Assessing visual impacts of forest operations on a landscape in the Serre Regional Park of southern Italy

Scarfò, Francesco; Mercurio, Riccardo; Peso, Carlos del

doi:10.1007/s11355-011-0168-x

Cited by 14 publications

(9 citation statements)

References 15 publications

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“…The comparison of visual sensitivity in summer and autumn indicates that the two seasons differed significantly; thus, when analyzing visual sensitivity, seasonal impact should be considered. In previous studies, seasonality was not adequately studied, and visual sensitivity was investigated in only one season [22,65]. High visual sensitivity areas in different seasons should be superimposed to ensure that high visual sensitivity areas for one season are also protected in other seasons.…”

Section: Discussionmentioning

confidence: 99%

“…If the land use type was forests or shrubs, the height was the average height of the stand, which could be obtained from the data of inventory for forest management planning and design. The mean height of the accommodations area for visitors is 20 m, and that of villages is 4 m. When the DSM was used, blocking on the viewshed by surface factors such as vegetation was considered [39,42,65]. The viewpoints were categorized into two types [39], of which the majority of the viewpoints were horizontally-oriented with an offset height of 1.6 m, and some viewpoints were high above overlooking the forest landscape, and the offset heights were valuated based on the actual height difference as compared with the surrounding environment (Table 3).…”

Section: Calculation and Mapping Of Sub-criteriamentioning

confidence: 99%

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GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity

Yang

Zhang

et al. 2019

Forests

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Visual sensitivity assessments identify the location of the high-sensitivity areas in terms of visual change. Studying the visual sensitivity of plantation forest landscapes and their seasonal changes can help resolve increasingly frequent conflicts between tourism and forest management activities, in the context of the multi-functional management of plantation forests. In this study, we used the geographic information system (GIS) and multi-criteria evaluation (MCE) methods combined with the analytic hierarchy process (AHP) to perform a visual sensitivity evaluation. Nine map-based criteria were selected, and the visual sensitivity of summer and autumn values were calculated, using data from sources including inventory data for forest management planning and design, digital elevation model (DEM), and aerial photographs. Vegetation uniformity (VU) and color diversity (CD) indices were constructed using three patch-level-based landscape indices, including area (AREA), fractal dimension index (FRAC), and proximity (PROX), to visualize the summer and autumn vegetation characteristics of a plantation forest landscape. We conducted a case study on the Saihanba Mechanical Forest Plantation, China’s largest forest plantation. The results were evaluated by experts, confirming the method to be reliable. This study provides an accurate, objective, and visualized evaluation method for the visual sensitivity of plantations for forest management units at the landscape scale. In analyzing the visual sensitivity of plantation forest landscapes, appropriate criteria, e.g., uniformity or diversity should be selected based on forest vegetation characteristics. When identifying high-sensitivity regions, it is necessary to simultaneously analyze areas with high visual sensitivity in different seasons and then superimpose the results.

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Section: Discussionmentioning

confidence: 99%

Section: Calculation and Mapping Of Sub-criteriamentioning

confidence: 99%

GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity

Yang

Zhang

et al. 2019

Forests

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“…Some scholars engaged in park landscape research have mainly focused on the forest edge landscape and plant landscape of parks. Only a few scholars have conducted research on the visual landscape of park recreational spaces [30] and main pedestrian corridors [31,32], where they only focused on the relationship between the visual preference or visual influence of visitors and the landscape designs or operations of scenic spots. 2.…”

Section: Related Literaturementioning

confidence: 99%

“…Yao [9] found that the visual perception of green landscapes in rural residential areas is affected by the vegetation type, vegetation area, color contrast, green space openness, terrain type, and positive human factors. Scarfò [31] evaluated the visual impact of forest operations on the landscape through a GIS analysis of three landscape features (visibility, forest landscape quality, and visual sensitivity) in the main tourism corridors of a reserve. Polat [30] found that the water area, widths of pedestrian passages, and functions of leisure areas have a positive impact on the visual quality of the landscape area.…”

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confidence: 99%

Elderly Suitability of Park Recreational Space Layout Based on Visual Landscape Evaluation

Sun

2021

Sustainability

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Urban parks are critical for sustainable urban development. They are of theoretical and practical significance for analyzing the visual landscape of recreational spaces from the perspective of the elderly. This analysis can be used for exploring new methods for optimizing recreational space layouts to improve the physical and mental health of the elderly in parks, thus realizing the sustainable development of urban society. Taking Ziyang Park in Shangrao Central District of Jiangxi Province, China, as an example, starting from the visual characteristics of the elderly, this study quantitatively calculated the landscape viewability, total view ratio, and water view ratio for the elderly in each recreational space using Python Scripting for ArcGIS. We briefly express the elderly suitability of the visual landscape for each recreational space through a weighted synthesis of the calculation results. Our findings show that, in Ziyang Park, the elderly suitability of the visual landscape for recreational spaces is not only low overall, but also gradually decreases from the interior to the exterior of this park. Moreover, this spatial distribution may be caused by the location of zoning, surface elevation, and road slopes, as well as the individual characteristics of each recreational space. Finally, we discuss the requirements of the elderly for some geographical factors, along with the feasibility of using ArcGIS 3-D analysis to optimize the layout of the park recreational space, with the aim of providing a new research perspective and an effective reference method for designing layouts of such spaces that are favorable for the elderly to better guarantee the sustainable development of urban society.

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“…For almost 50 years, investigators have been seeking quantitative methods to predict and assess the visual and environmental quality of the landscape. The literature on this subject is vast and continues as illustrated through recent investigations and contributions by psychologists, engineers, landscape architects, planners, and natural resource specialists [1][2][3][4][5][6][7][8][9][10][11]. One of the best summaries of the early efforts was described by Taylor et al [12].…”

Section: Introductionmentioning

confidence: 99%

A Visual Quality Prediction Map for Michigan, USA: An Approach to Validate Spatial Content

Yilmaz¹,

Liu²,

Burley³

2019

Land Use - Assessing the Past, Envisioning the Future

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For a least the last half-century, scholars have been seeking methods to predict and assess the visual and environmental quality of the landscape. In these investigations, some scholars have been interested in applying predictors to create maps, representing visual and environmental quality. In our study, we employed a reliable environmental quality prediction equation that assesses environmental quality to create a validated visual quality map of Michigan containing a variance of 0.67, containing an overall p-value less than 0.0001, and p-values less than or equal to 0.05 for each predictor. Measures ranging in the mid-40s and 50s indicate a moderate level of environmental quality, while scores in the 80s through 110 indicate a very poor environmental quality. Through the Kendall's coefficient of concordance statistical test, we determined that the map is significantly reliable (p ≤ 0.005) and conclude that constructing such a large area (250,493 km 2) is possible. This type of map can be employed to evaluate progress and decline in measuring the environmental quality/land-use change of extensive landscape areas.

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Assessing visual impacts of forest operations on a landscape in the Serre Regional Park of southern Italy

Cited by 14 publications

References 15 publications

GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity

GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity

Elderly Suitability of Park Recreational Space Layout Based on Visual Landscape Evaluation

A Visual Quality Prediction Map for Michigan, USA: An Approach to Validate Spatial Content

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