Decision support tools, systems and indices for sustainable coastal planning and management: A review

M Barzehkar, KE Parnell, T Soomere… - Ocean & Coastal …, 2021 - Elsevier
Coasts worldwide are facing enormous challenges relating to extreme water levels,
inundation and coastal erosion. These challenges need to be addressed with consideration …

[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility map**

L Lv, T Chen, J Dou, A Plaza - … Journal of Applied Earth Observation and …, 2022 - Elsevier
Landslides are highly hazardous geological disasters that can potentially threaten the safety
of human life and property. As a result, landslide susceptibility map** (LSM) plays an …

Machine learning-based landslide susceptibility assessment with optimized ratio of landslide to non-landslide samples

C Yang, LL Liu, F Huang, L Huang, XM Wang - Gondwana Research, 2023 - Elsevier
Abstract Machine learning models have been widely used for landslide susceptibility
assessment (LSA) in recent years. The accuracy of machine learning-based LSA often …

Snow and ice avalanches in high mountain Asia–scientific, local and indigenous knowledge

A Acharya, JF Steiner, KM Walizada… - … Hazards and Earth …, 2023 - nhess.copernicus.org
The cryosphere in high mountain Asia (HMA) not only sustains the livelihoods of people
residing downstream through its capacity to store water but also holds the potential for …

[HTML][HTML] DEM resolution effects on machine learning performance for flood probability map**

M Avand, A Kuriqi, M Khazaei… - Journal of Hydro …, 2022 - Elsevier
Floods are among the devastating natural disasters that occurred very frequently in arid
regions during the last decades. Accurate assessment of the flood susceptibility map** is …

Flood susceptibility map** using an improved analytic network process with statistical models

P Yariyan, M Avand, RA Abbaspour… - … , Natural Hazards and …, 2020 - Taylor & Francis
Flooding is a natural disaster that causes considerable damage to different sectors and
severely affects economic and social activities. The city of Saqqez in Iran is susceptible to …

Snow avalanche susceptibility map** using novel tree-based machine learning algorithms (XGBoost, NGBoost, and LightGBM) with eXplainable Artificial …

MC Iban, SS Bilgilioglu - Stochastic Environmental Research and Risk …, 2023 - Springer
This study examines the use of snow avalanche susceptibility maps (SASMs) to identify
areas prone to avalanches and develop measures to mitigate the risk in the Province of …

Landslide susceptibility zonation using statistical and machine learning approaches in Northern Lecco, Italy

M Mehrabi - Natural Hazards, 2021 - Springer
This study deals with landslide susceptibility map** in the northern part of Lecco Province,
Lombardy Region, Italy. In so doing, a valid landslide inventory map and thirteen …

[HTML][HTML] Multi-hazard exposure map** using machine learning for the State of Salzburg, Austria

TG Nachappa, O Ghorbanzadeh, K Gholamnia… - Remote Sensing, 2020 - mdpi.com
We live in a sphere that has unpredictable and multifaceted landscapes that make the risk
arising from several incidences that are omnipresent. Floods and landslides are widespread …

Determination of flood probability and prioritization of sub-watersheds: A comparison of game theory to machine learning

M Avand, AN Khiavi, M Khazaei… - Journal of Environmental …, 2021 - Elsevier
Floods often significantly impact human lives, properties, and activities. Prioritizing areas in
a region for mitigation based on flood probability is essential for reducing losses. In this …