Improvements in high-temporal resolution active fire detection and FRP retrieval over the Americas using GOES-16 ABI with the geostationary Fire Thermal Anomaly (FTA) algorithm
Improvements in high-temporal resolution active fire detection and FRP retrieval over the Americas using GOES-16 ABI with the geostationary Fire Thermal Anomaly (FTA) algorithm
复制标题
使用 GOES-16 ABI 和对地静止火热异常 (FTA) 算法改进美洲的高时间分辨率主动火灾探测和 FRP 检索
DOI：
10.1016/j.srs.2021.100016
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发表时间：
2021
影响因子：
--
通讯作者：
Xu W
中科院分区：
文献类型：
--
作者：
Xu W
地球静止成像传感器提供了独特的高时间分辨率能力，可以表征快速变化的景观火灾动态。新的r系列地球同步运行环境卫星（GOES- r）是目前运行的最先进的地球同步气象卫星，每颗卫星都携带新的先进基线成像仪（ABI），大大改善了以前GOES成像仪的空间、时间和辐射特性。在这里，我们开发并评估了首个景观火辐射功率（FRP）观测系统，用于GOES-R系列（GOES-16）的首个观测系统，并将其输出与先行者GOES-13成像仪和更高空间分辨率、但成像频率低得多的中空间分辨率成像光谱仪（MODIS）几乎同时产生的输出进行了比较。在整个美洲，当检查2017年8月至9月的近同时数据时，最初为Meteosat的旋转增强型可见光和红外成像仪（SEVIRI）开发的地球同步火灾热异常（FTA）算法使GOES-16 ABI能够比GOES-13成像仪检测到更多（6%）的活火（AF）像素，这主要是由于前者传感器的像素面积较小。由于其更高的时间分辨率，ABI检测到更多的自动对焦像素，但这里我们只比较近同时图像的结果。即使是ABI也无法检测到大多数FRP小于~30 MW的火灾，而且由于这些火灾是最常见的火灾类型，与MODIS图像中心数据（±30°扫描角度）相比，ABI仍然显示出很高的遗漏误差（68%）。使用MODIS作为基准时，ABI自动对焦像素误差远低于遗漏误差，但在12%左右。这似乎比使用火灾探测和表征（FDC）算法得到的结果要有利得多，FDC是对野火自动生物质燃烧算法（WF_ABBA）算法的改编，该算法长期应用于GOES，当应用于ABI数据时，最近被评估为有88%的委托误差。当ABI和MODIS同时成功探测到火灾时，它们在检索到的FRP方面具有很强的一致性和低偏差。因此，总体而言，我们发现FTA方法从GOES-16 ABI传感器生成AF数据在整个美洲表现良好，并且与该系统的数据兼容，该系统与Meteosat、Meteosat over India Ocean和Himawari-8的数据相结合，成为现已成熟的全球地球同步主动火灾观测系统的一部分。GOES-16以GOES-East位置运行，以及GOES-17以GOES-West位置运行，提供的AF检测和FRP数据现在可以在全球范围内近乎实时地使用。
Geostationary imaging sensors offer unique high temporal resolution capabilities with which to characterise the fast-changing dynamics of landscape fires. The new R-Series of Geostationary Operational Environmental Satellite (GOES-R) are the most advanced geostationary weather satellites currently operating, and each carry the new Advanced Baseline Imager (ABI) which greatly improves on the spatial, temporal and radiometric characteristics of the previous GOES Imager. Here we develop and evaluate the first landscape fire radiative power (FRP) observation system for the first of the GOES-R series (GOES-16), comparing its outputs to those generated near simultaneously from the forerunner GOES-13 Imager and from the far higher spatial resolution, but far less frequently imaging, Moderate Spatial Resolution Imaging Spectroradiometer (MODIS). Across the Americas, when examining near-simultaneous data from August to September 2017, the geostationary Fire Thermal Anomaly (FTA) algorithm originally developed for use with Meteosat’s Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) enables GOES-16 ABI to detect substantially more (6%) active fire (AF) pixels than GOES-13 Imager, due mainly to the former sensors‘ smaller pixel area. ABI detects even greater numbers of AF pixels due to its higher temporal resolution, but here we are only comparing results from near-simultaneous imagery. The majority of fires having an FRP substantially less than ~30 MW remain undetected even by ABI, and since these are the most common fire type ABI still shows a high error of omission (68%) compared to MODIS centre of swath data (±30° scan angle). ABI AF pixel errors of commission are far lower than errors of omission however at ~12% when using MODIS as a benchmark. This appears far more favorable than results found when using the Fire Detection and Characterization (FDC) algorithm, an adaptation of the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) algorithm long-applied to GOES, which when applied to ABI data was recently assessed to have an 88% commission error. When ABI and MODIS both successfully detect a fire at the same time there is strong agreement and low bias in terms of their retrieved FRP. Overall therefore we find that the FTA approach to generating AF data from GOES-16 ABI sensor appears well performing across the Americas, and is compatible with the data from this system joining that from Meteosat, Meteosat over India Ocean and Himawari-8 to become part of the global geostationary active fire observation system now reaching maturity. The AF detection and FRP data provided from GOES-16 operating as GOES-East, and also now GOES-17 operating from the GOES-West position, are now available in near real-time for use worldwide.
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DOI：
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