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For the topographic factors, the common values of the slope and elevation of the assessed unit were calculated using a digital elevation model Yingkou Institute Of Know-howYingkou Institute Of Expertiseyingkou institute of technologyLawyer YingkouLawyer Yingkou

Each variable was first standardized and normalized via a z-score standardization methodology. Independent variables had been tested by variance inflation elements to keep away from multicollinearity and variable redundancy. The world autocorrelation evaluation and all regression models had been carried out on GeoDa1.6.7 software.

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The degree of spatial autocorrelation could be measured by Moran’s I. First, the land use data used in this examine had been sourced from remote-sensing images and different institutions; however, the classification of pictures cannot be one hundred pc appropriate, and the spatial misalignment of knowledge could have resulted in incorrectly assessed pattern and processes of fragmentation . Therefore, knowledge processing is important to minimize back the misdetection of fragmentatio Spatial autocorrelation is amongst the primary problems in spatial data evaluation . A optimistic Moran’s I value indicates a common pattern of clustering in a space of similar values . Although this study assessed forest fragmentation and its determinants at completely different scales, there are still several limitations. In the current study, the worldwide Moran’s I was used to measure the degree of spatial autocorrelation of forest fragmentation at panorama stage.