Dr. Rosa Lasaponara Profile

Dr. Rosa Lasaponara

Researcher at Consiglio Nazionale delle Ricerche

SPIE Involvement:

Conference Program Committee | Author

Publications (15)

PROCEEDINGS ARTICLE | December 9, 2016

Educational activities of remote sensing archaeology (Conference Presentation)

Proc. SPIE. 10005, Earth Resources and Environmental Remote Sensing/GIS Applications VII

KEYWORDS: Aerospace engineering, Sensors, Satellites, Remote sensing, Vegetation, Cultural heritage, Analytical research, Scientific research, Ground penetrating radar

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PROCEEDINGS ARTICLE | August 12, 2016

Searching data for supporting archaeo-landscapes in Cyprus: an overview of aerial, satellite, and cartographic datasets of the island

Proc. SPIE. 9688, Fourth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2016)

KEYWORDS: Visualization, Sensors, Satellites, Remote sensing, Satellite imaging, Geographic information systems, Orthophoto maps, Analytical research, Spatial resolution, Earth observing sensors

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The landscape of Cyprus is characterized by transformations that occurred during the 20th century, with many of such changes being still active today. Landscapes’ changes are due to a variety of reasons including war conflicts, environmental conditions and modern development that have often caused the alteration or even the total loss of important information that could have assisted the archaeologists to comprehend the archaeo-landscape.

The present work aims to provide detailed information regarding the different existing datasets that can be used to support archaeologists in understanding the transformations that the landscape in Cyprus undergone, from a remote sensing perspective. Such datasets may help archaeologists to visualize a lost landscape and try to retrieve valuable information, while they support researchers for future investigations. As such they can further highlight in a predictive manner and consequently assess the impacts of landscape transformation -being of natural or anthropogenic cause- to cultural heritage.

Three main datasets are presented here: aerial images, satellite datasets including spy satellite datasets acquired during the Cold War, and cadastral maps. The variety of data is provided in a chronological order (e.g. year of acquisitions), while other important parameters such as the cost and the accuracy are also determined. Individual examples of archaeological sites in Cyprus are also provided for each dataset in order to underline both their importance and performance. Also some pre- and post-processing remote sensing methodologies are briefly described in order to enhance the final results. The paper within the framework of ATHENA project, dedicated to remote sensing archaeology/CH, aims to fill a significant gap in the recent literature of remote sensing archaeology of the island and to assist current and future archaeologists in their quest for remote sensing information to support their research.

PROCEEDINGS ARTICLE | August 5, 2013

GIS and archaeology: a spatial predictive model for neolithic sites of the Tavoliere (Apulia)

Proc. SPIE. 8795, First International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2013)

KEYWORDS: Statistical analysis, Solar radiation models, Data modeling, Remote sensing, Geology, Geographic information systems, Spatial analysis, Pollution control, Raster graphics, Statistical modeling

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PROCEEDINGS ARTICLE | October 14, 2008

Satellite-based enhancement of archaeological marks through data fusion techniques

Proc. SPIE. 7110, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII

KEYWORDS: Image fusion, Near infrared, Satellites, Image resolution, Vegetation, Optical inspection, Satellite imaging, Spatial resolution, Earth observing sensors, Data fusion

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PROCEEDINGS ARTICLE | October 13, 2008

Integrated and multiscale NDT for the study of architectural heritage

Proc. SPIE. 7110, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII

KEYWORDS: Infrared cameras, Thermography, Reflection, Inspection, Nondestructive evaluation, Ultrasonics, Infrared radiation, Antennas, Ground penetrating radar, General packet radio service

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PROCEEDINGS ARTICLE | November 6, 2007

Performance evaluation of data fusion techniques for archaeological prospection based on satellite data

Proc. SPIE. 6749, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII

KEYWORDS: Image fusion, Principal component analysis, Sensors, Satellites, Image processing, Wavelets, Multispectral imaging, Spatial resolution, Earth observing sensors, Data fusion

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PROCEEDINGS ARTICLE | October 26, 2007

Mapping forest fuel types by using satellite ASTER data and neural nets

Proc. SPIE. 6742, Remote Sensing for Agriculture, Ecosystems, and Hydrology IX

KEYWORDS: Data modeling, Sensors, Satellites, Remote sensing, Vegetation, Data acquisition, Ecosystems, Neural networks, Associative arrays, Earth observing sensors

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PROCEEDINGS ARTICLE | October 9, 2007

SPOT-VGT time series based estimation of fire-induced variability in vegetation covers

Proc. SPIE. 6742, Remote Sensing for Agriculture, Ecosystems, and Hydrology IX

KEYWORDS: Satellites, Remote sensing, Clouds, Vegetation, Atmospheric corrections, Data acquisition, Ecosystems, Spatial resolution, Data centers, Signal detection

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PROCEEDINGS ARTICLE | October 17, 2006

Remote characterization of fuel types using multi- and hyper-spectral data

Proc. SPIE. 6359, Remote Sensing for Agriculture, Ecosystems, and Hydrology VIII

KEYWORDS: Landsat, Data modeling, Satellites, Remote sensing, Vegetation, Data acquisition, Ecosystems, Image classification, Analytical research, Earth observing sensors

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PROCEEDINGS ARTICLE | October 11, 2006

Archaeological prospection based on satellite QuickBird imagery

Proc. SPIE. 6366, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VI

KEYWORDS: Image fusion, Near infrared, Edge detection, Sensors, Satellites, Vegetation, Satellite imaging, Reconnaissance, Earth observing sensors, Data fusion

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PROCEEDINGS ARTICLE | February 24, 2004

Estimation of seasonal trends of satellite-based parameters useful for the monitoring of surface moisture content: preliminary results by using NIR-SWIR data of SPOT vegetation

Proc. SPIE. 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V

KEYWORDS: Near infrared, Short wave infrared radiation, Statistical analysis, Agriculture, Satellites, Reflectivity, Vegetation, Data acquisition, Spatial resolution, Data analysis

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PROCEEDINGS ARTICLE | February 24, 2004

Performance evaluation of AVHRR-based methods for the estimation of fire susceptibility in southern Italy

Proc. SPIE. 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V

KEYWORDS: Thermography, Forestry, Agriculture, Satellites, Clouds, Vegetation, Satellite imaging, Ecosystems, Neodymium, Earth observing sensors

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PROCEEDINGS ARTICLE | January 23, 2002

Pollino Project Action D: a multi-scale approach in the space-time domain to environmental risk monitoring

Proc. SPIE. 4545, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology

KEYWORDS: Environmental monitoring, Landsat, Sensors, Satellites, Remote sensing, Photography, Geographic information systems, Spatial resolution, Earth observing sensors, Temperature metrology

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PROCEEDINGS ARTICLE | December 17, 1999

Forest fire danger estimation based on the integration of satellite AVHRR data and topographic factors

Proc. SPIE. 3868, Remote Sensing for Earth Science, Ocean, and Sea Ice Applications

KEYWORDS: Forestry, Data modeling, Satellites, Remote sensing, Reliability, Vegetation, Meteorology, Tantalum, Data integration, Temperature metrology

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PROCEEDINGS ARTICLE | December 11, 1998

Fire detection by AVHRR: toward a new approach for operational monitoring

Proc. SPIE. 3499, Remote Sensing for Agriculture, Ecosystems, and Hydrology

KEYWORDS: Forestry, Detection and tracking algorithms, Satellites, Combustion, Clouds, Ecosystems, Radiometry, Algorithm development, Flame detectors, Earth observing sensors

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