Claudio Parente

Coastline extraction using high resolution WorldView-2 satellite imagery

Abstract The aim of this paper is to remark possibilities to use WorldView-2 imagery for coastline extraction. Applications are conducted on a Phlegrean area in the Campania Region (Italy): the considered range of coastline is particularly interesting because it shows two typologies of shoreline including reefs interspersed with segments of sandy beach. Two indices are used: Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI).To enhance geometric resolution of the results pan-sharpening is applied so as to obtain maps with the same pixel dimensions of the panchromatic data. To solve the problem of thresholds determination that typically affects the classification, Maximum Likelihood method based on training sites is adopted to distinguish bare soil and sea water. Best results are given by NDWI and, comparing the resultant coastline with that obtained with visual interpretation of images, shifts of less than 1 m outcome from pan-sharpened data.

Object-Based Greenhouse Horticultural Crop Identification from Multi-Temporal Satellite Imagery: A Case Study in Almeria, Spain

Greenhouse detection and mapping via remote sensing is a complex task, which has already been addressed in numerous studies. In this research, the innovative goal relies on the identification of greenhouse horticultural crops that were growing under plastic coverings on 30 September 2013. To this end, object-based image analysis (OBIA) and a decision tree classifier (DT) were applied to a set consisting of eight Landsat 8 OLI images collected from May to November 2013. Moreover, a single WorldView-2 satellite image acquired on 30 September 2013, was also used as a data source. In this approach, basic spectral information, textural features and several vegetation indices (VIs) derived from Landsat 8 and WorldView-2 multi-temporal satellite data were computed on previously segmented image objects in order to identify four of the most popular autumn crops cultivated under greenhouse in Almeria, Spain (i.e., tomato, pepper, cucumber and aubergine). The best classification accuracy (81.3% overall accuracy) was achieved by using the full set of Landsat 8 time series. These results were considered good in the case of tomato and pepper crops, being significantly worse for cucumber and aubergine. These results were hardly improved by adding the information of the WorldView-2 image. The most important information for correct classification of different crops under greenhouses was related to the greenhouse management practices and not the spectral properties of the crops themselves.

Detection of environmental hazards through the feature-based fusion of optical and SAR data: a case study in southern Italy

The use of remote-sensing images is becoming common practice in the fight against environmental crimes. However, the challenge of exploiting the complementary information provided by radar and optical data, and by more conventional sources encoded in geographic information systems, is still open. In this work, we propose a new workflow for the detection of potentially hazardous cattle-breeding facilities, exploiting both synthetic aperture radar and optical multitemporal data together with geospatial analyses in the geographic information system environment. The data fusion is performed at a feature-based level. Experiments on data available for the area of Caserta, in southern Italy, show that the proposed technique provides very high detection capability, up to 95%, with a very low false alarm rate. A fast and easy-to-use system has been realized based on this approach, which is a useful tool in the hand of agencies engaged in the protection of territory.

Integrating Sensors into a Marine Drone for Bathymetric 3D Surveys in Shallow Waters

This paper demonstrates that accurate data concerning bathymetry as well as environmental conditions in shallow waters can be acquired using sensors that are integrated into the same marine vehicle. An open prototype of an unmanned surface vessel (USV) named MicroVeGA is described. The focus is on the main instruments installed on-board: a differential Global Position System (GPS) system and single beam echo sounder; inertial platform for attitude control; ultrasound obstacle-detection system with temperature control system; emerged and submerged video acquisition system. The results of two cases study are presented, both concerning areas (Sorrento Marina Grande and Marechiaro Harbour, both in the Gulf of Naples) characterized by a coastal physiography that impedes the execution of a bathymetric survey with traditional boats. In addition, those areas are critical because of the presence of submerged archaeological remains that produce rapid changes in depth values. The experiments confirm that the integration of the sensors improves the instruments’ performance and survey accuracy.

SAR/multispectral image fusion for the detection of environmental hazards with a GIS

In this paper we propose a GIS-based methodology, using optical and SAR remote sensing data, together with more conventional sources, for the detection of small cattle breeding areas, potentially responsible of hazardous littering. This specific environmental problem is very relevant for the Caserta area, in southern Italy, where many small buffalo breeding farms exist which are not even known to the productive activity register, and are not easily monitored and surveyed. Experiments on a test area, with available specific ground truth, prove that the proposed systems is characterized by very large detection probability and negligible false alarm rate.

Modelli tematici 3D della copertura del suolo a partire da DTM e immagini telerilevate ad alta risoluzione WorldView-2

The integration of thematic layers and DTM (Digital Terrain Model) becomes possible to achieve 3D models that can contextually display the variability of both the morphology and territorial and / or environmental components. WorldView-2 high resolution images, presenting a reduced size of the pixels on the ground (0.5 m in panchromatic and 2 m in multispectral) and a high spectral resolution (with 8 bands in the portion of the electromagnetic spectrum between wavelengths 400 nm and 1040 nm) allow the creation of very detailed maps of land cover. The simultaneous availability of DTM with appropriate cell size transforms these thematic layers in digital 3D models with high resolution.This paper is aimed to test positional and thematic accuracies that can be achieved in the construction of 3D models of land cover using WorldView-2 images. Phlegraean area (in Campania region, Italy), characterized by particular morphological configuration, mainly due to the presence of craters and volcanic cones, is considered. The dataset is firstly orthorectified, using rational polynomial functions, and then processed using supervised classification (Maximum Likelihood method) to identify several homogenous classes. The indices derived by confusion matrix (Producer Accuracy, User Accuracy, Overall Accuracy, Cohen Index) permit to check the thematic accuracy. DTM is derived from technical maps (at 1:5.000 scale) and used as the basis for 3D models of land cover.

Comparison of Different Algorithms to Orthorectify WorldView-2 Satellite Imagery

Due to their level of spatial detail (pixel dimensions equal to or less than 1 m), very high-resolution satellite images (VHRSIs) need particular georeferencing and geometric corrections which require careful orthorectification. Although there are several dedicated algorithms, mainly commercial and free software for geographic information system (GIS) and remote sensing applications, the quality of the results may be inadequate in terms of the representation scale for which these images are intended. This paper compares the most common orthorectification algorithms in order to define the best approach for VHRSIs. Both empirical models (such as 2D polynomial functions, PFs; or 3D rational polynomial functions, RPFs) and rigorous physical and deterministic models (such as Toutin) are considered. Ground control points (GCPs) and check points (CPs)—whose positions in the image as, well as in the real world, are known—support algorithm applications. Tests were executed on a WorldView-2 (WV-2) panchromatic image of an area near the Gulf of Naples in Campania (Italy) to establish the best-performing algorithm. Combining 3D RPFs with 2D PFs produced the best results.