Reprint

Sustainable Forest Management and Natural Hazards Prevention

Edited by
September 2024
274 pages
  • ISBN978-3-7258-2036-8 (Hardback)
  • ISBN978-3-7258-2035-1 (PDF)

This is a Reprint of the Special Issue Sustainable Forest Management and Natural Hazards Prevention that was published in

Business & Economics
Environmental & Earth Sciences
Social Sciences, Arts & Humanities
Summary

This reprint compiles cutting-edge research from 74 authors across 18 countries, addressing the critical challenges facing forest ecosystems worldwide. With deforestation progressing at alarming rates and environmental hazards intensifying, this work presents interdisciplinary perspectives on sustainable forest management and risk mitigation strategies. The articles in this collection highlight the necessity of advanced techniques, reliable data, and tailored approaches to achieve long-term sustainability and resilience. They emphasize the complex interplay between human activities and environmental health, advocating for the integration of innovative methodologies in forest management, ecological restoration, and occupational safety.Key topics covered include the following:- Innovative strategies and technologies for sustainable forest management and hazard prevention;- Risk and vulnerability assessment frameworks;- Adaptation programs to enhance ecosystem resilience;- Historical impact analysis and future vulnerability predictions under climate change scenarios.

Format
  • Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
ANFIS; beech; chestnut-leaved oak; Hyrcanian forests; MLP; landcreep; landslide; vulnerability criteria; slope type; parent rock; forest fire susceptibility; frequency ratio; analytic hierarchy process; Syria; permanent sample plot; matrix model; allowable cut; harvest rate; stable diameter distribution; COVID-19; urban heat island; vegetation indices; land use; land cover; albedo; climate change; Iran; land surface temperature; global warming; entinel data; remote sensing; machine learning; mangroves; landscape patterns; driver analysis; machine learning; MODIS; OpenStreetMap; random forest; forest fire occurrence mapping; WorldClim; natural resources; official statistics; wood; circular economy; European Union; illegal logging trade; current status; response actions; sustainability expectation; China; forest fires; OHS; OHS performance; multi-criteria decision-making; AHP; Changdao; Pinus thunbergii; pine wood nematode; forest management; tree clearance; peat; peat chemical; peat water environment; Melaleuca forest regeneration; U Minh Thuong National Park; Vietnam; microenvironment; beech seedling; soil compaction; seedling architecture; canopy gap; n/a