Abstract
Recent advances in satellite technologies, statistical and mathematical models, and computational resources have paved the way for operational use of satellite data in monitoring and forecasting natural hazards. We present a review of the use of satellite data for Earth observation in the context of geohazards preventive monitoring and disaster evaluation and assessment. We describe the techniques exploited to extract ground displacement information from satellite radar sensor images and the applicability of such data to the study of natural hazards such as landslides, earthquakes, volcanic activity, and ground subsidence. In this context, statistical techniques, ranging from time series analysis to spatial statistics, as well as continuum or discrete physics-based models, adopting deterministic or stochastic approaches, are irreplaceable tools for modeling and simulating natural hazards scenarios from a mathematical perspective. In addition to this, the huge amount of data collected nowadays and the complexity of the models and methods needed for an effective analysis set new computational challenges. The synergy among statistical methods, mathematical models, and optimized software, enriched with the assimilation of satellite data, is essential for building predictive and timely monitoring models for risk analysis.
Highlights
Examples include the study of the distribution of aerosols in the atmosphere using data collected by the Multiangle Imaging Spectroradiometer (MISR) and Moderateresolution Imaging Spectrometer (MODIS) (Nguyen et al 2012), the estimation of CO2 mole fraction in the atmosphere using data collected by the Greenhouse Gases Observing Satellite (GOSAT) and Atmospheric Infrared Sounder (AIRS) (Nguyen et al 2014), the prediction of the total column ozone using data collected by the Total Ozone Mapping Spectrometer (TOMS) (Huang et al 2002), the estimation of the terrestrial latent heat flux using data collected by MODIS and Landsat (Xu et al 2018), and analysis of the sea surface temperature from MODIS and the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) (Ma and Kang 2018)
Some examples of application in this context are provided by Fielding et al (1998), who study ground subsidence in oil fields due to the extraction of large volumes of fluid from shallow depths, Carnec and Fabriol (1999), who study land subsidence in a geothermal reservoir, Lu and Danskin (2001), Motagh et al (2008), and Lubis et al (2011), who study ground deformation produced by water reservoir dynamics and exploitation, and Perski et al (2009), who analyze ground deformation induced by mining activity in a salt mine
Given the wide variety of numerical methods available for lava flow prediction, assessing their validity is of the utmost importance: this issue has been addressed by proposing different benchmark cases, either analytical (as in Dietterich et al (2017)) or experimentally driven, that can be used to discriminate the range of applications and the scenarios covered by each model
Summary
Satellite Earth observation is increasingly used by the research community, civil protection authorities, international organizations, and industry to monitor and forecast natural hazards in order to develop disaster risk management strategies, see for example Van Westen (2000), Joyce et al (2009), Tomás and Li (2017) and references therein. Advanced statistical methodologies, physics-based models, and numerical and computational techniques seldom have been combined to overcome the issues arising from the complexity and the huge dimensionality of Earth observation data, and the need for fast and accurate response Such a statement opens new directions of research and challenges that should be tackled soon by the scientific community: in monitoring and forecasting natural hazards it is of utmost importance to support civil protection authorities in decision planning processes by means of reliable, physically sound, and prompt responses that can stem from mathematical analyses integrated with Earth observation satellite data evidence. The paper is organized as follows: Sect. 2 provides an overview on Earth observation satellite data, with a focus on interferometric processing of SAR data; Sect. 3 analyzes the application of the aforementioned data in the field of natural hazards monitoring and forecasting, with a focus on landslides, earthquakes, volcanic activity, and ground subsidence; Sect. 4 focuses on statistical models and methods currently used in this field of research; Sect. 5 describes physics-based approaches used to model natural hazards with a special focus on the integration of satellite data into such models; Sect. 6 draws the conclusions of the paper
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