The precise mapping of vegetation covers in semi-arid areas is a complex task as this type of environment consists of sparse vegetation mainly composed of small shrubs. The launch of high resolution satellites, with additional spectral bands and the ability to alter the viewing angle, offers a useful technology to focus on this objective. In this context, atmospheric correction is a fundamental step in the pre-processing of such remote sensing imagery and, consequently, different algorithms have been developed for this purpose over the years. They are commonly categorized as imaged-based methods as well as in more advanced physical models based on the radiative transfer theory. Despite the relevance of this topic, a few comparative studies covering several methods have been carried out using high resolution data or which are specifically applied to vegetation covers. In this work, the performance of five representative atmospheric correction algorithms (DOS, QUAC, FLAASH, ATCOR and 6S) has been assessed, using high resolution Worldview-2 imagery and field spectroradiometer data collected simultaneously, with the goal of identifying the most appropriate techniques. The study also included a detailed analysis of the parameterization influence on the final results of the correction, the aerosol model and its optical thickness being important parameters to be properly adjusted. The effects of corrections were studied in vegetation and soil sites belonging to different protected semi-arid ecosystems (high mountain and coastal areas). In summary, the superior performance of model-based algorithms, 6S in particular, has been demonstrated, achieving reflectance estimations very close to the in-situ measurements (RMSE of between 2% and 3%). Finally, an example of the importance of the atmospheric correction in the vegetation estimation in these natural areas is presented, allowing the robust mapping of species and the analysis of multitemporal variations related to the human activity and climate change. Full article

Remote sensing of coastal areas requires multispectral satellite images with a high spatial resolution. In this sense, WorldView-2 is a very high resolution satellite, which provides an advanced multispectral sensor with eight narrow bands, allowing the proliferation of new environmental monitoring and mapping applications in shallow coastal ecosystems. These challenges need the accurate determination of the water radiance, which is not often valued compared to other sources such as atmosphere and specular water reflection (sun glint). In this context, the atmospheric correction and the glinting removal have demonstrated to be critical steps in the preprocessing chain of high resolution images. In this work, the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) is used to compensate the atmospheric effects and to compute part of the deglinting algorithm using the modeled direct normalized irradiance. This paper describes a novel automatic deglinting procedure, integrated in the Radiative Transfer Modeling (RTM) inversion of the shallow water environments, which allows computing the water Inherent Optical Properties (IOPs), bathymetry and seafloor albedo contributions. The proposed methodology has demonstrated a proper performance for environmental monitoring in shallow water areas. Full article

The eruptive phase of a submarine volcano located 2 km away from the southern coast of El Hierro Island started on October 2011. This extraordinary event provoked a dramatic perturbation of the water column. In order to understand and quantify the environmental impacts caused, a regular multidisciplinary monitoring was carried out using remote sensing sensors. In this context, we performed the systematic processing of every MODIS and MERIS and selected high resolution Worldview-2 imagery to provide information on the concentration of a number of biological, physical and chemical parameters. On the other hand, the eruption provided an exceptional source of tracer that allowed the study a variety of oceanographic structures. Specifically, the Canary Islands belong to a very active zone of long-lived eddies. Such structures are usually monitored using sea level anomaly fields. However these products have coarse spatial resolution and they are not suitable to perform submesoscale studies. Thanks to the volcanic tracer, detailed studies were undertaken with ocean colour imagery allowing, using the diffuse attenuation coefficient, to monitor the process of filamentation and axisymmetrization predicted by theoretical studies and numerical modelling. In our work, a novel 2-step segmentation methodology has been developed. The approach incorporates different segmentation algorithms and region growing techniques. In particular, the first step obtains an initial eddy segmentation using thresholding or clustering methods and, next, the fine detail is achieved by the iterative identification of the points to grow and the subsequent application of watershed or thresholding strategies. The methodology has demonstrated an excellent performance and robustness and it has proven to properly capture the eddy and its filaments. Full article

Spatial registration of multidate or multisensorial images is required for many applications in remote sensing. Automatic image registration, which has been extensively studied in other areas of image processing, is still a complex problem in the framework of remote sensing. In this work we explore an alternative strategy for a fully automatic and operational registration system capable of registering multitemporal and multisensorial remote sensing satellite images with high accuracy and avoiding the use of ground control points, exploiting the maximum reliable information in both images (coastlines not occluded by clouds), which have been coarsely geometrically corrected only using an orbital prediction model. The automatic feature-based approach is summarized as follows: i) Reference image coastline extraction; ii) Sensed image gradient energy map estimation and iii) Contour matching, mapping function estimation and transformation of the sensed images. Several experimental results for single sensor imagery (AVHRR/3) and multisensorial imagery (AVHRR/3-SeaWiFS-MODIS-ATSR) from different viewpoints and dates have verified the robustness and accuracy of the proposed automatic registration algorithm, demonstrating its capability of registering satellite images of coastal areas within one pixel. Full article