An active-fire based burned area mapping algorithm for the MODIS sensor

2009 ◽  
Vol 113 (2) ◽  
pp. 408-420 ◽  
Author(s):  
Louis Giglio ◽  
Tatiana Loboda ◽  
David P. Roy ◽  
Brad Quayle ◽  
Christopher O. Justice
Keyword(s):  
Burned Area ◽  
Mapping Algorithm ◽  
Active Fire ◽  
Burned Area Mapping

scholarly journals A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data

2020 ◽  
Vol 236 ◽  
pp. 111493 ◽  
Author(s):  
Joshua Lizundia-Loiola ◽  
Gonzalo Otón ◽  
Rubén Ramo ◽  
Emilio Chuvieco
Keyword(s):  
Burned Area ◽  
Modis Data ◽  
Active Fire ◽  
Burned Area Mapping ◽  
Clustering Approach ◽  
Spatio Temporal

scholarly journals A Burned Area Mapping Algorithm for Chinese FengYun-3 MERSI Satellite Data

2017 ◽  
Vol 9 (7) ◽  
pp. 736 ◽  
Author(s):  
Tianchan Shan ◽  
Changlin Wang ◽  
Fang Chen ◽  
Qinchun Wu ◽  
Bin Li ◽  
...  
Keyword(s):  
Satellite Data ◽  
Burned Area ◽  
Mapping Algorithm ◽  
Burned Area Mapping

scholarly journals The Collection 6 MODIS burned area mapping algorithm and product

2018 ◽  
Vol 217 ◽  
pp. 72-85 ◽  
Author(s):  
Louis Giglio ◽  
Luigi Boschetti ◽  
David P. Roy ◽  
Michael L. Humber ◽  
Christopher O. Justice
Keyword(s):  
Burned Area ◽  
Mapping Algorithm ◽  
Burned Area Mapping

scholarly journals MODIS Reflectance and Active Fire Data for Burn Mapping in Colombia

2011 ◽  
Vol 15 (10) ◽  
pp. 1-17 ◽  
Author(s):  
Silvia Merino-de-Miguel ◽  
Federico González-Alonso ◽  
Margarita Huesca ◽  
Dolors Armenteras ◽  
Carol Franco
Keyword(s):  
Terrestrial Ecosystem ◽  
Fire Detection ◽  
Cost Effective ◽  
Burned Area ◽  
Remotely Sensed Data ◽  
Burnt Area ◽  
Ecosystem Monitoring ◽  
Active Fire ◽  
Burned Area Mapping ◽  
Area Product

Abstract Satellite-based strategies for burned area mapping may rely on two types of remotely sensed data: postfire reflectance images and active fire detection. This study uses both methods in a synergistic way. In particular, burned area mapping is carried out using MCD43B4 [Moderate Resolution Imaging Spectrometer (MODIS); Terra + Aqua nadir bidirectional reflectance distribution function (BRDF); adjusted reflectance 16-day L3 global 1-km sinusoidal grid V005 (SIN)] postfire datasets and MODIS active fire products. The developed methodology was tested in Colombia, an area not covered by any known MODIS ground antenna, using data from 2004. The resulting burned area map was validated using a high-spatial-resolution Landsat-7 Enhanced Thematic Mapper Plus (ETM+) image and compared to two global burned area products: L3JRC (terrestrial ecosystem monitoring global burnt area product) and MCD45A1 (MODIS Terra + Aqua burned area monthly global 500-m SIN grid V005). The results showed that this method would be of great interest at regional to national scales because it proved to be quick, accurate, and cost effective.

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

2015 ◽  
Vol 163 ◽  
pp. 140-152 ◽  
Author(s):  
Itziar Alonso-Canas ◽  
Emilio Chuvieco
Keyword(s):  
Burned Area ◽  
Active Fire ◽  
Burned Area Mapping

scholarly journals Multi-Sensor, Active Fire-Supervised, One-Class Burned Area Mapping in the Brazilian Savanna

2021 ◽  
Vol 13 (19) ◽  
pp. 4005
Author(s):  
Allan A. Pereira ◽  
Renata Libonati ◽  
Julia A. Rodrigues ◽  
Joana Nogueira ◽  
Filippe L. M. Santos ◽  
...  
Keyword(s):  
Fire Regime ◽  
Training Sample ◽  
Burned Area ◽  
Mapping Accuracy ◽  
Mapping Algorithm ◽  
Burned Areas ◽  
Active Fire ◽  
Landsat Satellite ◽  
Omission Errors

Increasing efforts are being devoted to understanding fire patterns and changes highlighting the need for a consistent database about the location and extension of burned areas (BA). Satellite-derived BA mapping accuracy in the Brazilian savannas is limited by the underestimation of burn scars from small, fragmented fires and high cloudiness. Moreover, systematic mapping of BA is challenged by the need for human intervention in training sample acquisition, which precludes the development of automatic-generated products over large areas and long periods. Here, we developed a multi-sensor, active fire-supervised, one-class BA mapping algorithm to address several of these limitations. Our main objective is to generate a long-term, detailed BA atlas suitable to improve fire regime characterization and validation of coarse resolution products. We use composite images derived from the Landsat satellite to generate end-of-season maps of fire-affected areas for the entire Cerrado. Validation exercises and intercomparison with BA maps from a semi-automatic algorithm and visual photo interpretation were conducted for the year 2015. Our results improve the BA mapping by reducing omission errors, especially where there is high cloud frequency, few active fires are detected, and burned areas are small and fragmented. Finally, our approach represents at least a 45% increase in BA mapped in the Cerrado, in comparison to the annual extent detected by the current coarse global product from MODIS satellite (MCD64), and thus, it is capable of supporting improved regional emissions estimates.

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