The interfaces between land and sea, estuaries, deltas, and coastal areas are vulnerable to rapid changes at local and global scales. These coastal areas are experiencing dramatic changes in land use, land cover, water, and sediment deposition, wetland hydrological ecological environment, and ground stability as a result of urban, industrial, and agricultural development. Human activities are exacerbating the effects of climate change and sea level rise on a global and regional scale, causing frequent danger or damage to coastal regions worldwide. We urgently need better remote sensing measurements and modeling to understand what and to what extent is causing coastal environmental change.
Coastal ecosystems are regions of remarkable primary and secondary productivity, biodiversity, and accessibility. Therefore, accurate, economical, frequent, and weather-compliant methods are needed to characterize and monitor these complex ecosystems. Coastal change is not limited to erosion in the form of coastal retreat and subsidence, but also includes the transformation of vegetation, changes in management and protection, as well as the effectiveness of coastal resilience in the face of weather–climate imbalances for short or longer periods. To complement the contributions of in situ measurements and facilitate systematic observations, various strategies have recently emerged to exploit innovative techniques from remote sensing.
Goal
Coastal environmental changes can be divided into temporal and spatial changes, horizontal and vertical changes, geometric position and biophysical chemical changes, morphological and dynamic changes, vegetation and physical geographical changes, global and local changes, etc. Coastal disasters are physical phenomena that expose coastal areas to the risk of property damage, life loss, and environmental degradation. An induced coastal hazard occurs rapidly and may last from minutes to days, including large cyclones with strong winds and storm surges or tsunamis caused by undersea earthquakes or landslides. The other is a hazard that occurs slowly, developing gradually over a longer period of time, such as erosion and gradual inundation.
The purpose of this research topic is to use high-frequency time series of remote sensing observations to detect, extract and monitor the morphological and dynamic indicators of the sea-land interfaces, such as land cover, water and sediment, coastline, subsidence, temperature, moisture, and vegetation, biomass and carbon, etc. The coastal expert community is committed to answering many questions about these complex interfaces, which lie at the junction of land, ocean, and meteorological mechanisms and other natural constraints, coupled with those caused by human activities. The intersection of disciplines, observations, and data sets is in the focus with the aim of translating into information about spatio-temporal characteristics, such as the expression of sediment imbalances and ecosystem adjustments, drivers of human activities, levels of exposure, and adaptation to hazards.
Scope
Remote sensing methods and observations from in situ, airborne, and spaceborne platforms provide large-scale, high-frequency data collection of coastal environments. This research topic will facilitate an informed debate among scientists and stakeholders on the coastal environment affected by global climate change and coastal hazards.
This research topic aims to address the challenges associated with assessing, quantifying, and monitoring coastal land-sea surface processes, interrelationships among vegetation, water, and sediment, and the impacts of rising sea levels. Various articles will illustrate remote sensing time series methods for detecting, monitoring, and quantifying any regular or unusual changes in coastal margins and tidal flats, as well as hotspot cases of spatio-temporal, morphological, physical, geographical, and ecological changes under the strong anthropogenic and climate pressures.
Multi-disciplinary spatio-temporal coupling and multi-source geospatial knowledge mining tools such as big data, artificial intelligence, machine learning, and deep learning are all welcome.
Keywords:
coastal environmental remote sensing, radar remote sensing, InSAR and PolSAR, machine learning and deep learning, coastal wetlands and tidal flats, coastal floods and sea-level rise, coastal object identification and classification, coastal geomorphology
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The interfaces between land and sea, estuaries, deltas, and coastal areas are vulnerable to rapid changes at local and global scales. These coastal areas are experiencing dramatic changes in land use, land cover, water, and sediment deposition, wetland hydrological ecological environment, and ground stability as a result of urban, industrial, and agricultural development. Human activities are exacerbating the effects of climate change and sea level rise on a global and regional scale, causing frequent danger or damage to coastal regions worldwide. We urgently need better remote sensing measurements and modeling to understand what and to what extent is causing coastal environmental change.
Coastal ecosystems are regions of remarkable primary and secondary productivity, biodiversity, and accessibility. Therefore, accurate, economical, frequent, and weather-compliant methods are needed to characterize and monitor these complex ecosystems. Coastal change is not limited to erosion in the form of coastal retreat and subsidence, but also includes the transformation of vegetation, changes in management and protection, as well as the effectiveness of coastal resilience in the face of weather–climate imbalances for short or longer periods. To complement the contributions of in situ measurements and facilitate systematic observations, various strategies have recently emerged to exploit innovative techniques from remote sensing.
Goal
Coastal environmental changes can be divided into temporal and spatial changes, horizontal and vertical changes, geometric position and biophysical chemical changes, morphological and dynamic changes, vegetation and physical geographical changes, global and local changes, etc. Coastal disasters are physical phenomena that expose coastal areas to the risk of property damage, life loss, and environmental degradation. An induced coastal hazard occurs rapidly and may last from minutes to days, including large cyclones with strong winds and storm surges or tsunamis caused by undersea earthquakes or landslides. The other is a hazard that occurs slowly, developing gradually over a longer period of time, such as erosion and gradual inundation.
The purpose of this research topic is to use high-frequency time series of remote sensing observations to detect, extract and monitor the morphological and dynamic indicators of the sea-land interfaces, such as land cover, water and sediment, coastline, subsidence, temperature, moisture, and vegetation, biomass and carbon, etc. The coastal expert community is committed to answering many questions about these complex interfaces, which lie at the junction of land, ocean, and meteorological mechanisms and other natural constraints, coupled with those caused by human activities. The intersection of disciplines, observations, and data sets is in the focus with the aim of translating into information about spatio-temporal characteristics, such as the expression of sediment imbalances and ecosystem adjustments, drivers of human activities, levels of exposure, and adaptation to hazards.
Scope
Remote sensing methods and observations from in situ, airborne, and spaceborne platforms provide large-scale, high-frequency data collection of coastal environments. This research topic will facilitate an informed debate among scientists and stakeholders on the coastal environment affected by global climate change and coastal hazards.
This research topic aims to address the challenges associated with assessing, quantifying, and monitoring coastal land-sea surface processes, interrelationships among vegetation, water, and sediment, and the impacts of rising sea levels. Various articles will illustrate remote sensing time series methods for detecting, monitoring, and quantifying any regular or unusual changes in coastal margins and tidal flats, as well as hotspot cases of spatio-temporal, morphological, physical, geographical, and ecological changes under the strong anthropogenic and climate pressures.
Multi-disciplinary spatio-temporal coupling and multi-source geospatial knowledge mining tools such as big data, artificial intelligence, machine learning, and deep learning are all welcome.
Keywords:
coastal environmental remote sensing, radar remote sensing, InSAR and PolSAR, machine learning and deep learning, coastal wetlands and tidal flats, coastal floods and sea-level rise, coastal object identification and classification, coastal geomorphology
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.