights knowledge gaps in ML methods for spatial data science and data specifications to guide future research.
SUSTAINABLE CITIES AND SOCIETY
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Tianhan Lan et al.
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SUSTAINABLE CITIES AND SOCIETY
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Shiliang Su et al.
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Dong Liu et al.
Summary: Urban green space has positive impacts on physical and mental health, but studies suggest disparities in access to UGS among different racial/ethnic and income groups. White-majority census tracts generally have better UGS accessibility compared to minority-dominated tracts, with black-majority tracts having higher accessibility than Hispanic-majority tracts. There is also income-based UGS accessibility inequality within racial/ethnic groups, with the most inequity found in black-majority census tracts.
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