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Processing of Near Real Time Land Surface Temperature and Its Application in Forecasting Forest Fire Danger Conditions

机译:近实时地表温度处理及其在森林火灾危险状况预测中的应用

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摘要

Near real time (NRT) remote sensing derived land surface temperature (Ts) data has an utmost importance in various applications of natural hazards and disasters. Space-based instrument MODIS (moderate resolution imaging spectroradiometer) acquired NRT data products of Ts are made available for the users by LANCE (Land, Atmosphere Near real-time Capability) for Earth Observing System (EOS) of NASA (National Aeronautics and Space Administration) free of cost. Such Ts products are swath data with 5 min temporal increments of satellite acquisition, and the average latency is 60-125 min to be available in public domain. The swath data of Ts requires a specialized tool, i.e., HEG (HDF-EOS to GeoTIFF conversion tool) to process and make the data useful for further analysis. However, the file naming convention of the available swath data files in LANCE is not appropriate to download for an area of interest (AOI) to be processed by HEG. In this study, we developed a method/algorithm to overcome such issues in identifying the appropriate swath data files for an AOI that would be able to further processes supported by the HEG. In this case, we used Terra MODIS acquired NRT swath data of Ts, and further applied it to an existing framework of forecasting forest fires (as a case study) for the performance evaluation of our processed Ts. We were successful in selecting appropriate swath data files of Ts for our study area that was further processed by HEG, and finally were able to generate fire danger map in the existing forecasting model. Our proposed method/algorithm could be applied on any swath data product available in LANCE for any location in the world.
机译:在自然灾害和灾害的各种应用中,近实时(NRT)遥感得出的地表温度(Ts)数据至关重要。 NASA(美国国家航空航天局)的地球观测系统(EOS)的LANCE(土地,大气近实时能力)已向用户提供了基于天文仪MODIS(中分辨率成像光谱仪)获取的Ts的NRT数据产品。 ) 免费的。此类Ts产品是卫星采集的时间增量为5分钟的条带数据,并且平均延迟为60-125分钟,可在公共领域使用。 Ts的条幅数据需要专门的工具,即HEG(HDF-EOS到GeoTIFF转换工具)来处理并使其对进一步分析有用。但是,LANCE中可用的条带数据文件的文件命名约定不适用于要由HEG处理的感兴趣区域(AOI)的下载。在这项研究中,我们开发了一种方法/算法来克服此类问题,即为AOI识别合适的条带数据文件,从而可以进一步支持HEG支持的过程。在这种情况下,我们使用Terra MODIS采集的Ts的NRT测绘数据,并将其进一步应用于现有的森林火灾预测框架(作为案例研究),以评估我们处理过的Ts的性能。我们成功地为我们的研究区域选择了合适的Ts数据文件,并由HEG进行了进一步处理,最终能够在现有的预测模型中生成火灾危险图。我们提议的方法/算法可以应用于LANCE在世界任何地方提供的任何条幅数据产品。

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