An outlook on varied ecological engineering solutions for landslide prevention

This review assesses ecological engineering solutions for landslide prevention and slope stabilization by synthesizing evidence identified through scientific databases. The review encompasses the idea of applying vegetation-based techniques, including live stakes, brush layering, revegetation, grasses, herbaceous plants, bamboo plantations, and lithophytic life forms, together with conventional and structural measures such as natural geotextiles, live wooden crib walls, wattle fences, live silt fences, and live gully breaks. The reviewed evidence highlights the importance of species with strong root systems, which can influence the effectiveness of bioengineering interventions. Species such as Vetiver, Bermuda Grass, Ryegrass, Alder, selected Ficus species, and bamboo show deep-rooted control over soil reinforcement, erosion, and slope stabilization, while lithophytic life forms and pioneer colonizers may support the restoration of exposed rocky and landslide-affected surfaces. The review also examines the contribution of artificial intelligence, remote sensing, unmanned aerial vehicles, LiDAR, interferometric synthetic aperture radar, and machine learning models in landslide susceptibility assessment, monitoring, and advance warning. Overall, the findings revealed that integrated ecological engineering and data-driven monitoring may complement conventional stabilization measures, reduce landslide risk, restore degraded slopes, and inform sustainable land-management planning.

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Publication Details

Journal
Journal of Environmental Science Health & Sustainability
Published
2026-11-01
DOI
https://doi.org/10.63697/jeshs.2026.10138
Primary Topic
Tree Root and Stability Studies
Type
article
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article

An outlook on varied ecological engineering solutions for landslide prevention

Ranjeet Kaur Parmar, Vikrant Arya, Ishant Yadav, Bharti Devi et al.
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Journal of Environmental Science Health & Sustainability
Tree Root and Stability Studies
article

An outlook on varied ecological engineering solutions for landslide prevention

Ranjeet Kaur Parmar, Vikrant Arya, Ishant Yadav, Bharti Devi, Simran Kour
article en

Abstract

This review assesses ecological engineering solutions for landslide prevention and slope stabilization by synthesizing evidence identified through scientific databases. The review encompasses the idea of applying vegetation-based techniques, including live stakes, brush layering, revegetation, grasses, herbaceous plants, bamboo plantations, and lithophytic life forms, together with conventional and structural measures such as natural geotextiles, live wooden crib walls, wattle fences, live silt fences, and live gully breaks. The reviewed evidence highlights the importance of species with strong root systems, which can influence the effectiveness of bioengineering interventions. Species such as Vetiver, Bermuda Grass, Ryegrass, Alder, selected Ficus species, and bamboo show deep-rooted control over soil reinforcement, erosion, and slope stabilization, while lithophytic life forms and pioneer colonizers may support the restoration of exposed rocky and landslide-affected surfaces. The review also examines the contribution of artificial intelligence, remote sensing, unmanned aerial vehicles, LiDAR, interferometric synthetic aperture radar, and machine learning models in landslide susceptibility assessment, monitoring, and advance warning. Overall, the findings revealed that integrated ecological engineering and data-driven monitoring may complement conventional stabilization measures, reduce landslide risk, restore degraded slopes, and inform sustainable land-management planning.

Journal of Environmental Science Health & SustainabilityVol. 2(4)
Government of Himachal Pradesh (IN)
Life on land
Openalex Percentile: Top 23%
Tree Root and Stability Studies
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An outlook on varied ecological engineering solutions for landslide prevention — Ranjeet Kaur Parmar, Vikrant Arya, et al. · Journal of Environmental Science Health & Sustainability (2026) | TGRS Research Map | TGRS