Land | Special Issue : Advances in Landscape Perception Based on New Approaches & Technologies

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22 pages, 5360 KiB

Open AccessArticle

A Comparison of the Efficacy of Fuzzy Overlay and Random Forest Classification for Mapping and Shaping Perceptions of the Post-Mining Landscape of Gauteng, South Africa

by Samkelisiwe Khanyile

Land 2024, 13(11), 1761; https://doi.org/10.3390/land13111761 - 26 Oct 2024

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Abstract

Post-mining landscapes are multifaceted, comprising multiple characteristics, more so in big metropolitan regions such as Gauteng, South Africa. This paper evaluates the efficacy of Fuzzy overlay and Random Forest classification for integrating and representing post-mining landscapes and how this influences the perception of [...] Read more.

Post-mining landscapes are multifaceted, comprising multiple characteristics, more so in big metropolitan regions such as Gauteng, South Africa. This paper evaluates the efficacy of Fuzzy overlay and Random Forest classification for integrating and representing post-mining landscapes and how this influences the perception of these landscapes. To this end, this paper uses GISs, MCDA, Fuzzy overlay, and Random Forest classification models to integrate post-mining landscape characteristics derived from the literature. It assesses the results using an accuracy assessment, area statistics, and correlation analysis. The findings from this study indicate that both Fuzzy overlay and Random Forest classification are applicable for integrating multiple landscape characteristics at varying degrees. The resultant maps show some similarity in highlighting mine waste cutting across the province. However, the Fuzzy overlay map has higher accuracy and extends over a larger footprint owing to the model’s use of a range of 0 to 1. This shows both areas of low and high memberships, as well as partial membership as intermediate values. This model also demonstrates strong relationships with regions characterised by landscape transformation and waste and weak relationships with areas of economic decline and inaccessibility. In contrast, the Random Forrest classification model, though also useful for classification purposes, presents a lower accuracy score and smaller footprint. Moreover, it uses discrete values and does not highlight some areas of interaction between landscape characteristics. The Fuzzy overlay model was found to be more favourable for integrating post-mining landscape characteristics in this study as it captures the nuances in the composition of this landscape. These findings highlight the importance of mapping methods such as Fuzzy overlay for an integrated representation and shaping the perception and understanding of the locality and extent of complex landscapes such as post-mining landscapes. Methods such as Fuzzy overlay can support research, planning, and decision-making by providing a nuanced representation of how multiple landscape characteristics are integrated and interact in space and how this influences public perception and policy outcomes. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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20 pages, 24028 KiB

Open AccessArticle

An Assessment of Landscape Perception Using a Normalised Naturalness Index in the Greater Seoul Area

by Doeun Kim and Yonghoon Son

Land 2024, 13(6), 750; https://doi.org/10.3390/land13060750 - 28 May 2024

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Abstract

This study analysed the greater Seoul area (GSA) in terms of naturalness, a representative indicator of natural scenic beauty, and created an assessment map, shifting from a traditional urban development perspective to a landscape perspective. It also developed a “normalised naturalness index” by [...] Read more.

This study analysed the greater Seoul area (GSA) in terms of naturalness, a representative indicator of natural scenic beauty, and created an assessment map, shifting from a traditional urban development perspective to a landscape perspective. It also developed a “normalised naturalness index” by combining the results of the expert metric score with the Hemeroby index, which was used as a naturalness assessment representative item. Then, it interpreted the naturalness status of the GSA landscape characteristics. As a result, the landscape of the GSA demonstrates the following five characteristics: First, the central business districts in the capital city of Seoul are densely developed areas with a very high degree of human intervention. Second, the satellite cities built to solve Seoul’s housing and logistics problems are rated as “a little less, but still heavily humanised” as a landscape characteristic. These areas are becoming increasingly humanised. Also, it is worth noting that the third characteristic, regarding moderate landscape areas, has a distinctly different meaning for areas outside of the city boundary, as well as those within the city boundary. Although these areas are in the same statistical category, they have two different meanings: one is the area where the average values converged on “moderate” by virtue of urban forests near the city centre, and the other is the area outside of Seoul that has a Hemeroby value of 0.5–0.6, which refers to open spaces such as agricultural lands, wetlands, or coastal areas. Fourth, suburban forests are reserved with legal restrictions to curb excessive urban sprawl, as well as parts of the demilitarised zone along the border areas of North and South Koreas. The last landscape characteristic is illustrated in the scenic area of the eastern woodlands. The normalised landscape naturalness index developed through this study provides an overall understanding of the environmental state of the GSA. Future research may build on the results of this study to refine methods for assessing public perceptions of naturalness. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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22 pages, 10829 KiB

Open AccessArticle

Differences in Emotional Preferences toward Urban Green Spaces among Various Cultural Groups in Macau and Their Influencing Factors

by Mengyao Wang, Yu Yan, Mingxuan Li and Long Zhou

Land 2024, 13(4), 414; https://doi.org/10.3390/land13040414 - 24 Mar 2024

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Abstract

This study explores the diversity in emotional tendencies and needs toward urban green spaces (UGSs) among people from different cultural backgrounds in the wave of cultural integration. We utilized social media data as research tools, gathering a wide range of perspectives and voices. [...] Read more.

This study explores the diversity in emotional tendencies and needs toward urban green spaces (UGSs) among people from different cultural backgrounds in the wave of cultural integration. We utilized social media data as research tools, gathering a wide range of perspectives and voices. Utilizing geolocation data from 176 UGSs in Macau, we collected 139,162 social media comments to analyze the emotional perceptions of different cultural groups. Furthermore, we conducted regression analysis on the number of posts and emotional intensity values from four linguistic groups—Chinese, English, Southeast Asian languages, and Portuguese—in UGSs, correlating them with ten locally relevant landscape features. Our findings reveal diverse attitudes, emotional inclinations, and functional and design needs of different linguistic groups toward UGSs, as follows: (1) there were significant differences in emotional intensity and tweet counts across 176 UGSs; (2) Chinese and Portuguese speakers showed a more positive attitude toward plazas and natural ecological areas, whereas English- and Southeast-Asian-language speakers tended to favor recreational areas and suburban parks; (3) Chinese speakers exhibited a more positive emotional intensity toward sports facilities, while English speakers placed more emphasis on green space areas, architecture, sports infrastructure, and plant landscapes; (4) there was no specific landscape feature preference for Portuguese- and Southeast-Asian-language speakers. This research not only deepens our understanding of the emotional perceptions and preferences of UGSs among different cultural groups but also explores the association between these groups and various urban landscape features. This provides important theoretical and practical insights for future UGS planning, construction, and promoting multicultural coexistence for sustainable urban development. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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20 pages, 12834 KiB

Open AccessArticle

Research on Adaptive Reuse Strategy of Industrial Heritage Based on the Method of Social Network

by Jinghua Song, Junyang Chen, Xiu Yang and Yuyi Zhu

Land 2024, 13(3), 383; https://doi.org/10.3390/land13030383 - 18 Mar 2024

Cited by 2 | Viewed by 2808

Abstract

With the deceleration of urban expansion, the adaptive reuse of industrial heritage buildings has emerged as a novel area of research. In previous times, the majority of approaches to adapting industrial heritage buildings relied on experiential knowledge, which lacked the ability to objectively [...] Read more.

With the deceleration of urban expansion, the adaptive reuse of industrial heritage buildings has emerged as a novel area of research. In previous times, the majority of approaches to adapting industrial heritage buildings relied on experiential knowledge, which lacked the ability to objectively assess the relationship between spaces and engage in rational planning. However, the social network analysis method offers an objective and comprehensive means of perceiving the spatial structure and analyzing its issues from a detached perspective. This study presents a proposal for addressing three spatial challenges encountered during the conversion of industrial heritage buildings into public buildings. It also suggests spatial optimization strategies to overcome these challenges. The Sanlinqiao Thermal Bottle Factory is selected as the research subject, and a spatial network structure model is constructed to analyze the existing issues using the social network analysis method. The proposed spatial optimization strategies are then applied, and the optimized space is evaluated through a re-analysis of the spatial layout. The spatial utilization rate has been significantly improved, leading to an effective enhancement of the spatial vitality of the site. This study presents a spatial strategy aimed at converting industrial heritage buildings into public buildings, thereby offering valuable insights for similar projects involving the transformation of industrial heritage sites. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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16 pages, 5668 KiB

Open AccessArticle

Research on the Vitality of Public Spaces in Tourist Villages through Social Network Analysis: A Case Study of Mochou Village in Hubei, China

by Jinghua Song, Yuyi Zhu, Xiangzhai Chu and Xiu Yang

Land 2024, 13(3), 359; https://doi.org/10.3390/land13030359 - 12 Mar 2024

Cited by 3 | Viewed by 1592

Abstract

The construction of tourist villages is an important implementation path for promoting the new urbanization strategy in China. The optimization of their spatial pattern and functional adjustment is a key way to achieve high-quality urban development. The purpose of this study is to [...] Read more.

The construction of tourist villages is an important implementation path for promoting the new urbanization strategy in China. The optimization of their spatial pattern and functional adjustment is a key way to achieve high-quality urban development. The purpose of this study is to determine the influencing factors of public space vitality in tourist villages from the perspective of human behavior activities and to provide design support strategies for enhancing the vitality of public spaces in tourist villages. Using Mochou Village as an example, physical and behavioral network models were used to conduct a quantitative study of the vitality characteristics, and Quantitative Analysis of Precedence (QAP) regression was used to investigate the influence factors. The results demonstrate that spatial characteristics, such as “small block size, high street density”, and grid-like street structure and squares, as well as factors such as store concentration, sight lines, street length, spatial openness, and street width, significantly impact the vitality of public spaces in tourist villages. The analysis of the characteristics of the vitality of public space networks in tourist villages and the discussion of the influencing factors of public space vitality in this study can provide guidance for evaluating the vitality of public spaces and designing public spaces with high vitality in tourist villages. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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29 pages, 35985 KiB

Open AccessArticle

Measuring the Convergence and Divergence in Urban Street Perception among Residents and Tourists through Deep Learning: A Case Study of Macau

by Jiacheng Shi, Yu Yan, Mingxuan Li and Long Zhou

Land 2024, 13(3), 345; https://doi.org/10.3390/land13030345 - 8 Mar 2024

Viewed by 1654

Abstract

In today’s context of flourishing tourism, the development of urban tourism leads to a continuous influx of population. Existing empirical evidence highlights the interaction between tourists’ and residents’ perception of urban spaces and the local society and living spaces. This study, focusing on [...] Read more.

In today’s context of flourishing tourism, the development of urban tourism leads to a continuous influx of population. Existing empirical evidence highlights the interaction between tourists’ and residents’ perception of urban spaces and the local society and living spaces. This study, focusing on Macau, utilizes the region’s streetscape images to construct a deep learning-based model for quantifying the urban street perception of tourists and local residents. To obtain more refined perceptual evaluation data results, during the training phase of the model, we intentionally categorized tourist activities into natural landscape tours, historical sightseeing, and entertainment area visits, based on the characteristics of the study area. This approach aimed to develop a more refined perception evaluation method based on the classification of urban functional areas and the types of urban users. Further, to improve the streetscape environment and reduce visitor and resident dissatisfaction, we delved into the differences in perception between tourists and residents in various functional urban areas and their relationships with different streetscape elements. This study provides a foundational research framework for a comprehensive understanding of residents’ and tourists’ perceptions of diverse urban street spaces, emphasizing the importance of exploring the differentiated perceptions of streetscapes held by tourists and residents in guiding scientific urban tourism development policies and promoting social sustainability in cities, particularly those where tourism plays a significant role. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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24 pages, 19767 KiB

Open AccessArticle

The Relationship between Emotional Perception and High-Density Built Environment Based on Social Media Data: Evidence from Spatial Analyses in Wuhan

by Wei Liu, Dong Li, Yuan Meng and Chuanmin Guo

Land 2024, 13(3), 294; https://doi.org/10.3390/land13030294 - 26 Feb 2024

Cited by 2 | Viewed by 1911

Abstract

The utilization of Social Media Data (SMD) from location-based services offers a wealth of information to analyze changes in human emotional perception influenced by high-density built environments. This study aimed to examine the impact of high-density built environment factors on human emotion perception. [...] Read more.

The utilization of Social Media Data (SMD) from location-based services offers a wealth of information to analyze changes in human emotional perception influenced by high-density built environments. This study aimed to examine the impact of high-density built environment factors on human emotion perception. First, a set of indicators for high-density built environments was established. Subsequently, Natural Language Processing (NLP) was employed to analyze SMD for sentiment identification and classification. Finally, the Multi-scale Geographically Weighted Regression (MGWR) model was utilized to investigate the spatial differentiation of human emotional perception in high-density built environments. The findings revealed that positive emotions display spatial variations in high-density built environments. Additionally, positive emotions were found to be influenced by multiple variables, with different variables simultaneously affecting individuals’ positive emotions. Specific built environment indicators showed positive correlations with Open Space Ratio (OSR), Green Space Ratio (GSR), POI Functional Density (PFD), and Road Network Density (RND), while negative correlations with Floor Space Index (FSI), Ground Space Index (GSI), Building Average Layer (BAL), Water Index (WI), and Space Syntax Integration (SSI) were observed. Normalized Difference Vegetation Index (NDVI), POI Functional Mixture (PFM), Space Syntax Choice (SSC), and Population Density (PD) exhibited mixed results in different spatial contexts. This research on human perception provides insights for refined urban design and governance, addressing the limitations of top-down approaches in dense urban renewal. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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18 pages, 63849 KiB

Open AccessArticle

A Digital Survey Approach for Large-Scale Landscape Heritage Resource Exploration: Auxiliary Beacons, the Uncharted Signal Structure of the Great Wall in China

by Zhe Li, Mingshuai Li and Yan Li

Land 2024, 13(2), 192; https://doi.org/10.3390/land13020192 - 5 Feb 2024

Cited by 2 | Viewed by 1216

Abstract

Following the completion of the Great Wall Resource Survey in 2012, numerous landscape heritage resources along the Great Wall remained undiscovered, highlighting the limitations of conventional survey methods. This study aimed to conduct in-depth investigations of Great Wall signal sites through digital fieldwork [...] Read more.

Following the completion of the Great Wall Resource Survey in 2012, numerous landscape heritage resources along the Great Wall remained undiscovered, highlighting the limitations of conventional survey methods. This study aimed to conduct in-depth investigations of Great Wall signal sites through digital fieldwork methods, unveiling a crucial signaling structure—the auxiliary beacon—and presenting genuine historical scenes of the Great Wall signal network. Through the retrieval of the image database of the entire Great Wall and the utilization of UAVs (drones) for low-altitude remote sensing surveys, 252 auxiliary beacon sites were identified in diverse environments (e.g., deserts, mountains, plains) in Xinjiang, Gansu, Inner Mongolia, Qinghai, Ningxia, and other 10 regions. These case studies enable the categorization of layout types and the proposal of reconstruction hypotheses for the signal network of the Great Wall of China. The findings demonstrate that the beacon fire signals are not lit on the beacon tower tops, but through the ignition of various signals by auxiliary beacons, expressing pre-arranged information. Beacon towers and auxiliary beacons together form an efficient signal network along the Great Wall. This study explores how to use digital survey methods to unearth unknown landscape heritage resources of the Great Wall, enhancing the accuracy of observation for cross-regional and large-scale cultural heritage. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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16 pages, 1907 KiB

Open AccessArticle

Intentional Characteristics and Public Perceived Preferences of Lake Parks Based on Machine Learning Models

by Dandan Wang, Hyun Min and Donggen Rui

Land 2024, 13(1), 57; https://doi.org/10.3390/land13010057 - 3 Jan 2024

Viewed by 1227

Abstract

This research aimed to analyze and understand the perceived landscape preferences of lake parks (LPs) and how the public perceives and prefers these elements within the context of lake parks. The objective was to provide insights beneficial for landscape design, urban planning, and [...] Read more.

This research aimed to analyze and understand the perceived landscape preferences of lake parks (LPs) and how the public perceives and prefers these elements within the context of lake parks. The objective was to provide insights beneficial for landscape design, urban planning, and the creation of more appealing and sustainable lake parks. To achieve this, two primary methods were employed in this study: the Automated Machine Learning (Auto ML) model and the DeepLab v3+ model. To gather data for the research, 46,444 images were collected from 20 different lake parks from 2019 to 2022. Social media platforms such as Instagram, Flickr, and specific lake park community groups were tapped to source photographs from both professional photographers and the general public. According to the experimental findings, the perceived frequency of natural landscapes was 69.27%, which was higher than that of humanistic landscapes by 30.73%. The perceived intensity was also maintained between 0.09 and 0.25. The perceived frequency of water body landscapes was much greater on a macro-scale, at 73.02%, and the public had various plant preferences throughout the year. Aquatic plant landscapes with low-to-medium green visibility were preferred by the public, according to the landscape share characterization, while amusement rides with medium-to-high openness were preferred. The sky visibility of amusement rides was between 0 and 0.1 and between 0.3 and 0.5, indicating that the public preferred amusement rides with medium-to-high openness. In lake parks, the populace chose settings with less obvious architectural features. When combined, the two models used in this study are useful for identifying and analyzing the intended traits and preferences of lake parks among the general public. They also have theoretical and practical application value for directing the development of lake parks and urban landscapes. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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19 pages, 1378 KiB

Open AccessArticle

Accepting Solar Photovoltaic Panels in Rural Landscapes: The Tangle among Nostalgia, Morality, and Economic Stakes

by Shengyuan Li and Zhonghua Gou

Land 2023, 12(10), 1956; https://doi.org/10.3390/land12101956 - 23 Oct 2023

Cited by 2 | Viewed by 1857

Abstract

In the context of climate change and rural revitalization, numerous solar photovoltaic (PV) panels are being installed on village roofs and lands, impacting the enjoyment of the new rural landscape characterized by PV panels. However, the visual acceptance of PV panels in rural [...] Read more.

In the context of climate change and rural revitalization, numerous solar photovoltaic (PV) panels are being installed on village roofs and lands, impacting the enjoyment of the new rural landscape characterized by PV panels. However, the visual acceptance of PV panels in rural areas of China is not yet fully understood. This study aims to identify and correlate three key influential factors that contribute to the acceptance and appreciation of PV panels in China’s rural settings. A quasi-experiment was conducted, incorporating diverse landscapes into six rural settings, each containing both the original landscape and PV panels. The findings demonstrated that the original rural landscape was significantly more scenic than PV panels, and factors contributing to the appreciation of traditional landscapes, such as nostalgia, played a vital role in rejecting PV panels. Conversely, renewable energy-related factors, such as economic stakes and moral desirability, were found to contribute to the acceptance of PV panels. This study contributes to the strategic planning and design of solar PV panels in rural landscapes, taking into consideration social acceptance and local contexts. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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Review

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22 pages, 3550 KiB

Open AccessReview

Social Media Image and Computer Vision Method Application in Landscape Studies: A Systematic Literature Review

by Ruochen Ma and Katsunori Furuya

Land 2024, 13(2), 181; https://doi.org/10.3390/land13020181 - 3 Feb 2024

Viewed by 1793

Abstract

This study systematically reviews 55 landscape studies that use computer vision methods to interpret social media images and summarizes their spatiotemporal distribution, research themes, method trends, platform and data selection, and limitations. The results reveal that in the past six years, social media–based [...] Read more.

This study systematically reviews 55 landscape studies that use computer vision methods to interpret social media images and summarizes their spatiotemporal distribution, research themes, method trends, platform and data selection, and limitations. The results reveal that in the past six years, social media–based landscape studies, which were in an exploratory period, entered a refined and diversified phase of automatic visual analysis of images due to the rapid development of machine learning. The efficient processing of large samples of crowdsourced images while accurately interpreting image content with the help of text content and metadata will be the main topic in the next stage of research. Finally, this study proposes a development framework based on existing gaps in four aspects, namely image data, social media platforms, computer vision methods, and ethics, to provide a reference for future research. Full article

(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)

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