4.5 Article

Ecological risk assessment of regions along the roadside of the Qinghai-Tibet highway and railway based on an artificial neural network

Journal

HUMAN AND ECOLOGICAL RISK ASSESSMENT
Volume 13, Issue 4, Pages 900-913

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/10807030601105092

Keywords

ecological risk assessment; artificial neural network; MLP (multilayer perceptron) model; natural factors; artificial factors

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A concept model of regional risk was constructed for the characteristics of ecosystems alongside the Qinghai-Tibet highway and railway based on the MLP (Multilayer perceptron) model. Seven indices such as snow hazard, drought hazard, and landslide were selected in order to evaluate the integrated ecological risk of the ecosystems along the study area. Results show that the Qaidam montane desert zone had the greatest average risk value (4.26), followed by the Golog-Nagqu high-cold scrub meadow zone (2.80) and the East Qinghai and Qilian montane steppe zone (2.73) among the ecosystems within the six natural zones within the study region. As far as land cover types are concerned, the top three ecological risk values appear in the needle-leaved forest (4.31), desert (4.12), and land without vegetation (3.62), which are higher than those in the other seven types in the study site. Although the risk values are influenced by natural factors and human activities, they are more strongly controlled by natural factors. According to the ecological risk characteristics, the ecosystems within the study area are subdivided into four subregions, including the Qaidam. basin region (high risk), the Xidatan to Damxung region (moderate risk), and the Eastern Qinghai-Qilian (slight risk) and Southern Xizang (Tibet) region (slighter risk).

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