A global review of remote sensing of live fuel moisture content for fire danger assessment: Moving towards operational products

M Yebra, PE Dennison, E Chuvieco, D Riaño… - Remote Sensing of …, 2013 - Elsevier
One of the primary variables affecting ignition and spread of wildfire is fuel moisture content
(FMC). Live FMC (LFMC) is responsive to long term climate and plant adaptations to …

Integrated wildfire danger models and factors: A review

I Zacharakis, VA Tsihrintzis - Science of the total environment, 2023 - Elsevier
Wildfires have been systematically studied from the early 1950s, with significant progress in
the applied computational methodologies during the 21st century. However, modern …

[图书][B] The normalized difference vegetation index

N Pettorelli - 2013 - books.google.com
There has been a recent surge of interest in remote sensing and its use in ecology and
conservation but this is the first book to focus explicitly on the NDVI (Normalised Difference …

Performance evaluation of machine learning methods for forest fire modeling and prediction

BT Pham, A Jaafari, M Avand, N Al-Ansari, T Dinh Du… - Symmetry, 2020 - mdpi.com
Predicting and mapping fire susceptibility is a top research priority in fire-prone forests
worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB) …

[图书][B] Use of the Normalized Difference Vegetation Index (NDVI) to assess Land degradation at multiple scales: current status, future trends, and practical …

GT Yengoh, D Dent, L Olsson, AE Tengberg… - 2015 - books.google.com
This report examines the scientific basis for the use of remotely sensed data, particularly
Normalized Difference Vegetation Index (NDVI), primarily for the assessment of land …

[图书][B] Fundamentals of satellite remote sensing: An environmental approach

E Chuvieco - 2020 - taylorfrancis.com
Fundamentals of Satellite Remote Sensing: An Environmental Approach, Third Edition, is a
definitive guide to remote sensing systems that focuses on satellite-based remote sensing …

A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using LogitBoost machine learning classifier and multi-source …

MS Tehrany, S Jones, F Shabani… - Theoretical and Applied …, 2019 - Springer
A reliable forest fire susceptibility map is a necessity for disaster management and a primary
reference source in land use planning. We set out to evaluate the use of the LogitBoost …

Development of a framework for fire risk assessment using remote sensing and geographic information system technologies

E Chuvieco, I Aguado, M Yebra, H Nieto, J Salas… - Ecological …, 2010 - Elsevier
Forest fires play a critical role in landscape transformation, vegetation succession, soil
degradation and air quality. Improvements in fire risk estimation are vital to reduce the …

[HTML][HTML] Simulation of forest fire spread based on artificial intelligence

Z Wu, B Wang, M Li, Y Tian, Y Quan, J Liu - Ecological Indicators, 2022 - Elsevier
This article aims to provide a more practical forest fire spread model for predicting and
managing forest fires in Heilongjiang Province, China. Heilongjiang is dominated by …

[HTML][HTML] Examining the effects of forest fire on terrestrial carbon emission and ecosystem production in India using remote sensing approaches

S Sannigrahi, F Pilla, B Basu, AS Basu, K Sarkar… - Science of the Total …, 2020 - Elsevier
Remote sensing techniques are effectively used for measuring the overall loss of terrestrial
ecosystem productivity and biodiversity due to forest fires. The current research focuses on …