Synergy of Optical and Radar Remote Sensing for Environmental Monitoring

Dear Colleagues,

Environmental monitoring represents an important task for the scientific community in the framework of the global change that comes with an important degradation of socioecosystems. For a better understanding and monitoring of the environment, scientists, politics, end-users, local managers, etc. need, inter alia, information on different spatial and temporal scales that remote sensing can provide.

The remote sensing community has mainly used optical and, more recently, radar satellite images, as they offer a large range of spatial, spectral, radiometric, and temporal resolutions which are useful for environmental research, focused, for example, on deforestation, land use characterization, ice melting, water management, etc. The synergy of optical and radar remote sensing images for environmental monitoring appears very promising, as they provide different information of the surface (e.g., biophysics variables for optical data and polarimetric variables for SAR data). Nevertheless, and irrespective of the remote sensing community’s research, relatively few studies have combined optical and radar data for environmental purposes.

The reason for this is that scientists usually focus on a domain of remote sensing that best responds to their research issues. Furthermore, the theorical background of optical and radar remote sensing is quite unrelated and necessitates significant involvement. Additionally, evaluation of the synergy of optical and radar for environmental purposes still remains a methodological challenge with no established theoretical formalism. Methods developed for synergy evaluation as data fusion rules, machine and deep learning algorithms, multicriteria analysis, etc. mainly depend on the environmental problems studied.

In this context, this Special Issue presents several studies which evaluate the synergy of radar and optical data for environmental monitoring. It provides, through different applications, indicators and knowledge for a better understanding of the potentialities, limitations, and perspectives of this specific domain of remote sensing for environmental purposes.

Prof. Dr. Samuel Corgne
Guest Editor

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• Optical and radar data
• Environment
• Synergy
• Data fusion
• Machine Learning
• Spatial analysis