Papers by Sandra P A O L A Viaña-Borja
Nearshore bathymetry is one of the main parameters used in coastal studies. However, regular and ... more Nearshore bathymetry is one of the main parameters used in coastal studies. However, regular and continuous bathymetries are scarce due to the difficulty of continuous data collection using traditional surveys. Remote sensing offers an attractive alternative to conventional collection methods for acquiring freely available, reliable, and frequent high-resolution data from space missions, such as the European Union's Copernicus programme Sentinel-2A/B satellites, which are increasingly demonstrating their potential to derive bathymetric information. Consequently, satellite-derived bathymetry (SDB) is being used more regularly because of its low cost and high efficiency. In this study, we apply a log-transformed band ratio SDB model in the Western Mediterranean Sea (Mallorca Island, Spain). This model has been widely used in the Caribbean and along the U.S. coast, among other sites, with outstanding results in heterogeneous environments. The SDB model consists of an automatic multi-scene approach applied over several images corrected by a robust atmospheric correction model (ACO-LITE), a switching model, and a procedure to remove pixels from optically deep waters. We retrieve depths up to 14 m with a mean bias of 0.02 m and a median absolute error of 0.71 m compared with multibeam echo-sounder (MBES) data. The outcomes of this study confirm the effectiveness of the multi-scene approach to automatically correct the imagery to derive accurate depths and characterize erosional and accretion patterns annually. Furthermore, it highlights the benefit of the switching model to take advantage of the spectral sensitivity of different multi-band ratio approaches. This study will provide the scientific community with substantial knowledge and improved SDB techniques to consolidate the understanding of nearshore processes in such a relevant ecosystem as the Mediterranean Sea.
Remote Sensing, 2019
Due to the importance of coastline detection in coastal studies, different methods have been deve... more Due to the importance of coastline detection in coastal studies, different methods have been developed in recent decades in accordance with the evolution of measuring techniques such as remote sensing. This work proposes an automatic methodology with new water indexes to detect the coastline from different multispectral Landsat images; the methodology is applied to three Spanish deltas in the Mediterranean Sea. The new water indexes use surface reflectance rather than top-of-atmosphere reflectance from blue and shortwave infrared (SWIR 2) Landsat bands. A total of 621 sets of images were analyzed from three different Landsat sensors with a moderate spatial resolution of 30 m. Our proposal, which was compared to the most commonly used water indexes, showed outstanding performance in automatic detection of the coastline in 96% of the data analyzed, which also reached the minimum value of bias of - 0 . 91 m and a standard deviation ranging from ±4.7 and ±7.29 m in some cases in contras...
Due to the importance of coastline detection in coastal studies, different methods have been deve... more Due to the importance of coastline detection in coastal studies, different methods have been developed in recent decades in accordance with the evolution of measuring techniques such as remote sensing. This work proposes an automatic methodology with new water indexes to detect the coastline from different multispectral Landsat images; the methodology is applied to three Spanish deltas in the Mediterranean Sea. The new water indexes use surface reflectance rather than top-of-atmosphere reflectance from blue and shortwave infrared (SWIR 2) Landsat bands. A total of 621 sets of images were analyzed from three different Landsat sensors with a moderate spatial resolution of 30 m. Our proposal, which was compared to the most commonly used water indexes, showed outstanding performance in automatic detection of the coastline in 96% of the data analyzed, which also reached the minimum value of bias of −0.91 m and a standard deviation ranging from ±4.7 and ±7.29 m in some cases in contrast to the existing values. Bicubic interpolation was evaluated for a simple sub-pixel analysis to assess its capability in improving the accuracy of coastline extraction. Our methodology represents a step forward in automatic coastline detection that can be applied to micro-tidal coastal sites with different land covers using many multi-sensor satellite images.
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Papers by Sandra P A O L A Viaña-Borja