Active and Passive Remote Sensing of Oceans and Environment (APRSOE or APRS)
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".
Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 13431
Special Issue Editor
Interests: computer science; engineering; observation; propagation; wave scattering; scattering in random media; monostatic and bistatic scattering; electromagnetic radar cross section; sea clutter; active and passive sensors (Radar, Lidar, Optics, GNSS); radar applications; data assimilation (n-D); sea surface and environment; extraction of parameters from the observed scene: imagery and target parameter estimation; direct and inverse problems; remote sensing of the ocean and the environment
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Special Issue Information
Dear Colleagues,
Observation and perception systems play an increasingly important role in the control, detection, localization, and monitoring of objects present in a natural environment (or only in the characterization and extraction of information from that environment). For example, the sea surface (or under the sea surface) is a complex environment and, in a coastal area, many practices can be distinguished. In this Special Issue, we provide an inventory of the progress made in exploiting active or passive sensors in data collection and exploitation in remote sensing of the oceans and the natural environment. This could include four important factors in decision-making, including the extraction of parameters from the observed area. The first factor concerns the utility of different sensors (depending on the different characteristics and limits of each, but also according to the intended application), as well as their use for the observation and perception of different scenes (depending on the geometry observation, multisource data, temporal data, multiscale data or multiphysical data). The second factor concerns the modeling, the fine characterization, and the specificities of the observed scene (sea, coastal zones, heterogeneous zones of the sea, and other zones of the environment). As for the third factor, it includes taking into account the physical aspects of the observed area. Finally, the fourth factor concerns the problem of inversion, including the innovative processing of available signals/images and/or those collected by sensors, and the extraction, from airborne or satellite images, of the relevant parameters (salinity and temperature of ocean surface water, wind speed and direction, currents, pollutants, moisture content, etc.) of the observed scene.
In this Special Issue, we provide an overview of technological and scientific advances in remote sensing by passive or active sensors (such as radar, lidar, optical, and GNSS sensors) in oceans, coastal areas, and the environment. In particular, it will be important to present new advances in the control of the dynamic nature of the oceans (in deep waters), but also in the relatively heterogeneous nature of the coasts, particularly in the context of climate change. In the estimation of parameters and characteristics of the observed surface, this Special Issue is also interested in different applications integrating physical and hydrodynamic phenomena. Authors are encouraged to submit contributions on the exploitation of satellite or airborne images or other signals of interest in the context of environmental characterization problems, including data fusion techniques support for decision, and artificial intelligence for different applications related to the environment. This could include issues such as automatic target recognition (ATR) and changes and/or modifications in an environment such as maritime environments.
Dr. Ali Khenchaf
Guest Editor
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Keywords
- Active and passive sensors
- GNSS, radar and lidar
- New sensors/platforms
- Heterogeneous environment (maritime, terrestrial, etc.)
- Monostatic, bistatic, multistatic configurations
- Electromagnetic/physical/hydrodynamic modeling
- EM scattering models/methods, clutter
- Direct and inverse problems
- Airborne, satellite and GNSS data
- Corrections and data preparation of radar/lidar/optical images
- Remote sensing of oceans and environment
- Data fusion and help for decision-making
- Development, exploitation and use of artificial intelligence (AI)
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