| Literature DB >> 35902571 |
Qichao Yao1, Keyan Fang2, Tinghai Ou3, Feifei Zhou1, Maosheng He, Ben Zheng4, Jane Liu1,5, Hang Xing1, Valerie Trouet6.
Abstract
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Year: 2022 PMID: 35902571 PMCID: PMC9334368 DOI: 10.1038/s41467-022-32014-8
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 17.694
Fig. 1Fire occurrence comparisons between fire datasets.
The fire occurrence numbers are from the Wildfire Atlas of China (WFAC) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data, including MOD14A1 provided by Terra and MYD14A1 provided by Aqua[4]. a Total fire occurrences from MODIS, b crop fire occurrences from MODIS, c the ratio between total fire occurrences from MODIS and WFAC, and d the ratio between non-crop fire occurrences from MODIS and the WFAC. The fire occurrences were aggregated via combining the spatiotemporal adjacent fire points from MODIS Terra and Aqua from 2005 to 2018 into one fire event. Crop fire was picked out based on the land cover data of China in 2018[11]. The The 2 × 2 degree fire data is a sum of the fire occurrences.
Fig. 2Spatial patterns of the fire occurrences in China.
The a first and b second empirical orthogonal basis functions (EOF1 and EOF2) represent the spatial distribution of wildfire occurrence from the Wildfire Atlas of China (WFAC). These basis functions account for 54 and 19% of total variance.