Document Type : Original Article
Authors
1
Research Group of Environmental Assessment and Risk, Research Center for Environment and Sustainable Development (RCESD), Department of Environment, Tehran, Iran.
2
Department of Environmental Studies, The Institute for Research and Development in the Humanities (SAMT), Tehran, Iran
3
Department of Environmental Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran
4
Research Group of Environmental Economics, Research Center for Environment and Sustainable Development (RCESD), Department of Environment, Tehran, Iran
5
Department of Natural Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran
10.22034/iwm.2026.2087988.1272
Abstract
Extended Abstract
Introduction: The ecosystem service associated with landscape aesthetic quality plays an important role in enhancing human well-being, mental health, and the perceptual experiences of communities. This service emerges through human interaction with natural and semi-natural landscapes and can generate considerable indirect economic effects on tourism, property values, and regional development. However, the quantification and valuation of such services have consistently faced methodological challenges due to their intangible nature and strong dependence on human perception. Focusing on Kohgiluyeh and Boyer-Ahmad Province, the present study aims to quantify and economically value the ecosystem service associated with landscape aesthetic quality at the watershed scale using a spatial–economic approach.
Materials and Methods: To quantify landscape aesthetic quality, the Scenic Quality module of the InVEST model was employed. Input data included a raster Digital Elevation Model (DEM), vector layers representing landscape-affecting elements (such as infrastructure and human-built facilities), the boundary of the study area, and optical parameters including the refractive index ratio. The model estimates the visibility of landscape elements using a viewshed algorithm. Subsequently, by assigning weights to visual scores and visual penalties, the raster layers were integrated to generate the final visual quality output. Landscape quality was categorized into several classes ranging from “no impact and high quality” to “low and very low quality,” representing the intensity of the visual effects of human activities on the landscape. In the next step, the economic valuation of the landscape aesthetic service was conducted using the benefit transfer method. Reference values for the economic value of aesthetic ecosystem services were extracted from relevent international studies. These values were standardized using economic indicators including gross domestic product per capita based on purchasing power parity, income elasticity of willingness to pay, exchange rate adjustments, and temporal updating to the base year 2024. Finally, the annual economic value was calculated and spatially allocated across pixels and sub-watersheds of the study area for further analysis.
Results and Discussion: The modeling results indicate that visual landscape quality at the watershed scale exhibits a heterogeneous spatial pattern and is strongly influenced by the spatial arrangement of human elements within the geomorphological structure of watersheds. Watersheds located in the northern and northwestern parts of the province, characterized by extensive natural cover, continuous topographic relief, and minimal human intervention, exhibit the highest levels of landscape quality. In these areas, topography and natural vegetation guide the visual field predominantly toward natural elements, thereby creating a high level of visual coherence. In contrast, watersheds in the southwestern parts and sections of the eastern province, where infrastructure and settlements are concentrated, display a more fragmented and patchy pattern of landscape quality. In these areas, the placement of human-made elements at locations with wide visibility affects large portions of the watershed and increases the spatial dispersion of visual quality. This pattern suggests that even limited interventions, when located at visually sensitive topographic positions, can exert substantial effects on watershed-scale landscape quality.
Conclusion: The results for the watersheds of the province indicate that, centers of human development in the southwest and areas of relatively pristine natural landscapes in the north and northeast represent the two ends of the spectrum of landscape aesthetic ecosystem services in the province. This spatial pattern should serve as a foundation for future conservation policies, landscape design strategies, and ecological management planning. In this regard, integrating the landscape quality index into urban planning can provide a more comprehensive perspective on the ecological condition of the landscape, thereby facilitating decision-making processes that influence the overall health of the landscape. On the other hand, approaches based on sustainable land management and the mitigation of anthropogenic pressures can contribute to landscape restoration and the gradual recovery of visual quality.
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