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Copyright of South Architecture / Nanfang Jianzhu is the property of South Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The primary objective of this study is to investigate the carbon footprint, resilience levels, and optimal landscape area ratios of various parks. Additionally, it explores the relationships between landscape element proportions (LEP), the normalized difference vegetation index (NDVI), resilience indicators (RI), and the carbon reduction benefits associated with carbon neutrality (CN). Six parks were assessed for resilience, NDVI, LEP, and CN values, with Pearson correlation analysis conducted. The results revealed that parks with or without waterbodies exhibited ideal LEP area ratios of 6.5:2:1.5 (Softscape:Waterbody:Hardscape) and 8.3:1.7 (Softscape:Hardscape), respectively. Enhanced Softscape and reduced Hardscape proportions in parks correlated with increased NDVI and CN. NDVI exhibited a positive correlation with Softscape percentage and a negative correlation with Hardscape percentage. Conversely, CN demonstrated a negative correlation with Hardscape percentage and a positive correlation with Softscape percentage. Suggesting Softscape should constitute over 65%, and Hardscape should be under 15% in parks with water bodies. Waterless parks are advised to maintain a Softscape ratio exceeding 83% and a Hardscape ratio below 17%. Finally, the study extended to assess the LEP of 22 additional parks, validating the suitability of the ideal LEP area ratio. [ABSTRACT FROM AUTHOR]

Rural landscapes are acknowledged for their potential to restore human health due to natural characteristics. However, modern rural development has degraded these environments, thereby diminishing the restorative potential of rural landscapes. Few studies have systematically analyzed the impact of naturalness, landscape types, and landscape elements on restorativeness using both subjective and objective measurements. This study investigated the restorative effects of various rural landscapes in Guangzhou, employing electroencephalography and eye-tracking technologies to record physiological responses and using the Restorative Components Scale and the Perceived Restorativeness and Naturalness Scale to evaluate psychological responses. The results indicated the following: (1) There was a significant positive correlation between perceived naturalness and restorativeness, surpassing the impact of actual naturalness. (2) Different landscape types had varying impacts on restorativeness at the same level of perceived naturalness. Natural forest landscapes, artificial forest landscapes, and settlement landscapes exhibited the most substantial restorative effects among the natural, semi-natural, and artificial landscapes examined, respectively. (3) Restorative properties varied across landscape elements: trees and water significantly enhanced restorativeness, whereas constructed elements reduced it. Findings from this study can provide support for policymakers to make informed decisions regarding the selection and arrangement of rural landscape types and elements to enhance mental health and well-being. [ABSTRACT FROM AUTHOR]

Due to the increased demand for agricultural products, the agricultural industry has become intensified, resulting in a homogenization of the rural landscape. Our study defines rural landscape types at three scales (national, regional, and local) using a multi-scale method. We generated three landscape element datasets using literature and gray statistical analysis. Subsequently, we used the overlay approach and two-step cluster analysis to identify landscape regions, types, and subtypes. The findings indicate the presence of 47 landscape regions at the national scale, 448 landscape types at the regional scale, and 44 landscape subtypes at the local scale with Dahongshan Mountain Region serving as the empirical study site. Furthermore, we have developed a novel method to evaluate landscape diversity index (LDI) which utilizes the proportion of land area occupied by landscape elements in various landscape types. This method incorporates diverse elements, such as topography, landform, land cover/use, vegetation, and agroforestry industries. To examine the role of LDI in landscape planning, we analyzed the relationship between LDI and recreation services using the geographically weighted regression model. The result facilitates landscape planning and management at different administrative levels.Article Highlights: Definition of landscape regions, types, and subtypes at multiple scales through overlay method and two-step cluster analysis method. An assessment approach of landscape diversity was carried out using data from the agricultural and forestry industries, topography and landform, land cover and use, and other elements. The GWR regression model of LDI and RS provides a potential use of LDI. This broadly applicable strategy and its results enable landscape monitoring and policy implementation at all scales, from the national to the regional to the local. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to investigate the carbon footprint, resilience levels, and optimal landscape area ratios of various parks. Additionally, it explores the relationships between landscape element proportions (LEP), the normalized difference vegetation index (NDVI), resilience indicators (RI), and the carbon reduction benefits associated with carbon neutrality (CN). Six parks were assessed for resilience, NDVI, LEP, and CN values, with Pearson correlation analysis conducted. The results revealed that parks with or without waterbodies exhibited ideal LEP area ratios of 6.5:2:1.5 (Softscape:Waterbody:Hardscape) and 8.3:1.7 (Softscape:Hardscape), respectively. Enhanced Softscape and reduced Hardscape proportions in parks correlated with increased NDVI and CN. NDVI exhibited a positive correlation with Softscape percentage and a negative correlation with Hardscape percentage. Conversely, CN demonstrated a negative correlation with Hardscape percentage and a positive correlation with Softscape percentage. Suggesting Softscape should constitute over 65%, and Hardscape should be under 15% in parks with water bodies. Waterless parks are advised to maintain a Softscape ratio exceeding 83% and a Hardscape ratio below 17%. Finally, the study extended to assess the LEP of 22 additional parks, validating the suitability of the ideal LEP area ratio.

Rural landscapes are acknowledged for their potential to restore human health due to natural characteristics. However, modern rural development has degraded these environments, thereby diminishing the restorative potential of rural landscapes. Few studies have systematically analyzed the impact of naturalness, landscape types, and landscape elements on restorativeness using both subjective and objective measurements. This study investigated the restorative effects of various rural landscapes in Guangzhou, employing electroencephalography and eye-tracking technologies to record physiological responses and using the Restorative Components Scale and the Perceived Restorativeness and Naturalness Scale to evaluate psychological responses. The results indicated the following: (1) There was a significant positive correlation between perceived naturalness and restorativeness, surpassing the impact of actual naturalness. (2) Different landscape types had varying impacts on restorativeness at the same level of perceived naturalness. Natural forest landscapes, artificial forest landscapes, and settlement landscapes exhibited the most substantial restorative effects among the natural, semi-natural, and artificial landscapes examined, respectively. (3) Restorative properties varied across landscape elements: trees and water significantly enhanced restorativeness, whereas constructed elements reduced it. Findings from this study can provide support for policymakers to make informed decisions regarding the selection and arrangement of rural landscape types and elements to enhance mental health and well-being.

This study aimed at revealing the subjective thermal comfort intervention of landscape elements in the humid and subtropical residential area of China. Data based on physical measurements and questionnaire surveys were collected. A new empirical model was developed according to microclimatic and subjective criteria, which considers air temperature, solar radiation, and wind speed. According to the empirical model in summer, a decrease of 84 W/m2 in global radiation or an increase of 0.35 m/s in wind speed would have the same effects on thermal perception as a drop of 1 °C in air temperature. A similar analysis could be conducted with the winter model, a change of 20 W/m2 in global radiation or a change of 0.10 m/s in wind speed have the same effects as a change of 1 °C in air temperature. Furthermore, the thermal comfort intervention of tree, shrubs, reflective surface and pervious ground were quantitatively analyzed based on the empirical model. We proposed that large broad-leaved trees and pervious ground were more conducive to the improvement of thermal acceptability during different seasons. The results showed that in summer, the total acceptable area significantly increased by 38.5%, whereas it was slightly reduced by 8.4% in winter.

Copyright of Journal of Social Sciences Research / Sosyal Bilimler Arastirmalari Dergisi is the property of ODU Journal of Social Sciences Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Measured 22 subjective perception scores from street-view images. • Model considers the relationships among all subjective perception evaluation items. • Modeled subjective perceptions with high accuracy and low computation cost. • The 22 subjective perceptions were classified into four classes (attractive, old-fashioned, calm, and lively) • Identified landscape elements that affect each subjective perception class. Developing a model to evaluate urban streetscapes based on subjective perceptions is important for quantitative understanding. However, previous studies have only considered limited types of subjective perceptions, neglecting the relationships between them. Further, accurately measuring subjective perception with low computational costs for large-scale urban regions at high spatial resolutions has been difficult. We present a deep-learning-based multilabel classification model that can measure 22 subjective perceptions scores from street-view images. This model uses the results of a web questionnaire survey encompassing 22 subjective perceptions, with 8.8 million responses. Our model demonstrates high accuracy (0.80–0.91) in measuring subjective perception scores from street-view images and achieves low computational cost by training on 22 subjective perception relationships. The 22 subjective perceptions were analyzed using PCA and k-means analysis. By categorizing the 22 subjective perceptions into a two-dimensional space visualized and grouped into distinct groups—positive, negative, calm, and lively—we unearthed vital insights into the intricate nuances of human perception. In addition, the study used semantic segmentation to extract landscape elements from street-view images and applied ℓ1-regularized sparse modeling to identify the landscape elements structurally correlating with each subjective perception class. The analysis revealed that only seven out of nineteen landscape elements significantly correlated with subjective impressions, and these effects varied by class. Notably, sky coverage positively influences positive subjective perceptions, such as attractiveness and calmness, but negatively affects lively impressions. The proposed model can be used to map the overall image of a city and identify landscape design issues in community development design. [ABSTRACT FROM AUTHOR]

Natural environments contribute to people's perception, preference and health restoration. Many researchers have focused either on the positive effects of overall rural environments on stress recovery or concentrated on the perception and preference aspects of the rural landscape, but few have integrated perception, preference and stress recovery simultaneously. This paper developed a framework which includes 11 elements and 38 element components related to Linpan, China, and distributed it online as part of a survey. As a result, a total of 324 valid questionnaires were collected. The questionnaire included demographic details, perception and preference degree for Linpan, as well as self-estimations of stress recovery. Stepwise multiple linear regression was employed, and revealed 16 significant predictors for the perception, preference and stress recovery in rural environments. In terms of elements, atmosphere and imagery were the two elements that could be best perceived, while woodland, farmland, water, residence and road were the five most important elements for the preference. Moreover, seven elements were also identified as significant predictors for stress recovery. Among the element components, tranquility as well as road and water proximity were the two significant predictors for perception, while wide visibility as well as woodland and residence blending contributed significantly to stress recovery. The five element components of woodland interior, vegetable field, stream, courtyard space and branch road each had a significantly predictive ability for preference and stress recovery. These findings extend the understanding of the perception, preference and restorative properties of rural environments through the combination of elements and element components in Linpan of Western Sichuan, helping to improve the quality and characteristics of rural external and internal environments and create health-promoting environments. [ABSTRACT FROM AUTHOR]

Agricultural non-point source pollution is a major ecological environment issue that seriously affects water safety. A new perspective based on the coupling effects of agricultural spatial-pattern and landscape elements to enhance the ecological function of the agricultural ecosystem and reduce non-point pollution risk was discussed in this study. Firstly, landscape connectivity and landscape heterogeneity should be emphasized to optimize the spatial pattern. Measures such as the building of wetlands, ecological islands, and collecting basins should be fully considered not only to improve animal diversity, strengthen ecological system stability, and reduce chemical pesticide input but also to adsorb and resist the migration of agricultural non-point pollution such as nitrogen and phosphorus,thereby realizing the multi-level utilization of nutrients and extending the space migration way of non-point source pollution. Secondly, enhancing the ecological function of landscape elements was suggested to control non-point pollution. Increasing the proportion of semi-natural habitat areas, as well as building ecological ditches and pre-storages, was suggested for varying conditions. To fully consider the coupling function of spatial-pattern and landscape elements in reducing chemical fertilizer and pesticide inputs, agricultural measures such as rational fertilization, compost, rotation and intercropping, and biological control were also suggested. Finally, we took the organic farm in the Songhua dam area as an example to expound the coupling effects of these measures. The animal species were significantly increased and the agriculture service function was elevated; moreover, nitrogen, phosphorus, and pesticide loss were reduced by 820~1093kg·hm-2, 273~364kg·hm-2, and 2.2~2.5kg·hm-2, respectively. [ABSTRACT FROM AUTHOR]

The standards of society with regard to agricultural land use have risen during the course of time. A method of management is increasingly being demanded that, alongside the production of food, also benefits the environment and society. Alley cropping agroforestry systems can make a contribution to supporting this demand, since they offer many environmental advantages and also enhance the landscape. In Germany, alley cropping systems in agriculture have only been of low-level importance, since the scale of planting has been restricted to just a few test areas. The reasons for the reticence among farmers to implement alley cropping are likely to lie in the economic disadvantages of agroforestry compared to full area field cultivation. With the aid of financial support, incentives could be created that encourage farmers to establish agroforestry systems. However, potential subsidies should be provided that take into account societal preferences, in order to be able to publicly legitimise them. The aim of this article is therefore to analyse and quantify the level of willingness to pay and its determining factors from the perspective of German taxpayers. To achieve this aim, a complex socio-economic research model has been developed on the basis of the contingent evaluation method and concepts for consumer awareness of sustainably produced food products. The primary data collected on the basis of this research framework from 1714 taxpaying individuals living in Germany was evaluated using descriptive statistics, t-tests, and the partial least squares (PLS) method. The descriptive results show that 65.1% of the respondents have an additional willingness to pay. Of the remaining respondents who were not willing to pay, 75.7% regard agroforestry systems as being useful, but are not willing to pay higher amounts of tax to subsidise them. Throughout the entire sample, an average willingness to pay of €36.59 (~ US$38.79) per year emerges. Furthermore, the majority of respondents regarded the fulfilment of environmental and nature conservation measures as being the responsibility of agriculture, and the subsidisation of these measures as being the responsibility of the government. The PLS model showed that the assessment regarding secondary tasks of agriculture, including the implementation of environmental and nature conservation measures and the provision of renewable raw materials, has a positive influence on taxpayers' willingness to pay for environmental improvement through agroforestry systems. Based on these results, a wide range of implications are derived for policy makers, farmers, and various advocacy groups. [ABSTRACT FROM AUTHOR]

The research examines the effects of agricultural subsidies on the landscape structure. According to the hypothesis, greening – which has been introduced as part of the European Union’s Common Agriculture Policy (EU CAP) reform –, if it is properly controlled and applied, can be a suitable tool for habitat network development. Landscape elements eligible for greening can function as significant landscape structural elements, and can promote the achievement of goals e.g. in the preservation of biodiversity. As part of this research, field surveys were performed in 2016 and 2017 in the Great Hungarian Plain, where significant landscape elements were assessed and documented in the sample area. During the research, Shape Index and Fractal Dimension Index values for polygonal elements were calculated based on their current extensions in 2016 and in 2017. In line with my basic hypothesis, eligible landscape elements (such as hedgerows, stonewalls, shadoofs and infield trees) do not possess extraordinary ecological values, nor can their persistence be guaranteed solely with greening subsidies. Therefore, they may also not be able to fill their role in the protection of landscape structure and biodiversity in the long term.

• We proposed a stepwise procedure to identify landscape elements and perceptions. • Multiple elements collectively affect vision, hearing and smell perception. • Touch and taste perception have pronounced association with specific elements. • We advocated perceptual improvement based on landscape elements. Challenges remain when assessing cultural ecosystem services (CES) due to the subjective and intangible features. Landsense ecology highlights the individual perception, providing a novel dimension to the CES assessment. Based on landsense ecology, this study aims to identify and correlate landscape elements and sensory perceptions using social media data. Taking the case of Belgian greenspaces, the factors were identified using custom lexicons through unsupervised and weakly supervised learning methods. The perception correlation network was established to link sensory perceptions with landscape elements. Integrating data from different platforms, we found that social elements were perceived frequently and that the most significant perceptions were vision and touch. Results also revealed that the perceptions of vision, hearing and smell were collectively affected by multiple elements, while the perceptions of taste and touch were strongly related to specific elements. Finally, this study encouraged creating multi-sensory spaces in greenspace management. [ABSTRACT FROM AUTHOR]

Nature and landscape protection has gained importance over the past 50 years from the economic, cultural, health, and recreational point of view. The process is closely linked to our civilizational endeavours (such as economic interests, pollution, urbanization, super-intensive agriculture, etc.) that threaten our natural values as well as to the ever more frequent environmental disasters resulting from the above. The continued destruction of our natural and landscape values is not reversible. The aim of this article is to determine the important and urgent professional tasks regarding exploring, documenting, safeguarding, and raising awareness of values. My work wishes to draw attention to the landscape values and deficiencies of Transylvania, working with examples from other countries; by using Romanian examples, I also wish to support my assumption according to which if we want to preserve unique landscapes on the European level we need to act quickly.