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Article

Establishing Landscape Networks Based on Visual Quality and Ecological Resistance: A Case Study in Tianmeng Scenic Spot, China

by
Menglin Xu
1 and
Hajime Matsushima
2,*
1
Graduate School of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita Ward, Sapporo 060-8589, Hokkaido, Japan
2
Research Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita Ward, Sapporo 060-8589, Hokkaido, Japan
*
Author to whom correspondence should be addressed.
Forests 2023, 14(3), 516; https://doi.org/10.3390/f14030516
Submission received: 26 December 2022 / Revised: 6 February 2023 / Accepted: 2 March 2023 / Published: 6 March 2023
(This article belongs to the Section Forest Ecology and Management)
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Abstract

:
Forest-based scenic spots have received widespread attention for their landscape aesthetics and ecological value, but the rapid growth of tourism and landscape exploitation make it challenging to balance human recreational needs, landscape quality, and ecological stability. This study aimed to evaluate, quantify, and grade landscape quality from the point of view of subjective human aesthetic needs as well as objective landscape visual sensitivity. After the selection of high-quality landscape viewpoints as sources, the minimum cumulative resistance (MCR) model was used to screen the optimal paths for connectivity among viewpoints with consideration of ecological resistance. High-quality landscape viewpoints, optimal paths, and ecological-resistance surfaces constructed the landscape network for sustainable development. The results showed that the landscape quality of viewpoints in Tianmeng Scenic Spot was not good; only 32.4% of these viewpoints had good performance of both landscape aesthetics and landscape visual sensitivity. In the analysis of ecological-resistance surfaces, the proportion of very-high resistance areas and high resistance areas was 32.9%, and these were mostly distributed in the main tourist roads and their buffer areas around the northwest of Tianmeng Mountain Scenic Spot. Eleven landscape core viewpoints and six secondary viewpoints, all with high landscape aesthetics, were selected as high-quality visual landscapes, and then based on the ecological-resistance surfaces, 11 core landscape-dissemination paths and 6 secondary landscape-dissemination paths were identified, respectively, using the MCR model. This method could provide scientific decision support to enhance the effectiveness of viewpoints as well as sustainable landscape planning for development.

1. Introduction

Scenic-spot landscape is a type of structural landscape unit that combines natural resource endowment and human resource characteristics [1,2,3]. Typical forest-based scenic spots are highly favored by humans for their large-scale forest vegetation cover, good air conditions, and beautiful scenery [4]. In recent years, with the proliferation of tourism activities, the function of forests has evolved from a single one of production to a multifunctional collection of leisure and tourism as well as ecological and economic functions. [5]. Therefore, the development and management of forest-based scenic areas requires an intelligent approach to balance the relationship between diverse functions. More specifically, how to scientifically evaluate landscape quality and establish a sustainable landscape network based on ecological status is something that needs careful consideration.
The economic benefits driven by the tourism business have also helped the development of scenic spots [6,7], and with people’s aesthetic appreciation increasing, the landscape quality of scenic spots is drawing considerable attention. Accordingly, a balance between the development and construction of viewpoints and landscape quality is an urgent issue. Concurrently, nature-based tourism has become an important and growing aspect of the tourism industry [8,9], but the surge in tourism demand has resulted in areas facing natural resource destruction and over-exploitation. There are three types of relationships between nature conservation and tourism: coexistence, conflict, and symbiosis [10,11]. While increasing human activity is bound to promote construction ventures, the coexistence of the ecological environment and tourism development has triggered conflict. Therefore, the effective use of existing tourism resources and improving the efficiency and quality of tourism development in scenic spots, while maintaining the stability of the ecosystem, has become the main focus of the academic community.
Visual perception is an important aspect of the sightseeing experience [12], and humans perceive the landscape and resources of a particular area mainly through the visual landscape [5]. A reasonable and comprehensive visual evaluation of landscape can effectively assess the visual situation of viewpoints, identify the quality of scenic spots, and make the enhancement, development, and construction of tourism viewpoints efficacious [13]. Research on visual landscape has been evolving in Western developed countries since the 1960s [14]. In the early stages of landscape visual assessment research, mostly based on environmental protection proposals in Western countries following the environmental crisis, the systematization and quantification of landscape visual assessment was promoted. Until the 1990s, there was no major breakthrough in the methodology of landscape visual assessment, which mainly focused on aspects such as visual assessment classification. In recent years, two models of visual assessment with high public acceptance have existed: assessment based on objective or physical aspect (expert assessment) [15] and assessment based on the subjective or psychological aspect (public perception) [12]. At this stage, a combination of expert-based assessment and public perception has emerged [16,17]. Meanwhile, comprehensive landscape assessment approaches based on information technology and geographic information systems have been developed using visual sensitivity based on the physical characteristics of the landscape as a starting point, and exploring the relationship and regularity between visual sensitivity and landscape features, ecology, culture, and society, in a closely-related manner [18,19,20,21,22,23]. The main evaluation methods include a comprehensive analysis of landscape characteristics with visual sensitivity evaluation [20] or landscape ecological status [5] and landscape cultural status [21] combined with visual sensitivity evaluation; or subjective visual perception as one of the basic elements combined with other objective landscape physiological characteristics [18]. Efforts to assess landscape quality from both subjective and objective aspects have already been incorporated in many countries in environmental-impact assessments as landscape quality assessment and landscape impact assessment [24,25,26,27] and are practiced in tourism development sites [28,29,30] and in the installation of renewable energy facilities such as wind turbines [31,32,33]. However, few studies have established sustainable landscape models based on a combination of the above two aspects of integrated visual assessment and ecological context, and these are still under research.
Tianmeng Mountain Scenic Spot is located on the northwest side of Linyi city and its ecosystem serves important ecological protection and provides critical support for ecological stability. In recent years, the rapid growth in tourism activities have brought great opportunities for landscape development and economic benefits to the Tianmeng Mountain Scenic Spot, but at the same time, it faces great challenges, such as over-exploitation and environmental pollution. How to fulfil the needs of tourism while fulfilling the role of ecological protection is an urgent issue to be solved. Therefore, strategies to enhance landscape effectiveness and establish reasonable landscape networks are important factors to be considered.
The purpose of this research was to integrate (after comprehensive visual evaluation) the landscape network in Tianmeng Mountain Scenic Spot, which links the scattered high-quality landscape viewpoints, in an efficient manner. Our aims were as follows: (1) Comprehensive evaluation of landscape vision: to evaluate the landscape quality of viewpoints in both visual characteristics (objective) and human aesthetic preferences (subjective). (2) Grading of landscape quality: to grade and summarize the combined performance of viewpoints that integrate the above two aspects, so as to propose specific measures for the improvement of landscape quality. (3) Establishment of landscape network: to establish a landscape network with high-quality landscape viewpoints, landscape-dissemination paths, and landscape core areas using the minimum cumulative resistance (MCR) method, and subsequently to provide suggestions for planning and management of the landscape and ecosystem of Tianmeng Mountain Scenic Spot. The MCR model is one of the least costly models and can predict the most efficient and shortest connection routes among sites under the influence of ecological resistance.

2. Materials and Methods

2.1. Study Area

Tianmeng Mountain Scenic Spot is located in the northwest of Linyi City, Shandong Province (Figure 1a), in the eastern part of the Yimeng Mountain Range, with the geographical coordinates ranging between 35°42′–35°48′ N and 118°03′–118°09′ E. It has a typical continental climate of the temperate monsoon zone, with an altitude of 1001.2 m, and is typically characterized by its rich forest, mountain, and waterfalls. The major viewpoints are concentrated on the main tourist road (Figure 1c, red line), which is located on the ridge line running through the east–west and north–south mountains, with the major landscape viewpoints such as Wanghai Tower, the world’s first glass bridge, Yuhuang Temple, and the Birthplace of Yimeng Mountain Minor. The land cover of Tianmeng Mountain Scenic Spot is mainly forest and also contains construction land such as viewpoints, tourist roads, and villages. (Figure 1b).

2.2. Data Descriptions and Pre-Processing

In this study, the following data sources were used: digital elevation information, Sentinel 2 remote sensing images, landscape-viewpoint distribution map, CAD file on the current state of the landscape, information on plant species, and other related documents; more details are showed in the Table 1. In addition, among the 34 major viewpoints in Tianmeng Mountain Scenic Spot, some viewpoints do not have a clear range. Therefore, based on the actual situation of field research, the unified standard area of such viewpoints was determined. Specifically, the center of the viewpoint was regarded as the center of the circle, with 5 m as the diameter, and the areas covered were considered the ranges of the viewpoints. The above data should be estimated as a uniform projection mode with a uniform resolution of 30 m × 30 m.

2.3. Integration of Landscape Visual Assessment

In this study, landscape visual assessment was based on both landscape visual sensitivity (LVS) from the objective aspect and landscape aesthetic evaluation (LAE) from the subjective aspect (Figure 2).

2.3.1. Landscape Visual Sensitivity (LVS)

LVS is highly significant in the visual landscape, which is a comprehensive reflection of landscape visibility [34,35]. Slope, distance from roads, visual probability, and remarkableness degree were selected as the four indicators based on the characteristics of Tianmeng Mountain Scenic Spot and previous studies [20]. The weights were assigned based on the AHP method [36]; more details were shown in Table 2.
(1) Slope: Tianmeng Mountain Scenic Spot is a typical mountainous scenic spot, and slope is an important indicator influencing sightseeing and touring. The higher slope increases the likelihood that the landscape will be noticed, which in turn enhances visual sensitivity. According to the situation of Tianmeng Mountain Scenic Spot and relevant classification criteria, relative slope (α) was categorized into four grades: 0 ≤ α ≤ 15, 15 < α ≤ 30, 30 < α ≤ 45, and 45 < α [37], which represented very low, low, medium, and high, and were assigned values 1, 3, 5, and 7, respectively.
(2) Distance from roads: In general, the closer the landscape is to the viewer, the higher the visibility and clarity of the landscape, and the greater the sensitivity of the landscape. According to the actual situation of Tianmeng Mountain Scenic Spot, and considering the roads as the baseline to create buffer zones of different distances in ArcGIS10.7., if 0 ≤ a ≤ 100 m, the structural features of the landscape can be distinguished clearly; if 100 m < a ≤ 200 m, landscape elements can be clearly seen, but certain details cannot be observed; if 200 m < a ≤ 400 m, only the overall outline of the landscape can be seen; and if 400 m < a, it is basically difficult to see the landscape. The above four categories correspond to the ecological visual sensitivity of high, medium, low, and very low, with values 7, 5, 3, and 1, respectively.
(3) Visual probability: The visual probability of landscape is determined primarily by the topography, the landscape elements on the surface that interfere with sightlines, and the number of landscape viewpoints [34]. The greater the visibility of the landscape seen by the viewer within the field of view, the greater the landscape visual sensitivity.
To identity landscape visibility, the main tourist roads were divided evenly in 359 points at 100 m intervals (Supplementary Figure S1). Subsequently, the visible/invisible area of each point was analyzed based on DEM data and the location of itself through ArcGIS10.7; a total of 359 analyses were performed. Visual probability was then obtained by overlaying the above 359 landscape-visibility analysis results. The natural break-point method was applied to classify the combined visual visibility results into four levels: very low, low, medium, and high, with values of 1, 3, 5, and 7, respectively.
(4) Remarkableness degree: Landscape remarkableness is an important indicator to determine visual sensitivity, and it mainly depends on the contrast between the landscape and environment [38]. The stronger the contrast between the external expression of the landscape (color, texture, shape, etc.) and surrounding environment, the higher the visual sensitivity. The Visual Resources Management system developed by the Bureau of Land Management is mostly used to evaluate the landscape value of large areas [39].
Based on the landscape characteristics of Tianmeng Mountain Scenic Spot and previous studies on the visual resources management system, seven sub-indicators and corresponding evaluation criteria were selected to reflect landscape quality: terrain, vegetation, water system, color, peculiarity, artificial construction, and adjacent landscape (Table 3). Thirty-four viewpoints (Figure S2) were photographed from three different perspectives by the same investigator with basic photographic skills, at a height of about 1.5 m and at an angle basically parallel to the line of sight. Four professionals (the staff of Tianmeng Mountain Scenic Spot and the students who participated in the investigation) were selected to evaluate photographs based on the criteria in Table 2. The scores of indicators were stacked together to obtain the results of each viewpoints and then averaged. The range was 0 < a ≤ 12, 12 < a ≤ 18, and 18 < a, corresponding to the four levels of very low, low, and medium, and assigned values of 1, 3, and 5, respectively.

2.3.2. Landscape Aesthetic Evaluation (LAE)

Scenic beauty estimation (SBE) is the main method in visual landscape quality evaluation [40]. It is based on psychophysical theory, using public perspective as the evaluation basis and setting the aesthetic evaluation value of the landscape for quantitative analysis.
The same photographs of 34 typical viewpoints as in Section 2.3.1 (4) were graded by 50 undergraduate students of landscape architecture (Table 4), and evaluators judged each slide by the beauty of the landscape. Seven criteria were chosen: “extremely beautiful, very beautiful, beautiful, ordinary, not very beautiful, not beautiful, and extremely unattractive” with corresponding scores ranging from 1 to 7 (Table 5). In order to eliminate or reduce the differences caused by the diverse aesthetic attitudes of judges, all evaluation results were standardized.

2.4. Integration of Landscape Networks

The landscape networks were composed of landscape sources (high-quality landscape viewpoints), landscape-dissemination paths, and landscape areas (ecological-resistance surfaces) by the MCR model. As a geographical processing model, it could predict the shortest and smartest paths among sites after full consideration of ecological status, and based on the source and sink theory that is now widely used in the establishment of ecological nodes, ecological corridors, ecological land-use [41], ecological security patterns [42], and urban expansion simulation [43]. The prediction of paths in the MCR model was based on the location of high-quality viewpoints and the ecological-resistance surfaces formed by the superposition of ecological-resistance factors, and then the path prediction was performed using the cost distance function of ArcGIS10.7.
(1) Landscape sources (high-quality landscape viewpoints): Refers to the viewpoints that have high landscape values and are popular with tourists. Among the 34 viewpoints mentioned above, viewpoints with good landscape performance in LVS and LAE were selected as first-level landscape source-points, and viewpoints with a high value in LAE but a low value in LVS were chosen as second-level landscape source-points.
(2) Ecological-resistance surfaces: The construction of ecological-resistance surfaces depends on the selection of resistance factors. Five factors related to ecological processes and landscape characteristics of Tianmeng Mountain Scenic Spot were considered in this study, they were normalized difference vegetation index (NDVI), distance from roads, land use and land cover (LULC), elevation, and relief amplitude. NDVI will reflect that the vegetation cover and ecological resistance are lower where there was more vegetation. The distance from the road that reflects the intensity of human interference was selected. Topographic features was the important resistance factors since the study area was dominated by continuous undulating mountains, so elevation and relief amplitude were chosen. In addition, LULC was chosen as land types can influence the rate and mode of propagation. By using the analytic hierarchy process (AHP) method to determine the weight of each factor [44] and overlaying it in ArcGIS 10.7, the ecological-resistance surfaces of Tianmeng Mountain Scenic Spot were constructed. The resistance factors were categorized into four levels, assigned as 1, 3, 5, and 7, and the weights of each factor were determined using AHP analysis (Table 6).
(3) Landscape-dissemination path: Combines aspects of landscape and ecological status by using high-quality viewpoints as sources and reflects the least-cost path after overcoming resistance during movement from one source to the others [47] based on the MCR model.

3. Results

3.1. Landscape Visual Assessment

3.1.1. Landscape Visual Sensitivity (LVS)

(1)
Evaluation criteria of landscape visual sensitivity
Four indicators were selected to construct the framework of LVS, and the weights of the indicators were assigned by the AHP method [44]. As shown in Table 2, among the evaluation criteria, it was shown that slope had the greatest influence on LVS and visibility probability had the least influence in Tianmeng Mountain Scenic Spot.
(2)
Sensitivity of each indicator
A higher sensitivity value means that it is easier to be noticed by tourists. As can be seen from Figure 3a, the high and medium sensitivity of the slope, which is mainly located in the ridgeline area with the high elevation, accounted for only 18.07%; the remaining areas were low or very-low sensitivity areas, which meant that most of the areas were not easily seen in the slope factor. The results of sensitivity of visual probability (Figure 3b), showed that the percentage of high-sensitivity areas was the lowest, accounting for 2.7% of the total area and mainly distributed in the hilltop area with high elevation. These areas contained major viewpoints of places such as Wanghai Tower, Tianmeng summit, and Qiludi. Very-low sensitivity areas made up the highest proportion of 60.95%, followed by medium- and low-sensitivity areas; the viewpoints located in these areas were not easily noticed by tourists. The results of relative distance from roads in Figure 3c showed that the high-sensitivity areas were mainly located within 100 m of both sides of the main tourist road. The remarkableness of landscape was an important indicator to determine visual sensitivity, and mainly depended on the contrast between the landscape and environment. The final results are shown in Table S1 and Figure 3d. High values were mostly concentrated in areas with a special geographical location and architectural style—the main building Wanghai Tower located at the high point of the mountain with a mean value of 26, followed by the Pedestrian Suspension Bridge, Feilong Springs, and Yuhuang Temple with the values of 23, 23, and 22, respectively.
(3)
Results of landscape visual sensitivity
Based on the analysis of the above four evaluation criteria, the distribution maps of each indicator and their corresponding values were obtained (Figure 3). Subsequently, the comprehensive results of LVS were obtained based on the superposition of the above indicators, as shown in Figure 4a.
The results of LVS in Figure 4a showed a trend of high sensitivity values in the northwest and low in the southeast of the entire scenic spot. The high-sensitivity area was mainly concentrated in the northwest and covered the most exciting and unique viewpoints, and a small part were distributed in the central area; the low-sensitivity area was mainly concentrated in the east, which was close to the village and showed a zonal distribution pattern along the main eastern traffic road. After standardization, Ropeway Viewing Platform had the highest visual sensitivity value of 2.22, owing to the spacious viewing space and its exceptional viewing effect based on the high altitude, followed by Valley of Wind and Yuhuang Temple with values 2.19 and 1.75, respectively. Grand View World, Valley of the Lovers, and RV Base were the three viewpoints with the lowest visual sensitivity scores of −1.49, −1.49, and −1.49, respectively (Table S2).

3.1.2. Landscape Aesthetic Evaluation (LAE)

LAE results are shown in Table S2. After standardization, a positive value indicates that the landscape is attractive compared to other attractions, while negative values indicated the opposite, and when the value is higher, it means that the landscape is more attractive.
Among the LAE results, Yuhuang Temple was highest with a standardized score of 1.89. It is one of the core viewpoints of Tianmeng Mountain Scenic Spot and famous for its Taoist architectural cluster, which had high scenic and aesthetic value. Wanghai Tower and Pedestrian Suspension Bridge had the same standardized score of 1.74, followed by Ropeway Viewing Platform and Tianmeng Summit. However, Linxin Pavilion had the lowest score of −1.72, followed by Lovers Valley and RV Base, with scores of −1.53 and −1.35, respectively; all three are located at the foot of Tianmeng Mountain and have no attractive landscape features compared to the viewpoints with high values.

3.1.3. The Combined Performance of LVS and LAE

In this paper, the standardized LVS and LAE were defined as positive if the values were greater than 0 and negative if the values less than 0, and they were combined and classified into four levels to indicate the levels of landscape quality (Table 7 and Table 8).
The results are shown in Figure 4b. In total, 34 viewpoints were classified into four levels: very-high, high, medium, and low, with the number of viewpoints being 11, 6, 10, and 7, respectively, which meant that most of the viewpoints on Tianmeng Mountain Scenic Spot were not in a relatively good condition and only 32.4% had good performance in both of the two aspects. The very-high-level viewpoints, which were the most attractive and characteristic areas of Tianmeng Mountain Scenic Spot and easily noticed by visitors, and mainly located at the top of the mountain in the northwest of Tianmeng Mountain Scenic Spot (such as Yuhuang Temple and Wanghai Tower) extending along to the Pedestrian Suspension Bridge, were in a good condition. The high number of viewpoints with negative LVS but positive LAE meant that while these viewpoints were attractive, they were not easily noticed by visitors, and most of these viewpoints such as Zhanlu Platform and Danqiu Exiled Fairy were located on the main tourist road at the back of the main mountain. The medium level had positive LVS but negative LAE. This type of viewpoint was characterized by being easily noticed, but landscape was not attractive, so there was an urgent need to redesign or retrofit their landscapes for enhancement. The low level with negative LVS and LAE represented that the landscape that was neither attractive nor easily noticed by tourists. These areas were generally concentrated in the locations stretching from the east and south entrances along the main tourist road to half way up the mountain. Due to the low height of these locations, they were not performing well in terms of visual sensitivity, while the landscape did not exhibit distinct regional characters.
Therefore, according to the different characteristics of the four levels, suggestions and measures should be proposed to promote the healthy and sustainable development of Tianmeng Mountain Scenic Spot and provide a basis for later planning. The classification (Table 8) and suggestions are as follows: (1) Landscape core viewpoints: very-high level. These are the core viewpoints of the entire Tianmeng Mountain Scenic Spot and represent the highest landscape quality. Therefore, it is critical to maintain the status stability. (2) Landscape-enhancement viewpoints: high and medium level. These are the two levels which urgently need to be enhanced based on the characteristics shown in Table 7 and could be improved through appropriate tour route planning and visual guidance. (3) Follow-up supplementary-development viewpoints: low level. Due to the location these viewpoints are not easy to be seen by tourists. Accordingly, they should be adjusted and reprogrammed for subsequent expansion and planning when the above two types have been adjusted.
In summary, the planning of Tianmeng Mountain Scenic Spot could be reasonably arranged based on the characteristics of the above three types, and the development and construction of the viewpoints can be carried out efficiently.

3.2. Spatial Distribution of Landscape Networks

3.2.1. Correlation Analysis

After standardization of LVS and LAE, scatter plots with Pearson’s correlations of the two types of data were created by Origin 2021. The correlation coefficient value between LVS and LAE was 0.598 and showed a significance level of 0.01, thus indicating a significant positive correlation.

3.2.2. Selection of Landscape Source-Points

Different source-points have distinct results for building landscape networks, and beauty was important for viewing. Through Pearson’s correlation analysis, the LVS and LAE had a strong positive correlation. Concurrently, it was crucial for the scenic spots with high landscape aesthetics to enhance the landscape quality. Therefore, the high-quality landscape viewpoints with high LAE (standardized values greater than 0) were selected to establish the landscape networks.
Based on the results of the assessment of 34 viewpoints in terms of LVS and LAE (Table S2), 11 very-high level viewpoints with positive LVS and LAE were selected as first-level landscape source-points, and 6 high-level viewpoints with positive LAE and negative LVS were selected as second-level landscape source-points. In general, 17 high-quality landscape viewpoints were selected with standardized LVS and LAE values, as shown in Table 9.

3.2.3. Landscape Networks in Tianmeng Mountain Scenic Spot

In order to establish the landscape networks of Tianmeng Mountain Scenic Spot and improve landscape planning for future development, the results of comprehensive visual analysis were combined with the MCR method to improve the landscape effectiveness of the viewpoints, establish the effective landscape-dissemination paths for landscape diffusion, and highlight several interesting aspects of landscape management.
The landscape networks consisted of three parts: high-quality landscape viewpoints, landscape-dissemination paths, and the core areas (ecological-resistance surface) among landscape viewpoints.
According to the weighted calculation of the resistance surfaces based on five resistance factors, the final ecological-resistance surface of Tianmeng Mountain Scenic Spot was obtained (Figure 5). Its distribution showed the characteristics of high resistance value in the edge area and low resistance value in the middle of Tianmeng mountain Scenic Spot.
Based on the natural break-point method of ArcGIS 10.7, ecological-resistance surface was segregated into four levels (Figure 5): low-resistance, medium-resistance, high-resistance, and extremely high-resistance, corresponding to the ecological buffer zone, ecological protection zone, landscape development zone, and landscape construction zone, with proportions of 26.76%, 40.32%, 23.65%, and 9.27%, respectively. The areas were mainly distributed in low- and medium-resistance levels, with the least proportion of areas being at the extremely high-resistance level, and each level showed a relatively obvious aggregation distribution feature. The medium-resistance level had the highest proportion of 40.32%, and was mainly located in the middle of the mountains, with coniferous forest dominated by black pine and broad-leaved forest dominated by acacia and hemlock trees being the main landscape characteristics. The second level was the low-resistance level, comprising 26.76%, and distributed in the central and eastern parts of Tianmeng mountain Scenic Spot and partially extending to the foot of the mountain. The proportion of the high-resistance level, which was adjacent to the extremely high-resistance area and served as its buffer zone, was 23.65%; most of it was distributed in the northwestern parts at the high elevation, and a small part in the foothill location around the mountain, near the villages and the Luyugou Reservoir. The extremely high-resistance level was the least represented, but the location had important characteristics and was mostly construction land, which covered most of the attractions, the villages, and the two water-storage reservoirs under construction in the south.
The landscape-dissemination paths were divided into two types: the core landscape-dissemination paths (Figure 6a) (established by the 11 first-level viewpoints) and the secondary landscape-dissemination paths (Figure 6b) (established by the 6 second-level viewpoints). Through cost-weighting analysis in ArcGIS 10.7, 11 core landscape-dissemination paths and 6 secondary landscape-dissemination paths were finally obtained. These showed the shortest and most efficient landscape-dissemination paths connecting high-quality viewpoints. Then, we superimposed high-quality landscape viewpoints, landscape-dissemination paths, and ecological-resistance surface to get the landscape networks of Tianmeng Mountain Scenic Spot (Figure 6c).

4. Discussion

In this article, firstly, the state of the landscape viewpoints was assessed based on the comprehensive visual evaluation from both subjective and objective aspects. Subsequently, the high-quality landscape viewpoints affecting the landscape of Tianmeng Mountain Scenic Spot were extracted to construct landscape networks, including the generation of landscape-dissemination paths and landscape areas.

4.1. Analysis from the Perspective of Visual Evaluation

With the increase of tourism activities and tourists, rapid expansion of landscape, while ignoring the landscape quality is not conducive to the sustainable development of scenic areas. Limited tourism resources need to be supported by efficient attractions, and improving the landscape quality of existing attractions is of great significance to scenic areas. Therefore, quantitative and comprehensive landscape quality assessment could provide an accurate, objective, decision-making basis for multi-purpose planning.
Many previous studies of landscape visual assessment have focused on subjective aesthetic evaluation of landscape quality, of which the SBE evaluation method, based on popular aesthetics, is the most commonly used internationally. This method focuses on the tourist’s preference [40,48], usually evaluating landscape photos for scoring [49]. In recent years, a small number of studies have begun to quantitatively analyze visual sensitivity at the objective level, usually by analyzing and overlaying visual sensitivity factors of the study area with the support of GIS [18,19,20,21,22,23]. The visual sensitivity factors are selected from terrain, visual probability, distance from the road, and other factors that can affect vision [20], and then the quantitative analysis can provide an accurate, objective, and intuitive decision basis for multi-purpose planning. Different than previous studies [12,20,49], this study does not rely solely on human preferences or objective-based landscape evaluation, but proposes a comprehensive method that combines subjective aesthetics and objective visual sensitivity, using the visual sensitivity and the SBE method to quantitatively analyze the landscape visual characteristics and human aesthetic perception, respectively, and to grade the landscape quality by integrating the two states.
The results of the comprehensive visual assessment could provide a decision-making basis for the improvement of the landscape quality. The negative LVS or negative LAE after standardization means that the viewpoints have bad performance in the corresponding aspects, which need to be targeted for improvement in the subsequent landscape-enhancement process. Negative LVS means that the visual point is not easily noticed by visitors and is caused by the location of the landscape itself, the distance from the main tourist road, or its own physical characteristics such as color and height, for example, Danqiu Exiled Fairy is located behind the main viewing surface of the mountain, and the peak blocks the view of visitors on the main tourist route. Therefore, improving the accessibility between the main tourist routes and the attractions is the main solution strategy for the current situation of its own landscape. Negative landscape aesthetics mean that the landscape is not attractive enough compared with other attractions; this kind of landscape needs to be re-modeled and designed, such as re-modeling of structures, vegetation planting design, or borrowing scenery. Comprehensive visual assessment quantitatively evaluates the quality of the landscape from both subjective and objective aspects, making the evaluation more comprehensive and credible.

4.2. Shortcomings and Future Development

The landscape network based on the MCR model is an analysis and prediction based on the ecological status using the existing high-quality viewpoints as the sources and could provide a good guide of green-infrastructure planning for the existing scenic areas. However, for undeveloped areas, finding high-quality visual points to establish the landscape network is somewhat difficult and requires a variety of methods to select and evaluate appropriate viewpoints. For the analysis of ecological status, the diversity of topographic changes, land-use types, and biological diversity is more advantageous for the identification of ecological resistance. However, for scenic areas with weak topographic changes, single land types, and low vegetation cover, the variations of the ecological-resistance factor and ecological-resistance surface are not prominent and it is not appropriate to use ecological resistance to identify ecological status, so there are still some limitations in the promotion and implementation of the method.
In addition, the establishment of the landscape network harmonizes the relationship between landscape quality and ecological protection, but it is not static and needs to be continuously adjusted with the changes of high-quality landscape viewpoints in the subsequent landscape enhancement of Tianmeng Mountain Scenic Spot. In the construction of the ecological-resistance surfaces, the ecological-resistance factors were selected based on the landscape characteristics of the study area. Tianmeng Mountain Scenic Spot is a typical mountainous region with outstanding topographic variability, rich vegetation resources, land cover types, and well-developed roads and other infrastructures, so slope, NDVI, distance from roads, land use and land cover (LULC), elevation, and relief amplitude were selected for the construction of ecological-resistance surfaces, but the selection of ecological-resistance factors should also consider more refined aspects, such as species, climate, etc. Therefore, the selection of appropriate factors needs to be further explored and evaluated.
The integration of high-quality landscape and ecological-resistance surfaces into a sustainable landscape network not only improves the service effectiveness of the viewpoints, but also protects the ecological stability and ecosystem health of Tianmeng Mountain Scenic Spot.

5. Conclusions

This study focused on the comprehensive evaluation of landscape visual quality based on human perception and landscape physical attributes, and the construction of a landscape network after full consideration of ecological status. It could be used to support the conservation of the Tianmeng Mountain Scenic Spot and enhance the landscape efficiency. The results showed that the landscape quality of Tianmeng Mountain Scenic Spot still needed to be improved as landscape viewpoints with both high landscape aesthetics and visual sensitivity only accounted for 32.4%. The subjective landscape aesthetics and objective landscape visual sensitivity in Tianmeng mountain Scenic Spot had a strong correlation in the evaluation of landscape quality, and improvement of landscape aesthetics could improve the quality of Tianmeng Mountain Scenic Spot to a certain extent. The comprehensive visual analysis of 34 viewpoints revealed the shortcomings of the landscape, such as the lack of landscape aesthetics but these locations were easily seen. Lack of accessibility despite the high landscape quality meant that three categories were formed according to the results of evaluation: landscape core viewpoints, landscape enhancement viewpoints, and follow-up supplementary-development viewpoints, so that the landscape status could be targeted to improve. Furthermore, the MCR model had a key role in selecting low-cost paths based on the distribution of high-quality landscape viewpoints and ecological resistance. Finally, it established 11 core landscape-dissemination paths and 6 the secondary landscape-dissemination paths, which could be efficient for movement and communication between landscape viewpoints. The results of the study could be applied to adjust the existing landscape and also to guide the subsequent landscape planning, especially for the lay-out of green infrastructure and viewpoints. In addition, the study is also applicable to other landscape types such as scenic areas and parks, which have both aesthetic and ecological value.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14030516/s1, Figure S1: 354 visual points at 100 m interval; Figure S2: Distribution map of main viewpoints; Table S1: Evaluation of VRM; Table S2: Evaluation of LAE and LVS.

Author Contributions

Conceptualization, M.X. and H.M.; methodology, M.X. and H.M.; software, M.X.; formal analysis, M.X.; investigation, M.X.; resources, M.X.; writing—original draft preparation, M.X.; writing—review and editing, M.X. and H.M.; funding acquisition, M.X. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by JST SPRING, Grant Number JPMJSP2119.

Data Availability Statement

The data presented in this study are available in the article.

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 14 00516 g001a 550Forests 14 00516 g001b 550
Figure 1. (a) The location, (b) land-use types, and (c) spatial-distribution patterns of the Tianmeng Mountain Scenic Spot.
Figure 1. (a) The location, (b) land-use types, and (c) spatial-distribution patterns of the Tianmeng Mountain Scenic Spot.
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Figure 2. The framework of landscape visual assessment.
Figure 2. The framework of landscape visual assessment.
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Figure 3. (a) Sensitivity of slope, (b) visual probability, (c) distance from the roads, and (d) remarkableness degree. From 1 to 7 represents an increase in visual sensitivity.
Figure 3. (a) Sensitivity of slope, (b) visual probability, (c) distance from the roads, and (d) remarkableness degree. From 1 to 7 represents an increase in visual sensitivity.
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Figure 4. (a) Landscape visual sensitivity of Tianmeng Mountain Scenic Spot. (b) The combined performance of LVS and LAE in Tianmeng Mountain Scenic Spot.
Figure 4. (a) Landscape visual sensitivity of Tianmeng Mountain Scenic Spot. (b) The combined performance of LVS and LAE in Tianmeng Mountain Scenic Spot.
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Figure 5. Ecological-resistance surface of Tianmeng Mountain Scenic Spot.
Figure 5. Ecological-resistance surface of Tianmeng Mountain Scenic Spot.
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Figure 6. (a) Distribution of the core landscape-dissemination paths, (b) distribution of the secondary landscape-dissemination paths, and (c) landscape patterns of Tianmeng Mountain Scenic Spot. The background graph shows ecological-resistance value, the color from green to red represents increasing ecological resistance, which means that migration is becoming more difficult.
Figure 6. (a) Distribution of the core landscape-dissemination paths, (b) distribution of the secondary landscape-dissemination paths, and (c) landscape patterns of Tianmeng Mountain Scenic Spot. The background graph shows ecological-resistance value, the color from green to red represents increasing ecological resistance, which means that migration is becoming more difficult.
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Table
Table 1. Information on data sources.
Table 1. Information on data sources.
DataSourcesResolutionAccessible Information from Data
Digital elevation model (DEM)China Geospatial Data Cloud Platform30 mSlope, elevation, relief amplitude
Sentinel 2 remote sensing imagesEuropean Space Agency10 mLand use and land cover (LULC),
normalized difference vegetation index (NDVI)
Landscape-viewpoint distribution map, CAD files on the current state of the landscape, plant species, and other related documentsThe management committee of Tianmeng Mountain Scenic Spot The tourist roads and 34 viewpoints of the location, shape, and area
Table
Table 2. Classification criteria of landscape visual sensitivity.
Table 2. Classification criteria of landscape visual sensitivity.
IndicatorsScoreWeights
1357
Very lowLowMediumHigh
Slope (°)0 ≤ α ≤ 1515 < α ≤ 3030 < α ≤ 4545 < α0.34
Distance from road (m)400 < a200 < a ≤ 400100 < a ≤ 20 0 ≤ a ≤ 1000.31
Visual probability0 ≤ a ≤ 88 < a ≤ 2530 < a ≤4545 < a0.15
Remarkableness degree0 ≤ a ≤ 1212 < a ≤ 1818 < a 0.2
Table
Table 3. Evaluation criteria of landscape remarkableness evaluation system.
Table 3. Evaluation criteria of landscape remarkableness evaluation system.
IndicatorDescriptionLandscape Quality
LevelScore
TerrainTerrain that is highly complex, varied, peculiar, or unusual.High5
Terrain has considerable variation and attractive features in details.Medium3
Terrain is flat and lacks variety and attractive features in details.Low1
VegetationThe vegetation is rich and varied, and has attractive shapes and textures.High5
There are only 1–2 types of vegetation.Medium3
The vegetation types are similar with little variation.Low1
WaterWater plays a dominant role in the landscape.High5
Water has a secondary and an auxiliary function in the landscape.Medium3
Lack of water or difficulty in seeing it even if it exists.Low1
ColorThe colors are contrasting, diverse, and vivid in the slopes, rocks, vegetation, water, and snow.High5
The colors have a certain variation and intensity, as well as a certain contrast with the rocks and vegetation, but play a secondary role in the composition of the landscape.Medium3
The variation and contrast of colors are weak and often have little meaning.Low1
PeculiarityIt is a rare landscape with local characteristics.High5
Although it has the same aspects as other landscapes, it still maintains its outstanding characteristics.Medium3
Although the scenery is very common locally, it attracts people’s attention.Low1
Artificial constructionIt plays a positive role in the quality of the scenery.High5
The mountain is damaged by unsuitable artificial factors.Medium3
Artificial construction destroyed the original scenery on a large scale.Low1
Adjacent landscapeIt plays a significant role in improving the landscape quality.High5
It plays a minor role in improving the quality of the scenery.Medium3
It has a minor effect on improving the quality of the scenery.Low1
Table
Table 4. Composition of the evaluators.
Table 4. Composition of the evaluators.
CategoryRemarkGenderNumber
Majors/studentsUndergraduate/major in landscape
architecture.		Male 25/female 2550
Table
Table 5. Evaluation criteria of landscape aesthetics.
Table 5. Evaluation criteria of landscape aesthetics.
Serial NumberLevelScore
1Extremely beautiful7
2Very beautiful6
3Beautiful5
4Ordinary4
5Not very beautiful3
6Not beautiful2
7Extremely unattractive1
Table
Table 6. The system of ecological-resistance factors.
Table 6. The system of ecological-resistance factors.
TypesScoreWeightsClassification Basis
1357
Slope (°)0 ≤ α ≤ 1515 < α ≤ 3030 < α ≤ 45α > 4523.70%Literature [37]
Normalized difference vegetation index (NDVI)0.88 < a0.64 < a ≤ 0.880.30 < a ≤ 0.640 ≤ a ≤ 0.3025.68%Natural break-point method
Distance from roads (m)0 ≤ a ≤ 100100 < a ≤ 200200 < a ≤ 400400 < a14.15%Based on the
characteristics of
Tianmeng Mountain Scenic Spot
Land use and land cover (LULC)ForestWaterBared landConstruction land17.30%Literature [45], natural break-point method
Elevation (m)0 ≤ a ≤ 312312 < a ≤ 483483 < a ≤ 667667 < a9.50%Natural break-point method
Relief amplitude (m)0 ≤ a ≤ 1818 < a ≤ 3232 < a ≤ 4848 < a9.68%Literature [46], natural break- point method
Table
Table 7. The combination performance of LVS and LAE.
Table 7. The combination performance of LVS and LAE.
LevelLVSLAEDescriptions (Combination Performance)Functions
Very-highPositive *Positive *Not only has good landscape quality, but is also easily noticed by tourists.Landscape core viewpoints
HighNegative *Positive *Good landscape quality, but not easily noticed by
tourists.		Landscape-enhancement viewpoints
MediumNegative *Negative *Relatively low landscape quality and not easily noticed by tourists.
LowPositive *Negative *Relatively low landscape quality, but easily noticed by tourists.Follow-up supplementary-development viewpoints
* The values of standardized LVS and LAE are defined as positive if they are greater than 0 and negative if they are less than 0.
Table
Table 8. The functional division of viewpoints.
Table 8. The functional division of viewpoints.
Serial NumberTypesViewpoints
1Landscape core viewpointsBirthplace of Yimeng Mountain Minor, Ropeway Viewing Platform, Wanghai Tower, Tianmeng Summit, Qiludi, Valley of Wind, Pedestrian Suspension Bridge, Yuhuang temple, Glass Viewing Platform of Tashan, Gourd Cliff, Children’s Play Area in the South.
2Landscape-enhancement viewpointsFlying Dragon Spring, Forest Rafting Platform, Zhanlu Platform, Danqiu Exiled Fairy, Zundao, Gourd Waterfall, Dongmeng Theatre,
Mountaineering Square in the East, Viewing Platform1, Viewing Platform 2,
Upper Ropeway entrance, Dawanghuan, Lin Xin Pavilion.
3Follow-up supplementary-development viewpointsWelcoming Feature, Shopping CTR, Entrance, Children’s Play Area in the East,
Dongmengshanfu Square, Grand View World, Yunmeng Tea Garden, RV Base,
Yixiantian, Valley of the Lovers.
Table
Table 9. Information about high-quality landscape viewpoints.
Table 9. Information about high-quality landscape viewpoints.
Serial NumberNameTypesStandardization of LVSStandardization of LAE
1Birthplace of Yimeng Mountain MinorLandscape
first-level source-points		0.221.15
2Ropeway Viewing Platform2.221.49
3Wanghai Tower0.691.74
4Tianmeng Summit0.221.21
5Qiludi0.040.81
6Valley of Wind2.190.35
7Pedestrian Suspension Bridge0.631.74
8Yuhuang Temple1.751.89
9Glass Viewing Platform of Tashan1.290.29
10Gourd Cliff0.630.07
11Children’s Play Area in the South0.820.2
12Flying Dragon SpringLandscape
secondary source-points		−0.241.15
13Forest Rafting Platform−1.020.72
14Zhanlu Platform−1.020.35
15Danqiu Exiled Fairy−0.560.35
16Zundao−0.930.35
17Gourd Waterfall−0.240.04
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Xu, M.; Matsushima, H. Establishing Landscape Networks Based on Visual Quality and Ecological Resistance: A Case Study in Tianmeng Scenic Spot, China. Forests 2023, 14, 516. https://doi.org/10.3390/f14030516

AMA Style

Xu M, Matsushima H. Establishing Landscape Networks Based on Visual Quality and Ecological Resistance: A Case Study in Tianmeng Scenic Spot, China. Forests. 2023; 14(3):516. https://doi.org/10.3390/f14030516

Chicago/Turabian Style

Xu, Menglin, and Hajime Matsushima. 2023. "Establishing Landscape Networks Based on Visual Quality and Ecological Resistance: A Case Study in Tianmeng Scenic Spot, China" Forests 14, no. 3: 516. https://doi.org/10.3390/f14030516

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