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The coastal zone offers among the world’s most productive and valuable ecosystems and is experiencing increasing pressure from anthropogenic impacts: human settlements, agriculture, aquaculture, trade, industrial activities, oil and gas exploitation and tourism. Earth observation has great capability to deliver valuable data at the local, regional and global scales and can support the assessment and monitoring of land‐ and water‐related applications in coastal zones. Compared to optical satellites, cloud‐cover does not limit the timeliness of data acquisition with spaceborne Synthetic Aperture Radar (SAR) sensors, which have all‐weather, day and night capabilities. Hence, active radar systems demonstrate great potential for continuous mapping and monitoring of coastal regions, particularly in cloud‐prone tropical and sub‐tropical climates. The canopy penetration capability with long radar wavelength enables L‐band SAR data to be used for coastal terrestrial environments and has been widely applied and investigated for the following geoscientific topics: mapping and monitoring of flooded vegetation and inundated areas; the retrieval of aboveground biomass; and the estimation of soil moisture. Human activities, global population growth, urban sprawl and climate change‐induced impacts are leading to increased pressure on coastal ecosystems causing land degradation, deforestation and land use change. This review presents a comprehensive overview of existing research articles that apply spaceborne L‐band SAR data for geoscientific analyses that are relevant for coastal land applications.

Due to the considerable resources investment, fine tuning the parameters of a spaceborne SAR system far in advance is very important. Most of them can be set by resorting to synthetic data, however models of complex natural phenomena are often not reliable enough to drive the choice. In this case, real data coming from airborne campaigns might be used as long as it is properly translated in a spaceborne setting. The problem of simulating spaceborne acquisitions was recently tackled and led to the definition of a new algorithm here exploited to analyze the effect of small changes in the system parameters.This work presents an analysis of the bond between biomass and tomography varying the orbits of the simulated spaceborne system. Different look angles and total baseline apertures are explored; moreover, random fluctuations of the trajectories are considered. These analyses provide recommendations about the nominal orbits and their accuracy.

International audience

A SAR system has to be calibrated for quantitative measurement. During this process all essential parameters of a SAR image are linked to their geophysical quantity. This includes the location of the image pixel, its backscattering characteristics (in amplitude and in phase) and polarimetric information. The Microwave and Radar Institute of the DLR has gained a lot of experience in these calibration procedures during the last decades and has developed special methods and dedicated reference targets for spaceborne SAR system calibration. In example of calibration results obtained for different spaceborne SAR systems the DLR SAR Calibration Center is presented.

International audience

Spaceborne SAR system concepts and mission design is often based on algorithms developed and the experience gathered from airborne SAR experiments and associated dedicated campaigns. However, airborne SAR systems have better performance parameters than their future space-borne counterparts as their design is not impacted by mass, power, and storage constraints. This paper describes a methodology to extrapolate spaceborne quality SAR image products from long wavelength airborne polarimetric SAR data which were acquired especially for the development and validation of bio/geo-retrieval algorithms in forested regions. For this purpose not only system (sensor) related parameters are altered, but also those relating to the propagation path (ionosphere) and to temporal decorrelation.

Global warning is now known to be the major environmental issue mankind will have to face in the next decade. Monitoring of vegetation and biomass is clearly an essential piece of information required at all levels ranging from the scientific studies to understand and forecast, to the political world responsible for drafting remediation policies and evaluating their impact. Microwave remote sensing with the low-frequency SAR technique can provide a useful characterization of forest (spatial coverage, species, density, height...) at a global scale, relying on the all-weather imaging capabilities of SAR linked with the significant penetration of the low-frequency EM wave in the canopy. In this paper, we will review the potential polarimetric indicators and evaluate their performance over several types of forest. We will particularly focus on the impact of the topography and the influence of the weather conditions.

The purpose of this paper is to present an end-to-end simulator for spaceborne high-resolution SAR systems that is capable of simulating realistic raw data and focused images of extended three-dimensional scenes. The simulator is based on precise mathematical modeling of an overall SAR system chain and generates information on the quality of the image data and its suitability to interpret target and background signatures. The principal components of the simulator are: - the generation of an extended scene, including the fully polarimetric scattering behavior of the three-dimensional surfaces, man made objects, and the typical SAR effects like overlay, speckle noise, shadowing;-an accurate SAR sensor simulation (antenna, transmit and receive path);-the generation of the raw data depending on the desired SAR mode (stripmap, spotlight mode);-the image processing and evaluation. The flexible and modular structure allows for adjustment and extension to fulfill different tasks. The most important modules reflecting the basic physical models will be described and simulation results will be demonstrated.