Availability of accurate and objective landslide susceptibility maps depicting zones defined on the basis of probability of occurrence of landslides is one of the critical inputs in assessing risk to property and lives in any mountainous region, particularly in the Himalayas. The aim of this study is to assess the utility of soft computing tools, namely, neural network, fuzzy and neuro-fuzzy ap...

Runoff forecasting in mountainous regions with processed based models is often difficult and inaccurate due to the complexity of the rainfall-runoff relationships and difficulties involved in obtaining the required data. Machine learning models offer an alternative for runoff forecasting in these regions. This paper explores and compares two machine learning methods, support vector regression (...

The mineral ore potential of many mountainous regions of the world, like the Kurdistan region of Iraq, remains unexplored. For logistical and sometimes political reasons, these areas are difficult to map using traditional methods. We highlight the improvement in remote sensing geological mapping that arises from the integration of geomorphic features in classifications. The Mawat Ophiolite Comp...

Extreme weather events have become more frequent and are likely linked to increases in greenhouse gases and aerosols, which alter the Earth’s radiative balance and cloud processes. On 8–9 July 2013, a catastrophic flood devastated the mountainous area to the northwest of the Sichuan Basin. Atmospheric simulations at a convection-permitting scale with aerosols and chemistry included show that he...

In three-dimensional (3D) navigation, if mountainous terrain is displayed based on ordinary perspective projection, viewers often find that the features of interest are occluded, which prevents an overview of the features. This paper presents an approach for the automatic generation of consecutive nonperspective views of mountainous terrain. The proposed method can generate views without occlus...

Soil depth is an important input parameter in hydrological and ecological modeling. Presently, the soil depth data available in national soil databases (STATSGO, SSURGO) is provided as averages within generalized map units. Spatial uncertainty within these units limits their applicability for spatially distributed modeling. This work reports a statistical model for prediction of soil depth in a...

Despite their rich energy renewable potential, mountainous areas suffer from energy poverty. A viable solution seems to be the radical turn towards renewable resources. Any tailor-cut energy planning for mountainous areas presupposes the adequate estimation of the energy demand of buildings, which in this case is hindered by the lack of long-term meteorological data, especially in remote, high ...

Due to limitations of 0.618 pole method, the triangle method and the champ ground resistance tester method on grounding resistance measurement of transmission lines and towers under conditions of complex landscape in a mountainous area, it adopts a generalized three-electrode grounding resistance measurement method which arranges electrode flexibly in the grounding resistance measurement of tra...

This paper introduces a new open source, knowledge-based framework for automatic interpretation of remote sensing images, called InterIMAGE. This framework owns a flexible modular architecture, in which image processing operators can be associated to both root and leaf nodes of the semantic network, which constitutes a differential strategy in comparison to other object-based image analysis pla...

The aim of this study was to test whether there is an association between elevation and cognitive function among elderly residents in rural mountainous areas. Data were collected in 2012 from a cross-sectional study conducted in Ohnan Town, which is located in a rural mountainous area in the southern part of Shimane Prefecture, Japan. Cognitive function was evaluated using CADi (Cognitive Asses...