Shahid Beheshti University Advanced Environmental Sciences 3115-7173 6 2 2008 12 21 Forest Landscape-and-Ecological Degradation Assessment of Sefidrod Watershed; Using Landscape Ecological Metrics, in Gilan Province of Iran Forest Landscape-and-Ecological Degradation Assessment of Sefidrod Watershed; Using Landscape Ecological Metrics, in Gilan Province of Iran 95526 FA Nooshin Khazaei Department of Student of Environmental Planning & Management, Faculty of Environment, University of Tehran , Forod Azari Dehkordi Department of Student of Environmental Planning & Management, Faculty of Environment, University of Tehran Journal Article 2015 05 17 Landscape ecological metrics are quantitative tools that are used to evaluate the patterns of landscape. In this article we considered some landscape ecological metrics such as SDI (Shannon Diversity Index) or TE (Total Edge) to consider configuration and composition of the landscape patches. Then, a degradation model (DM) was conducted to compute the degradation hierarchy between working units. The DM was introduced as "LD" = ∑kI/V, where "LD" was degradation coefficient of landscape compartment, "k" (intensity) and "I" metrics of landscape, and "V" was vulnerability of the natural habitat (here number of patches in each working unit). Thirteen sub watersheds in Sefidrod Watershed were considered and thus, degradation model was deployed to assess the status of each working unit. On the other hand, if there are deep red pixels in an infrared image, there are more areas of older ecosystems. Therefore, to reveal relationship between a metric and the status of the ecosystems in each working unit, the pixel number of deep-redness of infrared images was plotted against each metrics. Therefore, it was cleared that SDI has the highest correlation (R2 = 0.85) with the color intensity of infrared images. Landscape ecological metrics are quantitative tools that are used to evaluate the patterns of landscape. In this article we considered some landscape ecological metrics such as SDI (Shannon Diversity Index) or TE (Total Edge) to consider configuration and composition of the landscape patches. Then, a degradation model (DM) was conducted to compute the degradation hierarchy between working units. The DM was introduced as "LD" = ∑kI/V, where "LD" was degradation coefficient of landscape compartment, "k" (intensity) and "I" metrics of landscape, and "V" was vulnerability of the natural habitat (here number of patches in each working unit). Thirteen sub watersheds in Sefidrod Watershed were considered and thus, degradation model was deployed to assess the status of each working unit. On the other hand, if there are deep red pixels in an infrared image, there are more areas of older ecosystems. Therefore, to reveal relationship between a metric and the status of the ecosystems in each working unit, the pixel number of deep-redness of infrared images was plotted against each metrics. Therefore, it was cleared that SDI has the highest correlation (R2 = 0.85) with the color intensity of infrared images.

https://envs.sbu.ac.ir/article_95526_cdf99d667527c15f3fb21c5273b251f3.pdf