Correcting swath-dependent bias of MODIS FRP observations with quantile mapping

Inderpreet Kaur, Imke Hüser, Tianran Zhang, Berit Gehrke, Johannes W. Kaiser*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
135 Downloads (Pure)

Abstract

Active fire observations with satellite instruments exhibit a well-documented increase of the detection threshold with increasing pixel footprint size, i.e., distance from the sub-satellite point. This results in a viewing angle-dependent, negative bias in gridded representations of the observed Fire Radiative Power (FRP), which in turn is frequently being used for climate monitoring of biomass burning and for pyrogenic emission inventories. We present a method based on quantile mapping to alleviate this bias and apply it to the gridded-FRP from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instruments. The gridded-FRP observations are corrected with a correction function that depends on the satellite viewing angle and the magnitude of FRP in each grid cell. Assuming the fire observations at nadir to be the best representation of the truth, we derive a correction function by mapping cumulative distribution function (CDF) of off-nadir gridded-FRP to the CDF of near-nadir gridded-FRP. The method can be directly applied to correct the negative bias in gridded-FRP observations at a grid resolution of 1° or more. The performance of the correction methodology is confirmed through comparisons with co-located Visible Infrared Imaging Radiometer Suite (VIIRS) satellite observations: After bias correction, the gridded-FRP observations from both satellites agree better than before, particularly over savanna, tropical forests, and extra-tropical forests. Experiments with the Global Fire Assimilation System (GFAS) show that the impacts of the bias-corrected MODIS/Aqua gridded-FRP observations and VIIRS/Suomi-NPP gridded-FRP observations on regional FRP analyses are comparable, which confirms the potential for improving fire emission inventories and climate monitoring based on FRP.

Original languageEnglish
Article number1205
JournalREMOTE SENSING
Volume11
Issue number10
Early online date21 May 2019
DOIs
Publication statusPublished - May 2019

Keywords

  • Fire radiative power (FRP)
  • Moderate resolution imaging spectroradiometer (MODIS)
  • Quantile mapping bias correction
  • Viewing angle dependence

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