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Provedor de dados:  Anais da ABC (AABC)
País:  Brazil
Título:  Ecological capability evaluation for afforestation and forest expansion using Geographic Information System (GIS) in management area of Caspian Sea
Autores:  HASHEMI,SEYED A.
Data:  2018-12-01
Ano:  2018
Palavras-chave:  Ecological capability
Afforestation
AHP
Fuzzy
Forest
Resumo:  Abstract Ecological capability evaluation is referred to as evaluation of potential capability of land and determination of its natural land use. In this paper, ecological capability of Lille Basin in Lahijan was evaluated for afforestation and forest expansion using Geographical Information Systems (GIS). For this purpose, information layers (slope, elevation, geographical directions, temperature, rainfall, humidity, soil type, and canopy cover) were prepared by digitizing the data obtained from concerned organizations. First, the layers were prepared based on coordinate systems and pixel value. Then, they were standardized using fuzzy membership functions. The evaluation criteria were prioritized with regard to expert opinion, and by using multi-criteria evaluation method (MCE) and analysis of hierarchic process (AHP), and the final weight of each criterion was determined. The weight for 8 criteria including elevation, soil type, canopy cover (%), directions, slope, temperature, humidity, rainfall were 0.330, 0.210, 0.128, 0.117, 0.076, 0.054, 0.046 and 0.210, respectively. According to these weights, elevation has the highest value and the slope is the lowest. The results suggest that ecological capability exhibits sensitivity to variations of different criteria and its distribution is directly correlated to ecological factors especially climatic and physiographical ones. The incompatibility index (0.09) also indicated that the weights were logical. Then valuation of the maps performed. Finally, based on these values, capabilities of each environmental unit were identified and potentials of the area for afforestation were determined in five capability classes.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000703761
Editor:  Academia Brasileira de Ciências
Relação:  10.1590/0001-3765201820170805
Formato:  text/html
Fonte:  Anais da Academia Brasileira de Ciências v.90 n.4 2018
Direitos:  info:eu-repo/semantics/openAccess
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