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GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity
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.
GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity
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.
GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity
Huijuan Yang (author) / Yongning Li (author) / Zhidong Zhang (author) / Zhongqi Xu (author) / Xuanrui Huang (author)
2019
Article (Journal)
Electronic Resource
Unknown
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