Remote Sensing of Water-Related Hazards. Группа авторов. Читать онлайн. Newlib. NEWLIB.NET

Автор: Группа авторов
Издательство: John Wiley & Sons Limited
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Жанр произведения: География
Год издания: 0
isbn: 9781119159148
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increase in the frequency and intensity of drought and floods around the world (AghaKouchak et al., 2015; Gu et al., 2020). Importantly, climate change is projected to increase the frequency and intensity of drought and floods in the mid‐ to late 21st century (IPCC, 2013; Wu et al., 2020), and to combine with other anthropogenic activities (AghaKouchak et al., 2021; Zhang et al., 2015; Y. Q. Zhang et al., 2016), leading to a rising risk to humans (Kam et al., 2021; Roudier et al., 2016). The growing impacts of water hazards have spurred research into improving monitoring and prediction of water hazards (Khaing et al., 2019; Makinano‐Santillan et al., 2019), understanding the underlying drivers (Gui et al., 2020), implementing various mitigation and adaptation strategies (Xu et al., 2020), and identifying other relevant factors such as climate change, population growth, exposure, and socioeconomic development.

      Historically, water‐related hazards have been monitored and studied using ground‐based point observations or spatially interpolated grids (AghaKouchak et al., 2014; He et al., 2018; Sheffield et al., 2012). Globally, many areas are not well instrumented to provide sufficient ground‐based observations of precipitation, near‐surface air temperature, relative humidity, soil moisture, and atmospheric water vapor among other hydrometeorological variables that are necessary for monitoring and investigating the water‐related hazards (AghaKouchak et al., 2015). In addition, ground‐based gauges are often destroyed by water‐related hazards such as flash floods, hurricanes, and landslides, making real‐time observation and consistent analysis of water‐related hazards challenging.

      Remote sensing refers to the process of detecting and monitoring an object at a distance from sensors, often onboard platforms such as aircrafts, satellites, unmanned aerial vehicles (UAVs), and towers. Satellite remote sensing of the Earth’s weather started in earnest with the Television and Infrared Observation Satellite (TIROS‐1) mission 1960 (NASA, 1987). TIROS‐1 became a very successful mission and led to a series of additional meteorological satellite missions such as the Nimbus series, the Environmental Science Services Administration Satellite Program (ESSA), the NOAA satellites, QuikScat, Landsat, and Tropical Rainfall Measuring Mission (TRMM). NASA launched the Earth Resources Technology Satellite, which was eventually renamed Landsat 1 in 1975, on 23 July 1972. The Landsat program is a joint NASA/USGS program that provides the longest continuous space‐based record of Earth’s land in existence. In 1997, NASA launched the Earth Observing System (EOS) program (https://eospso.nasa.gov) that is composed of a series of satellite missions and scientific instruments in Earth orbit, making it possible for long‐term global observations of the land surface, biosphere, atmosphere, and oceans. There are mainly two common types of Earth‐observing satellites, namely, geostationary satellites and sun‐synchronous polar‐orbiting satellites (Njoku, 2014). Geostationary satellites, at altitudes of approximately 36,000 kilometers, revolve at speeds that match the rotation of the Earth so they are stationary relative to the Earth’s surface (Njoku, 2014). This allows the satellites to observe and collect information continuously over specific areas, which are particularly valuable for monitoring weather and forecasting water‐related hazards (Njoku, 2014). In contrast, sun‐synchronous polar‐orbiting satellites are designed to follow a north‐south orbit, allowing them to cover most of the Earth’s surface over a certain period and collect data at the same local solar time, which are extremely valuable to observe the Earth’s surface to a larger extent and monitor changes over a long time period (Njoku, 2014).

      The emergence of remote sensing techniques has provided new avenues to study, monitor, and predict water‐related hazards (AghaKouchak et al., 2015; Andreas et al., 2020; Argaz et al., 2019; Boni et al., 2020; Elsadek et al., 2019; Fu et al., 2009). Equipped with passive or active sensors in the optical, thermal, and/or microwave bands, remote sensing platforms can capture a wealth of information that can be used to measure and infer water‐related hazards and their impacts, including precipitation (Prabhakara et al., 1998; Sorooshian et al., 2000), evapotranspiration (Mu et al., 2007; Zhang et al., 2010), soil moisture (Du et al., 2016; Entekhabi et al., 2010; Kerr et al., 2012; Lindell and Long, 2016; Parinussa et al., 2015; Reichle et al., 2016; Wigneron et al., 2017), vegetation health (Jones et al., 2011; Mitchard et al., 2011; Zhang et al., 2008), total water storage (Schmidt et al., 2006; Tapley et al., 2004), snow cover (Ehrler et al., 1997; Zhou et al., 2014), inundation (Islam et al., 2010; Kumar et al., 2008), and land deformation (Guo et al., 2010; Rosi et al., 2018). As a result, remote sensing of water‐related hazards has become the cutting edge of the natural hazard studies.

      Remote sensing is applicable to the detection, monitoring, and forecasting of water‐related hazards because most hydrological and atmospheric variables and geologic phenomena can be observed or inferred from space (Njoku, 2014). Revealing the location/frequency of previous occurrences and/or distinguishing the conditions under which extreme events are likely to occur can improve not only our understanding of water‐related hazards but also their detection and monitoring. A deep understanding of the underlying processes and key variables along monitoring capabilities is fundamental to prevent future natural hazards from becoming human disasters.

      Aerial photography provides the closest approximation of what the human eye sees (Njoku, 2014; Weng, 2017), and hence, it offers unique opportunities for rapid large scale assessment of hazards and their impacts. However, the available light and the weather (e.g., clouds and fog) often limit the use of aerial photography, especially during floods and severe storms. Airborne radars are active sensors that produce their own transmissions rather than reflected light from other sources, which can be used at any time and in nearly all weather conditions. Thermal infrared scanners use a semiconductor detector, which is sensitive to the thermal infrared part of the spectrum, producing information on the thermal pattern of Earth’s surface. Combined with other sensors and information such as near‐infrared remote sensing, passive and active microwave remote sensing, hyperspectral remote imaging, and multitemporal high‐resolution synthetic aperture radar (SAR), our capabilities to monitor and assess water hazards have drastically improved especially in the past three decades (Du et al., 2016; Entekhabi et al., 2010; Huffman et al., 2007; Kerr et al., 2012; Mu et al., 2007; Njoku et al., 2003; Reichle et al., 2016; Wigneron et al., 2017; Zhang et al., 2010).

      Remote sensing of hazards will be increasingly relied on to reduce our vulnerability and increase our resilience against extreme events. However, understanding the breadth of the available contributions in this