Enhancing urban blue-green landscape quality assessment through hybrid genetic algorithm-back propagation (GA-BP) neural network approach: a case study in Fucheng, China.

This study employs an artificial neural network optimization algorithm, enhanced with a Genetic Algorithm-Back Propagation (GA-BP) network, to assess the service quality of urban water bodies and green spaces, aiming to promote healthy urban environments. From an initial set of 95 variables, 29 key variables were selected, including 17 input variables, such as water and green space area, population size, and urbanization rate, six hidden layer neurons, such as patch number, patch density, and average patch size, and one output variable for the comprehensive value of blue-green landscape quality. The results indicate that the GA-BP network achieves an average relative error of 0.94772%, which is superior to the 1.5988% of the traditional BP network. Moreover, it boasts a prediction accuracy of 90% for the comprehensive value of landscape quality from 2015 to 2022, significantly outperforming the BP network's approximate 70% accuracy. This method enhances the accuracy of landscape quality assessment but also aids in identifying crucial factors influencing quality. It provides scientific and objective guidance for future urban landscape structure and layout, contributing to high-quality urban development and the creation of exemplary living areas.

A new approach to the identification of Landscape Quality Objectives (LQOs) as a set of indicators.

The objective of the paper is threefold: (1) to introduce Landscape Quality Objectives (LQOs) as a set of indicators; (2) to present a method of linking social and expert opinion in the process of the formulation of landscape indicators; and (3) to present a methodological framework for the identification of LQOs. The implementation of these goals adopted a six-stage procedure based on the use of landscape units: (1) GIS analysis; (2) classification; (3) social survey; (4) expert value judgement; (5) quality assessment; and (6) guidelines formulation. The essence of the research was the presentation of features that determine landscape quality according to public opinion as a set of indicators. The results showed that 80 such indicators were identified, of both a qualitative (49) and a quantitative character (31). Among the analysed units, 60% (18 objects) featured socially expected (and confirmed by experts) levels of landscape quality, and 20% (6 objects) required overall quality improvement in terms of both public and expert opinion. The adopted procedure provides a new tool for integrating social responsibility into environmental management. The advantage of the presented method is the possibility of its application in the territories of various European countries. It is flexible enough to be based on cartographic studies, landscape research methods, and environmental quality standards existing in a given country.

Linkages between the concept of nature-based solutions and the notion of landscape.

As the effects of Nature-based solutions (NBS) application are usually much broader than only the area under the project implementation, it is necessary to capture the impact on these actions of landscape as well as the influence of landscape type on the NBS effectiveness. The main aim of this study was to detect linkages between the operational of NBS and the landscape dimention, based on a systematic literature review. The results showed the existence of seven linkages: (1, 2) 'input' and 'output' resulting from the consideration of landscape as a scale of NBS implementation; (3, 4) 'stimulator' and 'inspiration' based on the contribution of landscape-based management to the implementation of NBS; (5) 'co-beneficiary' since the implementation of NBS affects aesthetic dimensions of landscape; (6) 'tool' as landscape-based indicators are used to assess the impacts of NBS; and (7) 'foundation' as health-supporting landscapes may be considered as a type of NBS action.

How Thermal Perceptual Schema Mediates Landscape Quality Evaluation and Activity Willingness.

The use of outdoor space is closely related to local microclimate conditions. Some studies have shown that people form perceptual schemata based on their perceptual experience of microclimate conditions, which leads to perceptual bias, so it is necessary to further investigate how the thermal schemata formed by the accumulation of thermal experience affect the willingness to engage in activities, which will be beneficial to improve the use of urban space. Studies have not explored the relationship between the thermal perceptual schema (TPS), landscape quality evaluation (LQE), and activity willingness. Therefore, it is necessary to further investigate how thermal schemas formed by the accumulation of thermal experience affect activity willingness. A total of 3435 volunteers were surveyed online and divided into two groups, the first group for comfortable weather (N = 1773) and the second group for hot weather (N = 1662), and voted for each of the four dimensions of the five scenarios according to the TPS. This study found that socioeconomic status (SES) and age were the main factors contributing to TPS bias when perceiving the same destination according to TPS, and this difference was consistent in both groups, which affects the willingness to be active at the destination. The study also found that LQE may be a major factor in residents' willingness to be active in more pleasant weather, while TPS plays a more important role in hot weather conditions. In addition, we investigated the relationship between TPS and residents' activity willingness mediated by different landscape features and parameter configurations. These results indicate that the TPS formed by thermal experience accumulation affects people's LQE and activity willingness, and that landscape configuration parameters play an important role.

Assessing experienced tranquillity through natural language processing and landscape ecology measures.

CONTEXT: Identifying tranquil areas is important for landscape planning and policy-making. Research demonstrated discrepancies between modelled potential tranquil areas and where people experience tranquillity based on field surveys. Because surveys are resource-intensive, user-generated text data offers potential for extracting where people experience tranquillity. OBJECTIVES: We explore and model the relationship between landscape ecological measures and experienced tranquillity extracted from user-generated text descriptions. METHODS: Georeferenced, user-generated landscape descriptions from Geograph.UK were filtered using keywords related to tranquillity. We stratify resulting tranquil locations according to dominant land cover and quantify the influence of landscape characteristics including diversity and naturalness on explaining the presence of tranquillity. Finally, we apply natural language processing to identify terms linked to tranquillity keywords and compare the similarity of these terms across land cover classes. RESULTS: Evaluation of potential keywords yielded six keywords associated with experienced tranquillity, resulting in 15,350 extracted tranquillity descriptions. The two most common land cover classes associated with tranquillity were arable and horticulture, and improved grassland, followed by urban and suburban. In the logistic regression model across all land cover classes, freshwater, elevation and naturalness were positive predictors of tranquillity. Built-up area was a negative predictor. Descriptions of tranquillity were most similar between improved grassland and arable and horticulture, and most dissimilar between arable and horticulture and urban. CONCLUSIONS: This study highlights the potential of applying natural language processing to extract experienced tranquillity from text, and demonstrates links between landscape ecological measures and tranquillity as a perceived landscape quality. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s10980-020-01181-8) contains supplementary material, which is available to authorized users.

Hybrid choice model dataset of a representative Swiss online panel survey on peoples' preferences related to mixed renewable energy scenarios in landscapes and the effect of landscape-technology fit.

We present stated preference data based on a national representative Swiss online panel survey related to preference of mixed renewable energy infrastructure in landscapes. Data were collected between November 2018 and March 2019 via an online questionnaire and yielded 1026 responses. The online questionnaire consisted of two main parts - (1) questions covering meanings related to landscapes, nature and renewable energy infrastructure and questions regarding the "fit" of landscape/renewable energy infrastructure (REI) combinations and (2) a stated choice experiment. While in the first part of the questionnaire we asked respondents about their personal connection to certain landscapes, to nature and to specific REI, we also asked them to evaluate the fitting of seven different Swiss landscapes (near natural alpine areas, northern alps, touristic alpine areas, agricultural plateau, urban plateau, Jura ridges, urban alpine valley) with five different REI (wind, PV ground/agricultural, PV ground/other, PV roof, power lines) combinations. In the second part of the questionnaire, the stated choice experiment confronted respondents with 15 consecutive choice tasks, with each task involving a choice between two "energy system transformation" options and an opt-out option (none). Each choice option (beside the opt-out option) included four unlabeled attributes (landscape, wind energy infrastructure, photovoltaic energy infrastructure, high voltage overhead power line infrastructure) with varying levels. Due to data cleaning procedures (item nonresponse) the number of responses used within hybrid choice modeling and analysis was n = 844 (12,660 choice observations). An analysis of the hybrid choice model and further insights are presented in the article "How landscape-technology fit affects public evaluations of renewable energy infrastructure scenarios. A hybrid choice model."

Geomorphology applied to landscape analysis for planning and management of natural spaces. Case study: Las Batuecas-S. de Francia and Quilamas natural parks, (Salamanca, Spain).

Geomorphology is fundamental to landscape analysis, as it represents the main parameter that determines the land spatial configuration and facilitates reliefs classification. The goal of this article is the elaboration of thematic maps that enable the determination of different landscape units and elaboration of quality and vulnerability synthetic maps for landscape fragility assessment prior to planning human activities. For two natural spaces, the final synthetic maps were created with direct (visual-perceptual features) and indirect (cartographic models and 3D simulations) methods from thematic maps with GIS technique. This enabled the creation of intrinsic and extrinsic landscape quality maps showing sectors needing most preservation, as well as intrinsic and extrinsic landscape fragility maps (environment response capacity or vulnerability towards human actions). The resulting map shows absorption capacity for areas of maximum and/or minimum human intervention. Sectors of high absorption capacity (minimum need for preservation) are found where the incidence of human intervention is minimum: escarpment bottoms, fitted rivers, sinuous high lands with thick vegetation coverage and valley interiors, or those areas with high landscape quality, low fragility and high absorption capacity, whose average values are found across lower hillsides of some valleys, and sectors with low absorption capacity (areas needing most preservation) found mainly in the inner parts of natural spaces: peaks and upper hillsides, synclines flanks and scattered areas. For the integral analysis of landscape, a mapping methodology has been set. It comprises a valid criterion for rational and sustainable planning, management and protection of natural spaces.