Special Issue "New Perspectives of Remote Sensing for Archaeology"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (30 June 2014)
Dr. Rosa Lasaponara
CNR-IMAA (National Research Council, Institute for Environmental Analysis), C.da S. Loya, 85050 Tito Scalo (PZ), Italy
Phone: +39 0971 427214
Fax: +39 0971 427222
Interests: remote sensing; data processing; microwave sensor design; analytical methods, modeling, readout and software for sensors; sensor technology and new sensor principles
Dr. Nicola Masini
CNR-IBAM (National Research Council, Institute for Archaeological and Architectural Heritage), C.da S. Loya, 85050 Tito Scalo (PZ), Italy
Phone: +39 0971 427321
Fax: +39 0971 427333
Interests: remote sensing for archaeology; Lidar; archaeogeophisics; non invasive tests for historical building
Starting from 2000, the availability of the first very high resolution satellite imagery and LiDAR provided new opportunities for archaeological prospection, allowing us to enlarge the fields of application, from site discovery to monitoring, from single site to cultural landscape, also for cultural heritage covered by vegetation or located in extensive and difficult remote areas.
Currently, the main challenges to be addressed are mainly the need to set up ad hoc methodological approaches for different environmental and geomorphological conditions (from forest to desert, from flat areas to complex topography), types of applications (form preventive archaeology to preservation and protection), for all the current available earth observation technologies, including SAR and geophysics.
In detail the main topics will be:
- Integration of active and passive remote sensing technologies including ground based investigations (geophysics, ground spectroscopy)
- Semiautomatic and automatic approaches for extracting cultural information
- Interconnection between environmental changes and dynamics of human frequentation: the contribution of Earth Observation
- Remote Sensing as basic tool to support virtual fruition of ancient landscapes and archaeological sites
- Remote sensing and geospatial analysis for preventive archaeology;
- 3D modeling and visualization issues from satellite, airborne and terrestrial sensors
- Integration of different data acquisition technologies including UAV
Dr. Rosa Lasaponara
Dr. Nicola Masini
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.
Article: Openness as Visualization Technique for Interpretative Mapping of Airborne Lidar Derived Digital Terrain Models
Remote Sens. 2013, 5(12), 6427-6442; doi:10.3390/rs5126427
Received: 16 October 2013; in revised form: 25 November 2013 / Accepted: 26 November 2013 / Published: 28 November 2013| Cited by 1 | PDF Full-text (1639 KB) | HTML Full-text | XML Full-text
Article: Orthogonal Equations of Multi-Spectral Satellite Imagery for the Identification of Un-Excavated Archaeological Sites
Remote Sens. 2013, 5(12), 6560-6586; doi:10.3390/rs5126560
Received: 26 August 2013; in revised form: 26 November 2013 / Accepted: 27 November 2013 / Published: 3 December 2013| PDF Full-text (7694 KB) | HTML Full-text | XML Full-text
Remote Sens. 2014, 6(3), 2195-2212; doi:10.3390/rs6032195
Received: 31 December 2013; in revised form: 18 February 2014 / Accepted: 27 February 2014 / Published: 10 March 2014| PDF Full-text (1664 KB) | HTML Full-text | XML Full-text
Last update: 6 January 2014