Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data

By David P. Roy, Yufang Jin, Philip Lewis, C. Justice. 2005

371 citations recorded by the source corpus.

The remote sensing of Earth surface changes is an active research field aimed at the development of methods and data products needed by scientists, resource managers, and policymakers. Fire is a major cause of surface change and occurs in most vegetation zones across the world. The identification and delineation of fire-affected areas, also known as burned areas or fire scars, may be considered a change detection problem. Remote sensing algorithms developed to map fire-affected areas are difficult to implement reliably over large areas because of variations in both the surface state and those imposed by the sensing system. The availability of robustly calibrated, atmospherically corrected, cloud-screened, geolocated data provided by the latest generation of moderate resolution remote sensing systems allows for major advances in satellite mapping of fire-affected area. This paper describes an algorithm developed to map fire-affected areas at a global scale using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance time series data. The algorithm is developed from the recently published Bi-Directional Reflectance Model-Based Expectation change detection approach and maps at 500 m the location and approximate day of burning. Improvements made to the algorithm for systematic global implementation are presented and the algorithm performance is demonstrated for southern African, Australian, South American, and Boreal fire regimes. The algorithm does not use training data but rather applies a wavelength independent threshold and spectral constraints defined by the noise characteristics of the reflectance data and knowledge of the spectral behavior of burned vegetation and spectrally confusing changes that are not associated with burning. Temporal constraints are applied capitalizing on the spectral persistence of fire-affected areas. Differences between mapped fire-affected areas and cumulative MODIS active fire detections are illustrated and discussed for each fire regime. The results reveal a coherent spatio-temporal mapping of fire-affected area and indicate that the algorithm shows potential for global application.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/96c9f3637cc34c8b8701e5324e97cce18e47beb7

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Citations in the corpus

Remote sensing of fire severity: assessing the performance of the normalized burn ratio (2006, methodology): “4 shows histograms of MODIS 500-m NBR and NBR optimality values for observations sensed in predominantly boreal forest (Russian Federation), tropical forest (South America), and Savanna (Australia) study regions defined in [1].”
Global Rates of Habitat Loss and Implications for Amphibian Conservation (2007, background): “Although significant advances have been made in remote monitoring and change detection of fires and deforestation, and to a lesser extent of agriculture (Zhan et al., 2000, 2002; Roy et al., 2005), an operational, global-scale effort has not yet been implemented.”
Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art (2019, background): “s11069-016-2342-9 [170] D.”