Application of remote sensing data for forest fires severity assessment

Nedkov, Roumen; Velizarova, Emiliya; Molla, Ibrahim; Radeva, Kameliya

doi:10.1117/12.2325742

Cited by 5 publications

(2 citation statements)

References 23 publications

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“…Once an LFF has occurred, a strategy for restoration or land recovery must be studied: on-site treatments [24] and restoration activities are evaluated [25,26], the evolution of the burned wildland is monitored [27,28], and the likely future downstream impacts due to flooding, landslides, and soil erosion are estimated [29]. To perform this decision-making process in postfire management, the characterization of the burned areas becomes a key input.…”

Section: Introductionmentioning

confidence: 99%

Event-Based Integrated Assessment of Environmental Variables and Wildfire Severity through Sentinel-2 Data

Picos

Alonso

Bastos

et al. 2019

Forests

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To optimize suppression, restoration, and prevention plans against wildfire, postfire assessment is a key input. Since little research has been carried out on applying Sentinel-2 imagery through an integrated approach to evaluate how environmental parameters affect fire severity, this work aims to fill this gap. A set of large forest fires that occurred in northwest Spain during extreme weather conditions were adopted as a case study. Sentinel-2 information was used to build the fire severity map and to evaluate the relation between it and a set of its driving factors: land cover, aspect, slope, proximity to the nearest stream, and fire recurrence. The cover types most affected by fire were scrubland, rocky areas, and Eucalyptus. The presence of streams was identified as a major cause of the reduced severity of fires in broadleaves. The occurrence of fires in the past is linked to the severity of fires, depending on the land cover. This research aims to help fire researchers, authority managers, and policy makers distinguish the conditions under which the damage by fire is minimized and optimize the resources allocated to restoration and future fire suppression.

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Section: Introductionmentioning

confidence: 99%

Event-Based Integrated Assessment of Environmental Variables and Wildfire Severity through Sentinel-2 Data

Picos

Alonso

Bastos

et al. 2019

Forests

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“…As a matter of fact, we speak about the application of the mathematical apparatus, namely, of wavelet analysis in the subsystem of detecting the unauthorized WDSs, while working with aerospace information, primarily for automated decryption. As different information technologies with multiple characteristics emerge, remote monitoring of various phenomena and objects is now quite possible and is widely used [1,12,[22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Investigation of the basic Haar wavelet-transformations in the problem of decryption of space images on detection of waste disposal fields

Kazaryan¹,

Shahramanian²,

Zabunov³

2018

ARB

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In this paper, we study the use of orthogonal transformations, namely, the basic Haar wavelet transforms, for data processing of the Earth remote sensing. The internal structure of orthogonal Haar transforms is considered. The Haar matrix is divided into blocks of the same type, so that parallelization of the computations is possible. The expediency of replacing the spectral components corresponding to the whole block (or several blocks) of the original matrix with zeros is asserted. Theoretical and experimental studies are carried out to improve the results of image classification (on the example of cluster analysis). The Haar wavelet expansion coefficients are used as indicators when decoding space images for the presence of waste disposal sites. The aim of this paper is to describe the approach, on the basis of which an optimal method is established on a class of vectors with real components, application of two-dimensional discrete Haar wavelet transformations in the problem of recognition of space images for the presence of waste disposal sites. General methodology of research. The paper uses elements of mathematical analysis, wavelet analysis, the theory of discrete orthogonal transformations, and methods for decoding cosmic images. Scientific novelty. Encoding by means of conversion is an indirect method, especially effective in processing of two-dimensional signals, in particular, space images used for remote sensing of the Earth. We propose the approach that takes into account the structure of the wavelet-Haar matrix, while recognizing waste disposal fields by means of space images. The article comprises the result of the experimental application of wavelet-Haar transformations for decoding of space images. We consider this case, both with and without the technique of taking into account the structure of the wavelet-Haar matrices.

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