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Special Issue "Application of Remote Sensing on Fire Ecology"

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Quantitative Methods and Remote Sensing".

Deadline for manuscript submissions: 30 April 2019

Special Issue Editor

Guest Editor
Prof. Dr. José M.C. Pereira

Forest Research Centre, School of Agriculture, University of Lisbon. Tapada da Ajuda 1349-017, Lisbon, Portugal
Website | E-Mail
Interests: Pyrogeography, remote sensing, landscape ecology of fire

Special Issue Information

Dear Colleagues,

Many fire ecology research and applications require georeferenced, dynamic data, and disciplines such as pyrogeography and landscape ecology are intrinsically spatial. Current rates of land use change and climate change lead to fast and widespread dynamics on terrestrial environments that affect spatial and temporal patterns of fire, at scales ranging from local to global. Remote sensing is essential to analyze those spatial dynamics and can provide data at a wide range of spatial, temporal and spectral resolutions.

For this Special Issue we invite submissions that address: 1) processes preceding fire occurrence, such as fuel structure and fuel moisture dynamics; 2) the incorporation of remote sensing information in dynamic vegetation models and in landuse/land cover change models; 3) post-fire environments, namely the characterization of burned areas in terms of fire patch attributes, fire severity assessment, and vegetation recovery rates; 4) methodological and technological issues in remote sensing of fire, such as the use of state-of-the-art artificial intelligence techniques for image analysis, or the use of Google Earth Engine for large scale processing of spatial time series of satellite imagery.

Prof. Dr. José M.C. Pereira
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fuels mapping
  • burned area mapping
  • fire severity assessment
  • vegetation recovery monitoring
  • AI for image classification
  • time series analysis

Published Papers (2 papers)

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Research

Open AccessArticle Illegal Selective Logging and Forest Fires in the Northern Brazilian Amazon
Forests 2019, 10(1), 61; https://doi.org/10.3390/f10010061
Received: 27 December 2018 / Revised: 10 January 2019 / Accepted: 11 January 2019 / Published: 14 January 2019
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Abstract
Illegal selective logging and forest fires occur on a large scale in the northern Brazilian Amazon, contributing to an increase in tree mortality and a reduction in forest carbon stock. A total of 120 plots of 0.25 ha (30 ha) were installed in [...] Read more.
Illegal selective logging and forest fires occur on a large scale in the northern Brazilian Amazon, contributing to an increase in tree mortality and a reduction in forest carbon stock. A total of 120 plots of 0.25 ha (30 ha) were installed in transitional ecosystems or ecotones (LOt) between the forested shade-loving campinarana (Ld) and dense-canopy rainforest, submontane (Ds), in the National Forest (Flona) of Anauá, southern Roraima. Measuring the diameters at breast height (DBH ≥ 10 cm) and the heights of 171 dead trees (fallen naturally, illegally exploited, and affected by forest fires), enabled the estimation of carbon content from the application of a biomass equation developed at Manaus, and the calculation of a correction factor, using the average height of the largest trees. From 2015–2017, we mapped the real extent of illegal selective logging and forest fires across the region with CLASlite and INPE/Queimadas. From measurements of 14,730 live and dead trees across 30 hectares (491 ± 15 trees·ha−1), the illegal selective logging and associated forest fires, and aggravation by severe El Niño droughts resulted in an 8.2% mortality of trees (40 ± 9 dead trees·ha−1) and a 3.5% reduction in forest carbon stock (6 ± 3 Mg·ha−1) in the short-term. The surface area or influence of forest fires of very high density were estimated in the south-central region of Roraima (8374 km²) and the eastern region of the Flona Anauá (37 km²). Illegal selective logging and forest fires in forest areas totaled 357 km² in the mosaic area, and 6 km² within Flona Anaua. Illegal selective logging and forest fires in the years of severe El Niño droughts threatened the maintenance of environmental services provided by Amazonian forests. Full article
(This article belongs to the Special Issue Application of Remote Sensing on Fire Ecology)
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Open AccessArticle Mapping Burn Severity of Forest Fires in Small Sample Size Scenarios
Forests 2018, 9(10), 608; https://doi.org/10.3390/f9100608
Received: 2 September 2018 / Revised: 26 September 2018 / Accepted: 28 September 2018 / Published: 30 September 2018
PDF Full-text (2686 KB) | HTML Full-text | XML Full-text
Abstract
Mapping burn severity of forest fires can contribute significantly to understanding, quantifying and monitoring of forest fire severity and its impacts on ecosystems. In recent years, several remote sensing-based methods for mapping burn severity have been reported in the literature, of which the [...] Read more.
Mapping burn severity of forest fires can contribute significantly to understanding, quantifying and monitoring of forest fire severity and its impacts on ecosystems. In recent years, several remote sensing-based methods for mapping burn severity have been reported in the literature, of which the implementations are mainly dependent on several field plots. Therefore, it is a challenge to develop alternative method of mapping burn severity using limited number of field plots. In this study, we proposed a support vector regression based method using multi-temporal satellite data to map the burn severity, evaluated its performance by calculating correlations between the predicted and the observed Composite Burn Index, and compared the performance with that of the regression analysis method (based on dNBR). The results show that the performance of support vector regression based mapping method is more accurate (RMSE = 0.46–0.57) than that of regression analysis method (RMSE = 0.53–0.68). Even with fewer training sets, it can map the detailed distribution of burn severity of forest fires and can achieve relatively better generalization, compared to regression analysis burn severity mapping methods. It could be concluded that the proposed support vector regression based mapping method is an alternative to the regression analysis method in small sample size scenarios. This method with excellent generalization performance should be recommended for future studies on burn severity of forest fires. Full article
(This article belongs to the Special Issue Application of Remote Sensing on Fire Ecology)
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