All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Areas of the Terai Arc landscape in Nepal at risk of forest fire identified by fuzzy analytic hierarchy process

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F23%3A97007" target="_blank" >RIV/60460709:41320/23:97007 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1016/j.envdev.2023.100810" target="_blank" >http://dx.doi.org/10.1016/j.envdev.2023.100810</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.envdev.2023.100810" target="_blank" >10.1016/j.envdev.2023.100810</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Areas of the Terai Arc landscape in Nepal at risk of forest fire identified by fuzzy analytic hierarchy process

  • Original language description

    Forest fire frequency has increased in South Asia in recent decades, with a growing impact on forest ecosystems. Nepal's Terai Arc Landscape (TAL) is one of the most ecologically important landscapes in Asia, hosting a great diversity of endangered flora and fauna. To better predict the threat of fire to forest ecosystems in the TAL, we identified fire-prone areas using fuzzy AHP methods. We produced a fire risk map by applying the weighted linear combination method using topographic (slope, aspect, and elevation), climatic (temperature, precipitation, and wind speed), biophysical (normalised difference vegetation index and landcover classes), and anthropogenic variables (distance to road and proximity to settlements). We then validated the map with records of past fires by applying a confusion matrix. The accuracy of our technique of fire location pre-diction was above 95%, with a kappa coefficient of 0.93 and AUC value of 0.83. Locations of medium to very high forest fire risk were found in around 51% of the study area, usually in the vicinity of areas affected by anthropogenic factors. This landscape-level study shows the potential of multicriteria prediction models to inform the preparation of national and regional forest fire management strategies and plans.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10511 - Environmental sciences (social aspects to be 5.7)

Result continuities

  • Project

    <a href="/en/project/EF16_019%2F0000803" target="_blank" >EF16_019/0000803: Advanced research supporting the forestry and wood-processing sector´s adaptation to global change and the 4th industrial revolution</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Environmental Development

  • ISSN

    2211-4645

  • e-ISSN

    2211-4645

  • Volume of the periodical

    45

  • Issue of the periodical within the volume

    2023

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    11

  • Pages from-to

    1-11

  • UT code for WoS article

    000939810100001

  • EID of the result in the Scopus database

    2-s2.0-85147902192