Evaluation and zoning for reforestation using the ANP fuzzy method (Case study: Saqezchichay Watershed, Ardabil, Iran)

Document Type : Scientific article

Authors

1 Assistant Prof., Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

2 Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran

Abstract

Increasing the expansion of deforestation in forested areas and increasing soil erosion and sediment in downstream of watersheds there necessitates forest development in those areas. So, before any forestry project, site selection of prone areas and land capability evaluation should be considered. The aim of this research was to study forest expansion capability using multi-criteria evaluation method in Saqezchichay watershed located in Namin, Ardabil province. First, land use maps for years 1989 and 2019 were prepared using the Support Vector Machine algorithm (Kappa coefficient = 0.91 and overall accuracy = 95.5%). Then, the degraded forestlands were identified and introduced as priority sites for reforestation. In the next step, 12 criteria were weighted using Analytical Network Process and were transformed to the same scale using the Fuzzy method. Finally, all layers were overlaid by the WLC method and resulted in a forestry capability map. Results showed that 28.81 percent of this area have a high or very high potential for reforestation. Moreover, precipitation, temperature, and soil depth were recognized as the most important criteria. The integrated map of the current forest area and the potential map revealed 41.94 percent of the current forest area was in an area with high or very high potential class, whereas 41.1 percent was located in an area with a moderate potential class for forest expansion. Based on the results, the study area has the capability for forest expansion. In addition, the ANP Fuzzy approach was able to identify suitable areas that are appropriate for forest expansion.

Keywords


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