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Automated Mapping of Burned Areas in Semi-arid Ecosystems Using Modis Time-series Imagery : Volume Xl-7/W3, Issue 1 (29/04/2015)

By Hardtke, L. A.

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Book Id: WPLBN0004016023
Format Type: PDF Article :
File Size: Pages 4
Reproduction Date: 2015

Title: Automated Mapping of Burned Areas in Semi-arid Ecosystems Using Modis Time-series Imagery : Volume Xl-7/W3, Issue 1 (29/04/2015)  
Author: Hardtke, L. A.
Volume: Vol. XL-7/W3, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus Publications
Publication Date:
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications


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Del Valle, H. F., Blanco, P. D., Sione, W. F., Metternicht, G. I., & Hardtke, L. A. (2015). Automated Mapping of Burned Areas in Semi-arid Ecosystems Using Modis Time-series Imagery : Volume Xl-7/W3, Issue 1 (29/04/2015). Retrieved from

Description: National Patagonian Center-Argentinean National Research Council, Terrestrial Ecology Unit, U9120ACD Puerto Madryn, Chubut, Argentina. Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Standard satellite burned area and active fire products derived from the 500-m MODIS and SPOT are avail - able to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applica - tions. Consequently, we propose a novel algorithm for automated identification and mapping of burned areas at regional scale in semi-arid shrublands. The algorithm uses a set of the Normalized Burned Ratio Index products derived from MODIS time series; using a two-phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches. Region growing image segmentation algorithms are applied to the seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+ burned-area reference data was used for validation purposes. The correlation between the size of burnt areas detected by the global fire products and independently-derived Landsat reference data ranged from R2 = 0.01 - 0.28, while our algorithm performed showed a stronger correlation coefficient (R2 = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.

Automated mapping of burned areas in semi-arid ecosystems using modis time-series imagery


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