ZHU, Ying; LIU, Xiangzhuo; LAI, Gengke; QUAN, Xingwen

doi:10.1109/IGARSS39084.2020.9323341

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ZHU, Ying
University of Electronic Science and Technology of China [Chengdu] [UESTC]

LIU, Xiangzhuo
Interactions Sol Plante Atmosphère [UMR ISPA]

LAI, Gengke
University of Electronic Science and Technology of China [Chengdu] [UESTC]

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IEE, IEE, IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020-09-26, Waikoloa. 2021-02-17p. 6782-6785

IEEE

Résumé en anglais

Near-real-time monitoring live fuel moisture content (LFMC) from remote sensing is paramount to wildfire early management at a large scale since LFMC is a critical variable in affecting fire ignition and fire spread rate. The geostationary satellite Himawari-8 observes the land surface every 10 minutes, making near-real-time LFMC retrieval achievable. To this end, the potential of Himawari-8 data for LFMC retrieval using the radiative transfer model was explored in this study. The performance of retrieved LFMC was validated using 16 LFMC samplings located in Australia involving two land cover types: croplands and tree cover lands. Additionally, the MODIS data was also applied and compared for the LFMC retrieval. The results showed that Himawati-8 data performed poor accuracy level with R-2 and RMSE of 0.26 and 42.16%, respectively. Whereas better accuracy level was found for MODIS data, R-2 and RMSE were 0.67 and 29.17%, respectively. This result indicated that the LFMC estimated from Himawari-8 is challenged. Detailed fieldwork and methodology improvements adopted for this data are needed for improving the LFMC estimate in the future.< Réduire

Mots clés en anglais

Live Fuel Moisture Content (LFMC)

Himawari-8

PROSAIL RTM

PROGEOSAIL RTM

MCD43A4.006

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Evaluation of Himawari-8 for live fuel moisture content retrieval

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