Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth’s volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.     

基于电磁卫星的闪电哨声波智能检测算法的研究进展

闪电哨声波作为探索空间物理环境的重要媒介,淹没在海量的电磁卫星数据中.近年来随着计算机视觉和深度学习等人工智能技术的发展,从电磁卫星的存档数据中自动检测闪电哨声波的算法取得了一定的效果.本文对近年来闪电哨声波智能检测算法的文献进行了整理和总结.首先,阐述闪电哨声波在电磁卫星数据中呈现的时频特征和类型;然后,介绍了闪电哨声波智能检测算法的流程并从闪电哨声波的特征提取、分类和定位三个方面对主要的智能检测算法进行归纳、总结和评述;其次,简述了闪电哨声波智能检测模型的评价指标;接着,在张衡一号（ZH-1）卫星的磁场数据上对三种典型的闪电哨声波智能检测算法进行复现,并对三种算法的优缺点进行了较深入的分析;最后,对基于电磁卫星的闪电哨声波智能检测的研究领域进行总结和展望.

     

Fuzzy logic algorithms in the analysis of electrotelluric data with reference to monitoring of volcanic activity

The expert processing of monitoring data of large networks on hazardous natural phenomena becomes increasingly more complicated due to an increase in the initial data flow. An approach alternative to the visual recognition of signals is proposed. A number of recognition algorithms and results of their application to the analysis of geoelectric potential monitoring data are discussed. Data of monitoring La Fournaise Volcano (Réunion Island) obtained in the vicinity of the intense volcanic eruption of 1988 are used. The obtained results show that these algorithms are capable of recognizing anomalous segments of records and discriminating between several types of anomalies presumably associated with the effects of various physical factors (heavy atmospheric precipitation, hydrothermal processes, and so on). The algorithms proposed in this work can be used both for the automation of expert work in operating monitoring systems and in investigations aimed at the identification of typical morphologic sequences in time series of data of various origins.     

Electromagnetic 3D tomography of the Elbrus volcanic center according to magnetotelluric and satellite data

A geoelectric 3D model of the potentially active Elbrus volcano and its vicinities has been constructed using magnetotelluric data, which takes the volume model of the tectonic fragmentation field developed based on deciphering satellite photographs into account. An original method of searching for the correlation and determination of the character of the interrelation between the ground-based and satellite data has been used in this construction. The geoelectric 3D model constructed includes two conducting objects located at different depths. One of the objects, with a resistivity of 25–40 Ω m, located at depths of 0–10 km, is most intense at a depth of 5 km, where the object is quasi-isometric in shape and has a radius of 10 km along the 40–60 Ω m contour lines. Another object with a resistivity of 10–40 Ω m is located at a depth of ～45 km, where its dimensions along the contour line for 40 Ω m are 35 and 15 km in latitude and longitude, respectively. The thickness of the conducting core is approximately 20 km. The upper and lower objects can be interpreted as a volcano magma chamber and a volcano parent chamber, respectively.     

Evaluation of riverbed magnetic susceptibility for mapping biogeochemical hot spots in groundwater-impacted rivers

Redox hot spots occurring as metal-rich anoxic groundwater discharges through oxic wetland and river sediments commonly result in the formation of iron (Fe) oxide precipitates. These redox-sensitive precipitates influence the release of nutrients and metals to surface water and can act as ‘contaminant sponges’ by absorbing toxic compounds. We explore the feasibility of a non-invasive, high-resolution magnetic susceptibility (MS) technique to efficiently map the spatial variations of magnetic Fe oxide precipitates in the shallow bed of three rivers impacted by anoxic groundwater discharge. Laboratory analyses on Mashpee River (MA, USA) sediments demonstrate the sensitivity of MS to sediment Fe concentrations. Field surveys in the Mashpee and Quashnet rivers (MA, USA) reveal several discrete high MS zones, which are associated with likely anoxic groundwater discharge as evaluated by riverbed temperature, vertical head gradient, and groundwater chemistry measurements. In the East River (CO, USA), widespread cobbles/rocks exhibit high background MS from geological ferrimagnetic minerals, thereby obscuring the relatively small enhancement of MS from groundwater induced Fe oxide precipitates. Our study suggests that, in settings with low geological sources of magnetic minerals such as lowland rivers and wetlands, MS may serve as a complementary tool to temperature methods for efficiently mapping Fe oxide accumulation zones due to anoxic groundwater discharges that may function as biogeochemical hot spots and water quality control points in gaining systems.     

Geodetic methods for detecting volcanic unrest: a theoretical approach

In this paper we study the application of different geodetic techniques to volcanic activity monitoring, using theoretical analysis. This methodology is very useful for obtaining an idea of the most appropriate (and efficient) monitoring method, mainly when there are no records of geodetic changes previous to volcanic activity. The analysis takes into account the crustal structure of the area, its geology, and its known volcanic activity to estimate the deformation and gravity changes that might precede eruptions. The deformation model used includes the existing gravity field and vertical changes in the crustal properties. Both factors can have a considerable effect on computed deformation and gravity changes. Topography should be considered when there is a steep slope (greater than 10°). The case study of Teide stratovolcano (Tenerife, Canary Islands), for which no deformation or gravity changes are available, is used as a test. To avoid considering topography, we worked at the lowest level of Las Cañadas and examined a smaller area than the whole caldera or island. Therefore, the results are only a first approach to the most adequate geodetic monitoring system. The methodology can also be applied to active areas where volcanic risk is not associated with a stratovolcano but instead with monogenetic scattered centers, especially when sites must be chosen in terms of detection efficiency or existing facilities. The Canary Islands provide a good example of this type of active volcanic areas, and we apply our model to the island of Lanzarote to evaluate the efficiency of the monitoring system installed at the existing geodynamic station. On this island topography is not important. The results of our study show clearly that the most appropriate geodetic volcano monitoring system is not the same for all different volcanic zones and types, and the particular properties of each volcano/zone must be taken into account when designing each system.     

Diapirism of depleted peridotite — a model for the origin of hot spots

A model is proposed for the origin of hot spots that depends on the existence of major-element heterogeneities in the mantle. Generation of basaltic crust at spreading centers produces a layer of residual peridotite ～20–25 km thick directly beneath the crust which is depleted in Fe/Mg, TiO₂, CaO, Al₂O₃, Na₂O and K₂O, and which has a slightly lower density than undepleted peridotite beneath it. Upon recycling of this depleted peridotite back into the deep mantle at subduction zones, it becomes gravitationally unstable, and tends to rise as diapirs through undepleted peridotite. For a density contrast of 0.05 g cm^?3, a diapir 60 km in diameter would rise at roughly 8 cm y^?1, and could transport enough heat to the base of the lithosphere to cause melting and volcanism at the surface. Hot spots are thus viewed as a passive consequence of mantle convection and fractionation at spreading centers rather than a plate-driving force.It is suggested that depleted diapirs exist with varying amounts of depletion, diameters, upward velocities and source volumes. Such variations could explain the occurrence of hot spots with widely varying lifetimes and rates of lava production. For highly depleted diapirs with very low Fe/Mg, the diapir would act as a heat source and the asthenosphere and lower lithosphere drifting across the diapir would serve as the source region of magmas erupted at the surface. For mildly depleted diapirs with Fe/Mg only slightly less than in normal undepleted mantle, the diapir could provide not only the source of heat but also most or all of the source material for the erupted magmas. The model is consistent with isotopic data that require two separate and ancient source regions for mid-ocean ridge and oceanic island basalts. The source for mid-ocean ridge basalts is considered to be material upwelling at spreading centers from the deep mantle. This material forms the oceanic lithosphere. Oceanic island basalts are considered to be derived from varying mixtures of sublithospheric and lower lithospheric material and the rising diapir itself.     

Towards improved snow water equivalent retrieval algorithms for satellite passive microwave data over the mountainous basins of western USA

Space‐borne passive microwave snow water equivalent (SWE) retrieval algorithms are attractive for continuous SWE monitoring over large mountainous areas. The performance of three SWE retrieval algorithms, which were considered relevant for operational purposes, was examined for each month over the Colorado River Basin. In addition, statistical post‐processing was tested as a means of improving the SWE estimates from each algorithm. The evaluation started with the so‐called Chang equation, which was a pioneer algorithm and is still used in practice. Successive attempts were then made to improve the algorithm's performance through the calibration of the equation's coefficient and through the inclusion of brightness temperature data from various frequency channels. The Chang equation consistently underestimated SWE with average bias between 30 mm in November and more than 300 mm in April and root mean square error (RMSE) exceeding 500 mm at many locations in April. The statistical post‐processing effectively removed the bias and reduced the RMSE by half for all the months. When the Chang equation's coefficients were calibrated at each site, biases were reduced by approximately 85%, and RMSE was reduced by 40%–50%. Finally, the multiple channel equations produced unbiased SWE estimates with RMSEs 50%–60% of those from the Chang equation. However, the statistical post‐processing did not reduce RMSE for both calibrated algorithms. The last algorithm produced the most reliable estimates for at‐site analysis, but its skill deteriorated when analyses were performed over larger areal extents; therefore, it is only recommended for SWE monitoring over smaller areas. For larger areas, the calibrated Chang equation is desirable because it only requires interpolations of a calibrated coefficient, which was spatially coherent. Copyright © 2011 John Wiley & Sons, Ltd.     

一次卫星热红外地震前兆现象的证伪

卫星热红外异常与地震关系的研究是目前地震领域的前沿课题,而从复杂的热红外信息中提取真正由地震活动引起的红外异常则是这项研究的关键和难点所在.本文以2004年3月24日在内蒙东部发生的5.9级地震为例,对热红外异常与地震的关系及异常提取中的相关问题进行了探讨.首先对震前3个月的NOAA16卫星影像进行了分析,结果发现震前三个月研究区出现了明显的热红外增温异常.异常影象特征表现为表面光滑、亮度均匀、边界清晰的高温雾状物;异常出现的空间位置不固定,面积大小不固定,异常无明显移动方向,亮温高出周围区域约3～10K.之后,又对研究区两年的NOAA卫星影象进行了连续分析,结果发现了同样的异常现象.对比分析两年内异常的时空演化过程进一步认识到,此异常具有明显的季节性,在冬春季节重复出现.2004年3月24日的5.9级地震刚好发生于异常的多发期末,从震前震后短期内的卫星资料看,易将其判为震兆红外异常.最后结合研究区的地理环境和气象等因素,对异常的成因进行了探讨,认为它可能是由大气逆温引起的红外现象,并非地震前兆异常.     

Water quality and spatio-temporal hot spots in an effluent-dominated urban river

In arid and semi-arid regions, many rivers experience extremely low flow conditions during seasonal dry periods. During these times, effluent from wastewater treatment plants can make up the majority of flow in the river. However, water quality in urban systems can also be strongly influenced by the natural or human-influenced flow regime and discharge from other anthropogenic sources such as industrial operations and runoff from impervious surfaces. In this study, we aimed to determine whether water quality was controlled primarily by wastewater discharge in an effluent-dominated river. Between May 2016–May 2019, we systematically measured water temperature, pH, dissolved oxygen, biochemical oxygen demand, and the concentrations of nitrate-N, ammonia-N, and orthophosphate in the South Platte River in the Denver metropolitan area, Colorado, USA. We found that, despite being an effluent-dominated river, wastewater treatment plant discharge was not the principal factor controlling water quality in many of the sampled areas. Non-point source pollution from impervious surfaces, delivered to the river through storm drains and minor tributary streams, also contributed to the high nutrient conditions in several locations. We also noted a strong seasonality in water quality, with higher concentrations of nutrients and higher biochemical oxygen demand in the winter months when wastewater effluent can make up more than 90% of the flow in the river. Thus, the interaction of discharge location and reduced seasonal flow produced spatio-temporal hot spots of diminished water quality. More stringent enforcement of water quality regulations may improve water quality in this system. However, a large portion of the pollution seems to be from non-point sources, which are very difficult to control.     

国家测震台站卫星传输状态自动检测

介绍了国家测震台站卫星传输链路和数据传输状态检测方法,使用VS2015开发环境的C#语言编写了自动检测程序并将其应用于台站,台站值班人员可以及时得到卫星传输不正常的报警信息,以便及时进行修复。     

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs¹³⁷ activity given the measurements taken in the region of Briansk following the Chernobyl accident.     

The respiratory health hazards of volcanic ash: a review for volcanic risk mitigation

Studies of the respiratory health effects of different types of volcanic ash have been undertaken only in the last 40 years, and mostly since the eruption of Mt. St. Helens in 1980. This review of all published clinical, epidemiological and toxicological studies, and other work known to the authors up to and including 2005, highlights the sparseness of studies on acute health effects after eruptions and the complexity of evaluating the long-term health risk (silicosis, non-specific pneumoconiosis and chronic obstructive pulmonary disease) in populations from prolonged exposure to ash due to persistent eruptive activity. The acute and chronic health effects of volcanic ash depend upon particle size (particularly the proportion of respirable-sized material), mineralogical composition (including the crystalline silica content) and the physico-chemical properties of the surfaces of the ash particles, all of which vary between volcanoes and even eruptions of the same volcano, but adequate information on these key characteristics is not reported for most eruptions. The incidence of acute respiratory symptoms (e.g. asthma, bronchitis) varies greatly after ashfalls, from very few, if any, reported cases to population outbreaks of asthma. The studies are inadequate for excluding increases in acute respiratory mortality after eruptions. Individuals with pre-existing lung disease, including asthma, can be at increased risk of their symptoms being exacerbated after falls of fine ash. A comprehensive risk assessment, including toxicological studies, to determine the long-term risk of silicosis from chronic exposure to volcanic ash, has been undertaken only in the eruptions of Mt. St. Helens (1980), USA, and Soufrière Hills, Montserrat (1995 onwards). In the Soufrière Hills eruption, a long-term silicosis hazard has been identified and sufficient exposure and toxicological information obtained to make a probabilistic risk assessment for the development of silicosis in outdoor workers and the general population. A more systematic approach to multi-disciplinary studies in future eruptions is recommended, including establishing an archive of ash samples and a website containing health advice for the public, together with scientific and medical study guidelines for volcanologists and health-care workers.     

Suitable triggering algorithms for detecting strong ground motions using MEMS accelerometers

With the recent development of digital Micro Electro Mechanical System(MEMS) sensors, the cost of monitoring and detecting seismic events in real time can be greatly reduced. Ability of MEMS accelerograph to record a seismic event depends upon the efficiency of triggering algorithm, apart from the sensor′s sensitivity. There are several classic triggering algorithms developed to detect seismic events, ranging from basic amplitude threshold to more sophisticated pattern recognition. Algorithms based on STA/LTA are reported to be computationally efficient for real time monitoring. In this paper, we analyzed several STA/LTA algorithms to check their efficiency and suitability using data obtained from the Quake Catcher Network(network of MEMS accelerometer stations). We found that most of the STA/LTA algorithms are suitable for use with MEMS accelerometer data to accurately detect seismic events. However, the efficiency of any particular algorithm is found to be dependent on the parameter set used(i.e., window width of STA, LTA and threshold level).     

A method for assessing lake morphometric characteristics with the use of satellite data

A method is proposed for assessing the main morphometric characteristics of lakes based on satellite data and relationships derived from the analysis of data from WORLDLAKE database.     

A new technique for evaluating mesospheric momentum balance utilizing radars and satellite data

A new method for evaluating momentum balance in the mesosphere using radar and satellite data is presented. This method is applied to radar wind data from two medium frequency installations (near Adelaide, Australia and Christchurch, New Zealand) and satellite temperature data from the Improved Stratospheric and Mesospheric Sounder (ISAMS). Because of limitations in data availability and vertical extent, the technique can only be applied to evaluate the momentum balance at 80 km above the radar sites for May 1992. The technique allows the calculation of the residual terms in the momentum balance which are usually attributed to the effects of breaking gravity waves. Although the results are inconclusive above Adelaide, this method produces values of zonal and meridional residual accelerations above Christchurch which are consistent with expectation. In both locations it is apparent that geostrophic balance is a poor approximation of reality. (This result is not dependent on a mismatch between the radar and satellite derived winds, but rather is inherent in the satellite data alone.) Despite significant caveats about data quality the technique appears robust and could be of use with data from future instruments.     

A review of the estimation of downward surface shortwave radiation based on satellite data: Methods,progress and problems

The estimation of downward surface shortwave radiation(DSSR) is important for the Earth's energy budget and climate change studies. This review was organised from the perspectives of satellite sensors, algorithms and future trends,retrospects and summaries of the satellite-based retrieval methods of DSSR that have been developed over the past 10 years. The shortwave radiation reaching the Earth's surface is affected by both atmospheric and land surface parameters. In recent years,studies have given detailed considerations to the factors which affect DSSR. It is important to improve the retrieval accuracy of cloud microphysical parameters and aerosols and to reduce the uncertainties caused by complex topographies and high-albedo surfaces(such as snow-covered areas) on DSSR estimation. This review classified DSSR retrieval methods into four categories:empirical, parameterisation, look-up table and machine-learning methods, and evaluated their advantages, disadvantages and accuracy. Further efforts are needed to improve the calculation accuracy of atmospheric parameters such as cloud, haze, water vapor and other land surface parameters such as albedo of complex terrain and bright surface, organically combine machine learning and other methods, use the new-generation geostationary satellite and polar orbit satellite data to produce highresolution DSSR products, and promote the application of radiation products in hydrological and climate models.     

卫星遥感解译湖泊蓝藻水华的几个关键问题探讨

蓝藻水华是全球性的水环境健康问题,对水华暴发过程信息的快速准确获取是制定有效防治措施的关键.卫星遥感因具有大范围、周期性观测的特点,被广泛地用于湖泊蓝藻水华的时空动态监测.本文指出在利用遥感对湖泊蓝藻水华进行研究时,需要注意的4个问题:(1)湖泊水体中泥沙等信号对藻华存在干扰;(2)大气程辐射及水陆边界影响藻华特征提取...     

卫星通信在地震烈度速报数据传输中的应用

在分析地震烈度速报数据传输特点后,提出将卫星通信引入烈度速报系统。通过对目前中国使用较多的北斗卫星、海事卫星、铱卫星系统和VSAT卫星系统进行对比,选取铱星短消息和海事卫星数据流这两种典型通讯方式,设计由通用数字强震仪与卫星通信系统结合地震速报通讯模块组成的实验系统,实现数字强震动记录信息通过卫星信道进行的数据传输,展现卫星通信在地震烈度速报数据传输中的应用前景。     

从卫星红外亮温与大地热流的关系看地震前的热红外异常

一些强地震前地表可产生热异常是人们比较一致的认识,但能否用卫星遥感技术观测到地下热异常则存在很大的分歧.本文试图通过分析热红外亮温与大地热流值的关系,探讨利用卫星遥感技术观测地震热异常的可能性及其存在的一些问题.研究结果表明:（1）在绝大多数情况下,亮温随大地热流值的升高而升高,升高的速率平均为0.057℃/mW·m-2.如果地震引起的大地热流异常为100 mW·m-2,则有可能产生卫星红外平均亮温约5.7℃的异常.（2）不同地区亮温随大地热流值变化速率不同,即使地震前出现了卫星热红外亮温异常,但不同地区表现也是不同的.（3）在一些地区一些季节,亮温与大地热流值关系不明显,可能是亮温数据受气象因素干扰所致.这说明地震前的热红外亮温异常是复杂的,甚至有时是难于观测到的.