Automatic features extraction in sub-urban landscape using very high resolution Cosmo-Skymed SAR images

2011 ◽  
Author(s):  
Fabio Del Frate ◽  
Chiara Pratola ◽  
Giovanni Schiavon ◽  
Domenico Solimini
Keyword(s):  
High Resolution ◽  
Urban Landscape ◽  
Features Extraction ◽  
Sar Images ◽  
Very High

Sub-urban landscape characterization by very high-resolution X-band COSMO-Skymed SAR images: first results

2010 ◽  
Author(s):  
Fabio Del Frate ◽  
Domenico Loschiavo ◽  
Chiara Pratola ◽  
Giovanni Schiavon ◽  
Domenico Solimini
Keyword(s):  
High Resolution ◽  
Urban Landscape ◽  
Sar Images ◽  
Landscape Characterization ◽  
X Band ◽  
First Results ◽  
Very High

scholarly journals Shoreline Extraction Based on an Active Connection Matrix (ACM) Image Enhancement Strategy

2019 ◽  
Vol 8 (1) ◽  
pp. 9 ◽  
Author(s):  
Sara Zollini ◽  
Maria Alicandro ◽  
María Cuevas-González ◽  
Valerio Baiocchi ◽  
Donatella Dominici ◽  
...  
Keyword(s):  
High Resolution ◽  
Anthropogenic Factors ◽  
Connection Matrix ◽  
Sar Images ◽  
Dynamic Algorithm ◽  
Water Index ◽  
Canny Edge ◽  
Experimental Algorithm ◽  
Changes Over Time ◽  
Very High

Coastal environments are facing constant changes over time due to their dynamic nature and geological, geomorphological, hydrodynamic, biological, climatic and anthropogenic factors. For these reasons, the monitoring of these areas is crucial for the safeguarding of the cultural heritage and the populations living there. The focus of this paper is shoreline extraction by means of an experimental algorithm, called J-Net Dynamic (Semeion Research Center of Sciences of Communication, Rome, Italy). It was tested on two types of image: a very high resolution (VHR) multispectral image (WorldView-2) and a high resolution (HR) radar synthetic aperture radar (SAR) image (Sentinel-1). The extracted shorelines were compared with those manually digitized for both images independently. The results obtained with the J-Net Dynamic algorithm were also compared with common algorithms, widely used in the literature, including the WorldView water index and the Canny edge detector. The results show that the experimental algorithm is more effective than the others, as it improves shoreline extraction accuracy both in the optical and SAR images.

Contextual Descriptors for Scene Classes in Very High Resolution SAR Images

2012 ◽  
Vol 9 (1) ◽  
pp. 80-84 ◽  
Author(s):  
Anca A. Popescu ◽  
Inge Gavat ◽  
Mihai Datcu
Keyword(s):  
High Resolution ◽  
Sar Images ◽  
Very High

Markovian Change Detection of Urban Areas Using Very High Resolution Complex SAR Images

2014 ◽  
Vol 11 (5) ◽  
pp. 995-999 ◽  
Author(s):  
Fabio Baselice ◽  
Giampaolo Ferraioli ◽  
Vito Pascazio
Keyword(s):  
High Resolution ◽  
Change Detection ◽  
Urban Areas ◽  
Sar Images ◽  
Very High
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