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Joshua Nathan Jones

Researcher at University of Plymouth

Publications -  6
Citations -  65

Joshua Nathan Jones is an academic researcher from University of Plymouth. The author has contributed to research in topics: Landslide & Monsoon. The author has an hindex of 3, co-authored 6 publications receiving 14 citations. Previous affiliations of Joshua Nathan Jones include University of East Anglia.

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Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling

TL;DR: In this article, the authors proposed a landslide susceptibility model that assumes that landslide occurrence is time-independent, even though process process is not necessarily independent of the landslide susceptibility, and used it in landslide risk management strategies.
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30-year record of Himalaya mass-wasting reveals landscape perturbations by extreme events.

TL;DR: In this article, the authors quantified the magnitudes of mass-wasting caused by the Asia Summer Monsoon (ASM), extreme rainfall and earthquakes in the Nepal Himalayas.
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Characteristics of landslide path dependency revealed through multiple resolution landslide inventories in the Nepal Himalaya

TL;DR: In this paper, the authors investigated and quantified landslide path dependency in the Nepal Himalaya by applying several path dependent metrics to three monsoon-triggered landslide inventories for two different spatial and temporal resolutions.
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Coseismic and monsoon-triggered landslide impacts on remote trekking infrastructure, Langtang Valley, Nepal

TL;DR: In this article, qualitative and quantitative observations from fieldwork and remote sensing are used to describe the materials and geomorphology of the landslides across Langtang Valley, and quantify the extent to which coseismic and monsoon-triggered landslides have affected Langding9s trekking infrastructure.

Implementing the Sendai framework in developing countries using remote sensing techniques for the evaluation of natural hazards

TL;DR: The potential of available “Open Source” data, such as ASTER/SRTM Digital Elevation Models (DEMs) and Landsat/Sentinel satellite imagery, coupled with a range of processing techniques, for the cost and time effective screening and preliminary assessment of arange of natural hazards is evaluated.