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BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data

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TLDR
A new supervised burned area mapping software named BAMS (Burned Area Mapping Software) is presented in this paper, which computes several of the spectral indexes most commonly used in burned area detection and implements a two-phase supervised strategy to map areas burned between two Landsat multitemporal images.
Abstract
A new supervised burned area mapping software named BAMS (Burned Area Mapping Software) is presented in this paper. The tool was built from standard ArcGISTM libraries. It computes several of the spectral indexes most commonly used in burned area detection and implements a two-phase supervised strategy to map areas burned between two Landsat multitemporal images. The only input required from the user is the visual delimitation of a few burned areas, from which burned perimeters are extracted. After the discrimination of burned patches, the user can visually assess the results, and iteratively select additional sampling burned areas to improve the extent of the burned patches. The final result of the BAMS program is a polygon vector layer containing three categories: (a) burned perimeters, (b) unburned areas, and (c) non-observed areas. The latter refer to clouds or sensor observation errors. Outputs of the BAMS code meet the requirements of file formats and structure of standard validation protocols. This paper presents the tool’s structure and technical basis. The program has been tested in six areas located in the United States, for various ecosystems and land covers, and then compared against the National Monitoring Trends in Burn Severity (MTBS) Burned Area Boundaries Dataset.

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Journal ArticleDOI

Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa

TL;DR: In this paper, a locally adapted multitemporal two-phase burned area (BA) algorithm has been developed using as inputs Sentinel-2 MSI reflectance measurements in the short and near infrared wavebands plus the active fires detected by Terra and Aqua MODIS sensors.
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Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies

TL;DR: In this article, the authors presented a new global burned area (BA) product, generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) red (R) and near-infrared (NIR) reflectances and thermal anomaly data, thus providing the highest spatial resolution (approx. 250m) among the existing global BA datasets.
Journal ArticleDOI

Global burned area mapping from ENVISAT-MERIS and MODIS active fire data

TL;DR: In this paper, a global burned area (BA) algorithm based on MERIS imagery along with the assessment of the global BA results for three years (2006-2008) was developed within the Fire Disturbance project under the European Space Agency Climate Change Initiative programme, which aimed to generate long-term BA information for climate models.
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African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data.

TL;DR: In this paper, the relevance of small fires was estimated by comparing a BA product generated from Sentinel-2 MSI images (20m spatial resolution) with a widely used global BA product based on MODIS images (500 m) focusing on sub-Saharan Africa.
Journal ArticleDOI

30 m Resolution Global Annual Burned Area Mapping Based on Landsat Images and Google Earth Engine

TL;DR: In this paper, the authors proposed an automated pipeline for generating 30-m resolution global-scale annual burned area maps from time-series of Landsat images, and a novel 30m resolution Global annual Burned Area Map of 2015 (GABAM 2015) was released.
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GEMI: a non-linear index to monitor global vegetation from satellites

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