Topographic effects on the mesoscale ocean circulation near Canarian archipelago examined by means of satellite images and laboratory simulations

Abstract-The ocean covers over 70% of the surface of our planet and plays a key role in the global climate. Most ocean circulation is mesoscale (scales of 50-500 km and 10-100 days), and the energy in mesoscale circulation is at least one order of magnitude greater than general circulation; therefore, the study of mesoscale oceanic structures (MOS) is crucial to ocean dynamics, making it especially useful for analyzing global changes. The detection of MOS, such as upwellings or eddies, from satellites images is significant for marine environmental studies and coastal resource management. In this paper, we present an objectbased image analysis (OBIA) system which segments and classifies regions contained in sea-viewing field-of-view sensor (SeaWiFS) and Moderate Resolution Imaging Spectro-radiometer (MODIS)-Aqua sensor satellite images into MOS. After color clustering and hierarchical data format (HDF) file processing, the OBIA system segments images and extracts image descriptors, producing primary regions. Then, it merges regions, recalculating image descriptors for MOS identification and definition. First, regions are labeled by a human-expert, who identifies MOS: upwellings, eddies, cool, and warm eddies. Labeled regions are then classified by learning algorithms (i.e., decision tree, Bayesian network, artificial neural network, genetic algorithm, and near neighbor algorithm) from selected features. Finally, the OBIA system enables images to be queried from the user interface and retrieved by means of fuzzy descriptors and oceanic structures. We tested our system with images from the Canary Islands and the North West African coast.Index Terms-Automatic recognition, fuzzy logic, image retrieval, moderate resolution imaging spectro-radiometer (MODIS), object-based image analysis (OBIA), ocean satellite images, sea-viewing field-of-view sensor (SeaWiFS).

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“…In this area, there are many MOS throughout the year. Many works have described the MOS in this area [8], [22]- [25].…”

Section: A Ocean Phenomenamentioning

confidence: 99%

OBIA System for Identifying Mesoscale Oceanic Structures in SeaWiFS and MODIS-Aqua Images

Vidal-Fernandez

Piedra-Fernández

Almendros-Jiménez

et al. 2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…These centres are due to the different wind conditions, variability in coastal topography, and the continental platform, giving rise to four well-differentiated zones along it delimited by the coasts' largest capes (see Figure 2), as proposed in García-Weil (1998); Garcia-Weil et al (2000); Barton et al (1998) ;Nieto, Demarcq, and McClatchie (2012), although with different limits. It so happens that there is frequent cloud cover in that zone, which causes the upwelling to be partially covered by clouds in most of the satellite images processed, leaving only pieces of it in view.…”

Section: Introductionmentioning

confidence: 85%

A location-based approach to the classification of mesoscale oceanic structures in SeaWiFS and Aqua-MODIS images of Northwest Africa

Vidal-Fernandez

Piedra-Fernández

Almendros-Jiménez

et al. 2015

International Journal of Remote Sensing

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This study presents a different approach to the classification of Mesoscale Oceanic Structures (MOS) present in the Northwest African area, based on their location. The main improvement stems from the partition of this area in four large zones perfectly differentiated by their morphological characteristics, with attention to seafloor topography and coastal relief. This decomposition makes it easier to recognize structures under adverse conditions, basically the presence of clouds partly hiding them. This is observed particularly well in upwellings, which are usually very large structures with a different morphology and genesis in each zone. This approach not only improves the classification of the upwellings, but also makes it possible to analyse changes in the MOS over time, thereby improving the prediction of its morphological evolution. To identify and label the MOS classified in the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Aqua-MODIS (Moderate Resolution Imaging Spectroradiometer) chlorophyll-a and temperature images, we used a tool specifically designed by our group for this purpose and which has again shown its validity in this new proposal.

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“…A detailed oceanographic description of this area can be found in [9]- [13]. In this area there are several significant mesoscale oceanic structures: upwellings, cold eddies, warm eddies and wakes (see Fig.…”

Section: A Ocean Satellite Imagesmentioning

confidence: 99%

A Framework for Ocean Satellite Image Classification Based on Ontologies

Almendros-Jiménez

Domene

Piedra-Fernández

2013

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In this paper we present a framework for ocean image classification based on ontologies. With this aim, we will describe how low and high level content of ocean satellite images can be modeled with an ontology. In addition, we will show how the image classification can be modeled with the ontology in which decision tree based classifiers and rule-based expert systems are represented. Particularly, the rule based expert systems include rules about low-level features (called training and labeling rules), and rules defined from the labeling (called human expert rules). The modeling with the ontology provides an extensible framework in which accommodate several methods of image classification. One of the main aims of our proposal is to provide a mechanism to share data about image classification between applications. We have developed an extensible Protégé plugin to classify images.

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Topographic effects on the mesoscale ocean circulation near Canarian archipelago examined by means of satellite images and laboratory simulations

Cited by 5 publications

References 10 publications

OBIA System for Identifying Mesoscale Oceanic Structures in SeaWiFS and MODIS-Aqua Images

OBIA System for Identifying Mesoscale Oceanic Structures in SeaWiFS and MODIS-Aqua Images

A location-based approach to the classification of mesoscale oceanic structures in SeaWiFS and Aqua-MODIS images of Northwest Africa

A Framework for Ocean Satellite Image Classification Based on Ontologies

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