This paper presents the preliminary results of an object-based image analysis aimed at the implementation of a package of procedures of remotely sensed object/ pattern/ scenery recognition specificallydesigned for the semi-automatic and automatic recognition of a batch of critical archaeological and ethnoarchaeological features. The research focuses on the guided recognition of mountain and plain features with elliptic, linear and polygonal shape on high resolution aerial photographs and near-infrared imagery. Case studies from Northern Italy are investigated, stating the image processing steps and highlighting the pros and cons of using an artificial intelligence for the analysis in the domain of Remote Sensing

Geobia approaches to remote sensing of fossil landscapes: two case studies from Northern Italy / De Guio, Armando; Magnini, Luigi; Bettineschi, Cinzia. - 1:(2015), pp. 45-53.

Geobia approaches to remote sensing of fossil landscapes: two case studies from Northern Italy

MAGNINI, LUIGI;
2015

Abstract

This paper presents the preliminary results of an object-based image analysis aimed at the implementation of a package of procedures of remotely sensed object/ pattern/ scenery recognition specificallydesigned for the semi-automatic and automatic recognition of a batch of critical archaeological and ethnoarchaeological features. The research focuses on the guided recognition of mountain and plain features with elliptic, linear and polygonal shape on high resolution aerial photographs and near-infrared imagery. Case studies from Northern Italy are investigated, stating the image processing steps and highlighting the pros and cons of using an artificial intelligence for the analysis in the domain of Remote Sensing
9789089647153
Geobia approaches to remote sensing of fossil landscapes: two case studies from Northern Italy / De Guio, Armando; Magnini, Luigi; Bettineschi, Cinzia. - 1:(2015), pp. 45-53.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11388/240058
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