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Detecting high-temperature anomalies from Sentinel-2 MSI images
ISPRS Journal of Photogrammetry and Remote Sensing ( IF 12.7 ) Pub Date : 2021-05-23 , DOI: 10.1016/j.isprsjprs.2021.05.008
Yongxue Liu , Weifeng Zhi , Bihua Xu , Wenxuan Xu , Wei Wu

High-temperature anomalies (HTAs) of the earth's surface, such as fires, volcanic activities, and industrial heat sources, have a profound impact on Earth's system. Sentinel-2 Multispectral Instrument (MSI) provides spatially-specific information for precisely measuring the location and extent of HTAs at a fine scale. However, detecting HTAs from MSI images remains challenging because the emitted radiance of an HTA in the short-wave infrared (SWIR) bands can be easily mixed with the reflected solar radiance background in the daytime; and an increasing number of atypical cases in MSI images need to be treated with the enhanced spatial resolution. A generic HTA detection approach that handles both anthropogenic and natural HTAs will broaden the scope of MSI applications. In this study, (i) we highlight two spectral characteristics of HTAs in the far-SWIR, near-SWIR, and NIR bands (i.e., (ρfar-SWIR - ρnear-SWIR)/ρNIR ≥ 0.45 and (ρfar-SWIRnear-SWIR) ≥ ρnear-SWIR - ρNIR) that can effectively enhance HTAs from background geo-features, based on the reflectance spectra in airborne imaging spectrometer data. (ii) We propose a tri-spectral thermal anomaly index (TAI) that jointly uses the two high-temperature-sensitive SWIR bands and the high-temperature-insensitive NIR band to enhance HTAs, based on the above characteristics and a comprehensive sampling of different types of HTAs from 1,974 MSI images. (iii) We develop a TAI-based approach for MSI images to detect HTAs in general. The proposed approach was applied to detect different types of HTAs, including different biomass burnings, active volcanoes, and industrial HTAs, over a wide range of land-cover scenarios. Validations and comparisons demonstrate the proposed approach is reliable and performs better than the existing state-of-the-art HTA detection approaches. Evaluations on two types of small industrial HTAs, including operating kilns and enclosed landfill gas flares, show that the HTA detection probability of the TAI-based approach from time-series MSI images is ~ 84.91% and 88.23%, respectively. Further investigations show that the TAI-based approach also has good transferability in detecting HTAs from multispectral images acquired by Landsat-family satellites.



中文翻译:

从Sentinel-2 MSI图像检测高温异常

地球表面的高温异常(HTA),例如火灾,火山活动和工业热源,对地球系统产生了深远的影响。Sentinel-2多光谱仪(MSI)提供了特定于空间的信息,可精确测量HTA的位置和范围。但是,从MSI图像检测HTA仍然具有挑战性,因为在短波红外(SWIR)波段中,HTA的发射辐射在白天容易与反射的太阳辐射背景混合。因此,需要使用增强的空间分辨率来处理MSI图像中越来越多的非典型案例。处理人为和自然HTA的通用HTA检测方法将扩大MSI应用范围。在这项研究中,()我们强调的HTA的两个光谱特性在远SWIR,近SWIR,和近红外波段(即,(ρ远SWIR - ρ近SWIR)/ρ NIR  ≥0.45和(ρ远SWIR近SWIR)≥ρ近SWIR - ρ NIR),可以有效地从背景地理特征增强HTA的,基于在空中成像光谱仪的数据的反射光谱。()我们基于上述特征和对不同类型的综合采样,提出了三光谱热异常指数(TAI),该指数结合使用两个对温度敏感的SWIR波段和对温度不敏感的NIR波段来增强HTA来自1,974个MSI图像的HTA。(iii)我们为MSI图像开发了一种基于TAI的方法来检测一般的HTA。所提出的方法被用于在广泛的土地覆盖场景中检测不同类型的HTA,包括不同的生物量燃烧,活火山和工业HTA。验证和比较表明,所提出的方法是可靠的,并且比现有的最新HTA检测方法具有更好的性能。对两种类型的小型工业HTA的评估(包括运行窑和封闭的垃圾填埋场火炬)显示,从时间序列MSI图像中,基于TAI的方法的HTA检测概率分别为〜84.91%和88.23%。进一步的研究表明,基于TAI的方法在从Landsat系列卫星获取的多光谱图像中检测HTA时也具有良好的可传递性。

更新日期:2021-05-24
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