Based on experimental results, this chapter describes applications of SAR polarimetry to extract relevant information on agriculture and wetland scenarios by exploiting differences in the polarimetric signature of different scatterers, crop types and their development stage depending on their physical properties. Concerning agriculture, crop type mapping, soil moisture estimation and phenology estimation are reviewed, as they are ones with a clear benefit of full polarimetry over dual or single polarimetry. For crop type mapping, supervised or partially unsupervised classification schemes are used. Phenology estimation is treated as a classification problem as well, by regarding the different stages as different classes. Soil moisture estimation makes intensive use of scattering models, in order to separate soil and vegetation scattering and to invert for soil moisture from the isolated ground component. Then, applications of SAR polarimetry to wetland monitoring are considered that include the delineation of their extent and their characterisation by means of polarimetric decompositions. In the last section of the chapter, the use of a SAR polarimetric decomposition is shown for the assessment of the damages consequential to earthquakes and tsunamis.

The segmentation of open water areas plays an important role in the wetland monitoring. Moreover, a veil of mist often covers this kind of land and the use of optical sensors is quite limited. In this paper, the open water segmentation is applied over Radarsat-2 images acquired in the north west of France. Results obtained for different incidence angle are presented and validated using meteorological data.

Remotely sensed data are widely used to identify, delineate, and characterize wetlands. Optical data provide interesting information to inventory vegetation and agricultural practices in wetlands but are limited to cloud-free periods. For this reason it is not possible to precisely delineate the extent of saturated areas as well as water cycles and water levels in these areas with passive remote sensing techniques. The objective of this article is to evaluate fully polarimetric RADARSAT-2 time-series datasets to identify and locate the seasonal dynamics of saturated areas in wetlands. To that end, the development and validation of a supervised PolSAR segmentation including multitemporal analysis of wetland evolution and polarimetric decomposition method is presented. The proposed methodology is based on the segmentation of a polarimetric descriptor, the Shannon Entropy, which has been shown to be a very sensitive parameter to the temporal variability of flooded areas. The results were validated using ground truth measurements in the field and a LiDAR image. They showed that it is possible to produce detailed water feature maps useful for delineating and monitoring the seasonal dynamics of saturated areas extent in wetlands. These products provide useful information to identify and delineate wetlands to support conservation and management in these ecosystems across large areas.

The project entitled Evaluation of RADARSAT-2 quad-pol data for functional assessment of wetlands (Id6842), developed in the framework of the CSA-ESA SOAR-EU (Science and operational applications research for Europe) aims to contribute to the application development in demonstrating the exploitation of fully polarimetric time-series datasets for the functional assessment of wetlands. The objective of this paper is to address the issue of evaluating fully polarimetric RADARSAT-2 time-series datasets to determine the water cycle dynamics, in order to delineate precisely potential, effective and efficient wetlands.

Remotely sensed data are widely used to identify, delineate and characterize wetlands. Optical data provide interesting information on land-use and land cover but are limited to cloud-free periods and to a description of the top layer of the vegetation strata because penetration depth is very small. For these reasons, it is not possible to precisely inventory wetland vegetation and agricultural practices, as well as water cycles and water levels in these areas with passive remote sensing techniques. The objective of this article is to evaluate fully polarimetric RADARSAT-2 time-series datasets to determine the water cycle dynamics, in order to delineate precisely potential, effective and efficient wetlands. To that end, the development and validation of a supervised PolSAR segmentation including multi-temporal analysis of wetland evolution, and the investigation of polarimetric decomposition methods for quantitative physical parameter inversion algorithms are presented. The proposed methodology is based on the segmentation of a polarimetric descriptor, the Shannon Entropy, which has been shown to be a very sensitive parameter to the temporal variability of flooded areas. The results have been validated using soil moisture measurements in the field and a LiDAR image. They show that it is possible to produce detailed water feature maps useful for delineating water tables as well as water-saturated areas, and for monitoring water area dynamics. These products provide useful information to identify and delineate wetlands in order to support conservation and management in these ecosystems across large areas.

The project entitled Evaluation of RADARSAT-2 quad-pol data for functional assessment of wetlands (Id6842), developed in the framework of the CSA-ESA SOAR-EU (Science and operational applications research for Europe) by a consortium comprising I.E.T.R at the University of Rennes 1 and COSTEL-LETG at the University of Haute-Bretagne, aims to contribute to the application development in demonstrating the exploitation of fully polarimetric time-series datasets for the functional assessment of wetlands. The objective of this article is to address the issue of evaluating fully polarimetric RADARSAT-2 time-series datasets to determine the water cycle dynamics, in order to delineate precisely potential, effective and efficient wetlands. To that end, the development and validation of a general PolSAR segmentation including multi-temporal analysis of wetland evolution, and the investigation of polarimetric decomposition methods for quantitative physical parameter inversion algorithms are presented.

The objective of this paper is to make a review of the current status of the project entitled Evaluation of RADARSAT-2 quad-pol data for functional assessment of wetlands (Id6842), developed in the frame of the CSA-ESA SOAR-EU (Science and operational applications research for Europe) program by a consortium comprising I.E.T.R at the University of Rennes 1 and COSTEL-LETG at the University of Haute-Bretagne. The main objective of this project concerns in evaluating fully polarimetric RADARSAT-2 time-series datasets to delineate precisely effective and potential wetlands, map detailed vegetation distribution, identify agricultural practices and determine water cycle and waterlevels.

Time series of satellite data, generated by the AVHRR (1981–1999), CZCS (1979–1985) and SeaWiFS (1998–2002), have been used to assess trends and interactions of physical and bio-geo-chemical features in the Adriatic Sea. The images were processed to estimate Sea Surface Temperature (SST) and Chlorophyll-like Pigment Concentration (CPC). Long-term composites and climatologies were derived, using fixed geographical grids and projections. The AVHRR data show an apparent warming trend, when plotting the sequence of seasonal cycles (monthly mean SST, averaged over the whole basin) against time, due to a steady rise of summer values. Considering 3 regions (north, central and south), split into east and west sections, the northern Adriatic shows high SST fluctuations (possibly associated with the cycle of winter cooling and summer warming, typical of the relatively shallow sub-basin), while the southern Adriatic exhibits a lower variability (possibly influenced by the periodic water incoming from, and outflowing to the Ionian Sea). During summer, an east–west gradient prevails, while during winter only a general north–south gradient can be found. The SeaWiFS-derived CPC values, distributions and trends appear to be consistent with the historical CZCS record. Persistent differences in the quantitative assessment of CPC for coastal waters is due to the use of improved algorithms, less influenced by the presence of dissolved organics and suspended sediments in the water column, for the processing of SeaWiFS data. Apparent incongruities of the space and time patterns in the SeaWiFS record with respect to the reference climatology, obtained by CZCS more than a decade before, occur chiefly when considering the spring bloom in the southern Adriatic and the summer development of the north Adriatic front. The comparison of the long-term times series of satellite data shows that there is a high correlation between patterns in the thermal field and in the colour field. This suggests that different surface waters, identified by the SST index, are also traced by different ecological features, identified by the CPC index. Both indices also show a high correlation with the classical cyclonic circulation scheme of the Adriatic Sea, proposing once again an intimate relationship between the water dynamics and its bio-geo-chemistry.