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.
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 Almería, 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 OPEN ACCESSRemote Sens. 2015, 7 7379 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.
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
Transmitting sound waves into water, and measuring time interval between emission and return of a pulse, single beam echo sounder determines the depth of the sea. To obtain a bathymetric model representing sea-floor continuously, interpolation is necessary to process irregular spaced measured points resulting from echo sounder acquisition and calculate the depths in unsampled areas. Several interpolation methods are available in literature and the choice of the most suitable of them cannot be made a priori, but requires to be evaluated each time. This paper aims to compare different interpolation methods to process single beam echo sounder data of the Gulf of Pozzuoli (Italy) for 3D model achievement. The experiments are carried out in GIS (Geographic Information System) environment (Software: ArcGIS 10.3 and its extension Geostatistical Analyst by ESRI). The choice of the most accurate digital depth model is made using automatic cross validation. Radial basis function and kriging prove to be the best interpolation methods for the considered dataset.
In the last decades, combinations of natural and human factors\ud have resulted in extensive morphological changes to our coastlines and in\ud many cases have amplified erosion. In order to limit these changes and their\ud impact on coastal zone, it is important to plan specific actions; for this\ud purpose detailed cognizance of coastal zone is necessary. Different and\ud heterogeneous data such as historical and recent maps, remotely sensed\ud images and topographic survey result very useful to reconstruct temporal\ud shoreline changes. In this study the attention is focalized on Domitian coastal\ud zone (Italy), which is one of the most emblematic examples of coastal erosion\ud in Europe. Study of the shoreline evolution in this area between 1876 and\ud 2005 was used as the starting point of the present paper that investigates over\ud a span of seven years (2005 to 2012), by using remotely sensed data. The aim\ud is to adapt and integrate geomatics techniques to transform very high\ud resolution satellite images in powerful tools to analyse coastline changes. So,\ud in order to identify eroded and added areas, IKONOS-2 (2005), GeoEye-1\ud (2011) and WorldView-2 (2012) imageries are compared. These data-sets\ud were re-georeferred to improve the positional accuracy. More over\ud Normalized Difference Water Index (NDWI) was applied to pan-sharpened\ud multispectral images to facilitate coastline vectorising at the same\ud geometric resolution of panchromatic data. In addition, variance\ud propagation was considered to establish the accuracy of the reconstruction\ud of coastal evolution. Added and eroded areas were defined and related to\ud the impact of the defence structures that were built in this zone in 2011
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