Wildfire Detection Notifications for Impact-based Decision Support Services in Oklahoma Using Geostationary Super Rapid Scan Satellite Imagery
Wildfire Detection Notifications for Impact-based Decision Support Services in Oklahoma Using Geostationary Super Rapid Scan Satellite Imagery
复制标题
使用对地静止超快速扫描卫星图像为俄克拉荷马州基于影响的决策支持服务提供野火检测通知
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发表时间：
2016
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通讯作者：
S. Bachmeier
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作者：
Todd Lindley;A. Anderson;V. Mahale;Thomas Curl;W. Line;S. Lindstrom;S. Bachmeier
2016年2月18日，野火烧毁了524.80平方公里(129682交流电)，损坏或摧毁了俄克拉荷马州的656座建筑。在这场高影响的火灾事件中，俄克拉荷马州诺曼市国家气象局预报办公室的气象学家利用GOES-R(SRSOR)的实验性1分钟地球静止业务环境卫星-14(GOES-14)成像器超快速扫描操作，与高级天气交互处理系统(AWIPS)内基于短信的通知工具相结合，向官员发出关于遥感野火热点的警报。这些通知使俄克拉荷马州林业服务局和俄克拉荷马州紧急管理部能够迅速将当地消防资源部署到新检测到的野火起火地点-在某些情况下，是在接到紧急911电话之前。本文将介绍为在实时操作期间在AWIPS中使用而开发的Python应用程序，并将简要说明火灾爆发的SRSOR采样，特别是俄克拉荷马州西北部的布法罗火灾。SRSOR的这一使用证明了GOES-R时代能力的研究到运营在未来基于影响的决策支持服务中的适用性。
On 18 February 2016, wildfires burned 524.80 km 2 (129 682 ac) and damaged or destroyed 656 structures across Oklahoma. During this high-impact fire episode, meteorologists at the Norman, Oklahoma, National Weather Service Forecast Office leveraged experimental 1-min Geostationary Operational Environment Satellite-14 (GOES-14) imager super rapid scan operations for GOES-R (SRSOR) in concert with a text messaging-based notification tool within the Advanced Weather Interactive Processing System (AWIPS) to alert officials of remotely sensed wildfire hot spots. These notifications allowed Oklahoma Forestry Services and Oklahoma Department of Emergency Management to rapidly deploy local firefighting resources to the site of newly detected wildfire ignitions—in some instances before emergency 911 calls were received. This article will describe the Python application developed for use in AWIPS during real-time operations and will briefly illustrate SRSOR sampling of the fire outbreak, particularly the Buffalo Fire in northwestern Oklahoma. This use of SRSOR demonstrates the applicability of research-to-operations for GOES-R era capabilities in future impact-based decision support services.