The Belt and Road Initiative (BRI) is a project launched by the Chinese Government whose main goal is to connect more than 65 countries in Asia, Europe, Africa and Oceania developing infrastructures and facilities. To support the prevention or mitigation of landslide hazards, which may affect the mainland infrastructures of BRI, a landslide susceptibility analysis in the countries involved has been carried out during the presented PhD research activity. Due to the large study area, the analysis has been carried out using a multi-scale approach which consists of mapping susceptibility firstly at continental scale, in order to have an overview of the large study area, and then at national scale, where a detailed susceptibility map is required. The study area selected for the continental assessment is the south-Asia, where a pixel-based landslide susceptibility map has been carried out using the Weight of Evidence method and validated by Receiving Operating Characteristic (ROC) curves. The results highlighted several areas which require a second landslide susceptibility analysis at national scale, such as: the 83% of Tajikistan, the 92% of Nepal, the 98% of Bhutan, the 84% of Myanmar and the 94% of Laos which are moderately to very highly susceptible. In particular, we selected the regions of west Tajikistan and north-east India to be investigated at national scale. Data scarcity is a common condition for many countries involved into the Initiative. Therefore in addition to the landslide susceptibility assessment of west Tajikistan, which has been conducted using a Generalized Additive Model and validated by ROC curves, we have examined, in the same study area, the effect of incomplete landslide dataset on the prediction capacity of statistical models. Differently from what we expected, the variation in landslide presence significantly influences in a negative way the model prediction capacity only in the worst scenarios reproduced. The entire PhD research activity has been conducted using only open data and open- source software. In this context, to support the analysis of the last years an open-source plugin for QGIS has been implemented. The SZ-tool allows the user to make susceptibility assessments from the data preprocessing, susceptibility mapping with statistic-based models, to the final classification. The SZ-tool has been tested in the study area of north-east India which demonstrated the possibility to compute a complete landslide susceptibility assessment in few steps. All the output data of the analysis conducted during the presented PhD research are freely available and downloadable. This text describes the research activity of the last three years which is summed up in three main chapters. Each chapter reports the text of the articles published in international scientific journal during the PhD, titled: ’Landslide susceptibility in the Belt and Road Countries: continental step of a multi-scale approach’, ’When enough is really enough? On the minimum number of landslides to build reliable susceptibility models’ and ’Mapping susceptibility with open-source tools: a new plugin for QGIS’.
Landslide susceptibility in the Belt and Road Initiative
Giacomo Titti
Primo
2022
Abstract
The Belt and Road Initiative (BRI) is a project launched by the Chinese Government whose main goal is to connect more than 65 countries in Asia, Europe, Africa and Oceania developing infrastructures and facilities. To support the prevention or mitigation of landslide hazards, which may affect the mainland infrastructures of BRI, a landslide susceptibility analysis in the countries involved has been carried out during the presented PhD research activity. Due to the large study area, the analysis has been carried out using a multi-scale approach which consists of mapping susceptibility firstly at continental scale, in order to have an overview of the large study area, and then at national scale, where a detailed susceptibility map is required. The study area selected for the continental assessment is the south-Asia, where a pixel-based landslide susceptibility map has been carried out using the Weight of Evidence method and validated by Receiving Operating Characteristic (ROC) curves. The results highlighted several areas which require a second landslide susceptibility analysis at national scale, such as: the 83% of Tajikistan, the 92% of Nepal, the 98% of Bhutan, the 84% of Myanmar and the 94% of Laos which are moderately to very highly susceptible. In particular, we selected the regions of west Tajikistan and north-east India to be investigated at national scale. Data scarcity is a common condition for many countries involved into the Initiative. Therefore in addition to the landslide susceptibility assessment of west Tajikistan, which has been conducted using a Generalized Additive Model and validated by ROC curves, we have examined, in the same study area, the effect of incomplete landslide dataset on the prediction capacity of statistical models. Differently from what we expected, the variation in landslide presence significantly influences in a negative way the model prediction capacity only in the worst scenarios reproduced. The entire PhD research activity has been conducted using only open data and open- source software. In this context, to support the analysis of the last years an open-source plugin for QGIS has been implemented. The SZ-tool allows the user to make susceptibility assessments from the data preprocessing, susceptibility mapping with statistic-based models, to the final classification. The SZ-tool has been tested in the study area of north-east India which demonstrated the possibility to compute a complete landslide susceptibility assessment in few steps. All the output data of the analysis conducted during the presented PhD research are freely available and downloadable. This text describes the research activity of the last three years which is summed up in three main chapters. Each chapter reports the text of the articles published in international scientific journal during the PhD, titled: ’Landslide susceptibility in the Belt and Road Countries: continental step of a multi-scale approach’, ’When enough is really enough? On the minimum number of landslides to build reliable susceptibility models’ and ’Mapping susceptibility with open-source tools: a new plugin for QGIS’.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
