Automatic detection and monitoring of oil spills illegal discharges is fundamental importance in ensuring compliance with marine legislation protection the coastal environments, which are under considerable threat from intentional or accidental spills, uncontrolled sewage wastewater discharged. In this paper, level set based image segmentation was evaluated for real‐time tracking SAR imagery. The processing scheme developed consists a pre‐processing step, an advanced simplification takes...

Edge preserving smoothing and image simplification is of fundamental importance in a variety remote sensing applications during feature extraction object detection procedures. The construction pre‐processing filtering tool for edge segmentation tasks still an open matter. Towards this end, paper brings together two advanced nonlinear scale space representations, anisotropic diffusion morphological levellings, forming processing scheme by their combination. proposed was applied to watershed...

A methodology was developed previously by the authors for segmentation of Global Digital Elevation Model (GTOPO30) to three terrain classes (mountains, basins and piedmont slopes) it applied Great Basin Section (south-west USA). In present research effort, mountain objects were identified through a connected component-labelling algorithm on class. Taking into account physical perceptual attributes features, 12 morphometric defined used as descriptors in their parametric representation....

A region-based level set segmentation was developed for the automatic detection of man-made objects from aerial and satellite images. The essence approach is to optimize position geometric form an evolving curve, by measuring information within regions that compose a particular image partition based on their statistical description. present variational model fully automated without need manually specify initial contour. Furthermore, it converges after small number iterations, allowing...

Monitoring and mapping urban changes is of great importance for the development, planning management zone, especially in countries with a rapidly growing area. The aim this paper was to develop GEographic Object-Based Image Analysis (GEOBIA) approach, by integrating Deep Learning classification Fuzzy Ontologies through multi-scale analysis, monitor building suburban areas Greece. Three east Attica, Greece were selected as representative test methodology. For each area, one QuickBird...

Classification of land surface to landforms is fundamental interpretation various environmental processes. The heterogeneous landform descriptions and classification approaches, in combination with the scale dependence digital elevation models (DEMs) their products, defy development an interoperable transferable automated approach. A theoretical framework has proposed that should be regionalised morphologic meaningful objects, delimited by discontinuities (i.e. slope breaks inflections)...

The aim of this study is to investigate the potential Sentinel-2 imagery for identification and determination forest patches particular interest, with respect ecosystem integrity biodiversity produce a relevant map, based on Simpson's diversity index in Taxiarchis university research forest, Chalkidiki, North Greece. OBIA being developed bi-temporal summer winter imagery. Fuzzy rules, which are topographic factors, such as terrain elevation slope distribution each tree species, derived from...

Abstract In Geographic Object-Based Image Analysis (GEOBIA) an image is partitioned into objects by a segmentation algorithm. These are then classified semantic categories based on unsupervised/ supervised methods, or knowledge-based such as ontology. The aim of this paper was to develop SPatial Ontology Reasoner (SPOR) allow the development GEOBIA ontologies employing fuzzy, spatial, and multi-scale representations, with time efficiency. An enhanced version Web Language 2 (OWL 2) fuzzy...

Abstract This research focuses on the investigation of remote-sensing techniques for detection coastal sub-aerial springs and submarine groundwater discharges using airborne thermal hyperspectral imagery. Very high spatial resolution images were acquired Thermal Airborne Broadband Imager 320 (TABI-320) Compact Spectrographic 550 (CASI-550) sensors. Extensive in situ spectroradiometer oceanographic measurements carried out parallel with image acquisitions. Experiments analysis data show that...

The aim of this paper was to investigate the development a fuzzy knowledge base within an object based image analysis (OBIA) system for automatic change detection buildings. A multitemporal very high resolution satellite data (QuickBird and IKONOS) performed. Two case studies Keratea suburb Athens, Greece were selected. For each dataset, primitive objects created through multi-resolution segmentation, in five hierarchical levels, following mixed top-down strategy established by...

Region merging is the most effective method for segmentation of remote sensing data. The quality and size resulted image objects controlled by a global heterogeneity threshold, termed as scale parameter. However, multidimensional nature visible features in scene defies use an even optimum single In this study, novel region proposed, where local parameter defined each object its internal external measures (i.e., variance Moran’s I). This allows with low to be further merged higher values,...

An approach towards automatic coastline detection from satellite imagery through edge techniques is presented. Linear transformations, such as Gaussian filtering and nonlinear median, adaptive morphological filtering, are combined image smoothing enhancement. Two detectors applied, a Laplacian operator the classical Canny threshold detector. The connectivity recovered with combination of transformations. results appear promising.