152 research outputs found
Big Earth Data for Cultural Heritage in the Copernicus Era
No full textDigital data is stepping in its golden age characterized by an increasing
growth of both classical and emerging big earth data along with trans- and multidisciplinary
methodological approaches and services addressed to the study, preservation
and sustainable exploitation of cultural heritage (CH). The availability of new
digital technologies has opened new possibilities, unthinkable only a few years ago
for cultural heritage. The currently available digital data, tools and services with
particular reference to Copernicus initiatives make possible to characterize and
understand the state of conservation of CH for preventive restoration and opened up
a frontier of possibilities for the discovery of archaeological sites from above and
also for supporting their excavation, monitoring and preservation. The different
areas of intervention require the availability and integration of rigorous information
from different sources for improving knowledge and interpretation, risk assessment
and management in order to make more successful all the actions oriented to the
preservation of cultural properties. One of the biggest challenges is to fully involve
the citizen also from an emotional point of view connecting “pixels with people”
and “bridging” remote sensing and social sensing
Satellite and close range analysis for the surveillance and knowledge improvement of the Nasca geoglyphs
No full textTraditionally the history of remote sensing began during the First World War when aerial photography became a valuable reconnaissance tool. However, moving back more than a thousand years, the real pioneers of remote observation were probably the Nasca, a pre-Hispanic civilization living in southern Peru, between 100BC and 700 AD. They used ‘earth observation’ as a mean of cultural expression drawing the geoglyphs (known as Nasca Lines) only visible from above. These drawings were made on flat desert surface of the Pampa by removing or clearing sand or stones, to create paths for ritual functions to please the gods and create harmonious relationships between man and environment. In this paper, the Nasca geoglyphs in Pampa de Atarco, are object of remote sensing based investigations with the twofold aim to identify and characterize them as well as to analyse and monitor their fragile state of conservation, threatened mainly by vandalism and off road vehicles. The approach herein proposed includes the integration and reuse of diverse remote sensing dataset, from multispectral satellite to Unmanned Aerial Vehicle (UAV) based LSAR data and close range photogrammetry. In particular, a multidate (2002–2013) very high resolution (VHR) optical satellite dataset has been processed in the spatial and temporal domain using textural indicators, including Skewness, Principal Component Analysis (PCA), and automatic classification tools which allowed us to enhance the visibility of disturbance features and to automatically extract them. The best results in terms of enhancement and automatic extraction capability of disturbance features have been obtained by Skewness. Moreover, the reuse of UAV L SAR-based correlation map, available free of charge from NASA, provided useful information on the state of disturbance from 2013 to 2015, widening the observation time window of the VHR satellite data set from 2002 to 2013. Finally, the integrated use of satellite VHR data with UAV-based photographs and DTMs, processed using structure from motion (SfM), allowed us to characterize, identify and reconstruct the relative chronological sequence of geoglyphs thus providing new insights and opening new perspectives for archaeological studies
Full-waveform Airborne Laser Scanning for the detection of medieval archaeological microtopographic relief
No full textThis paper focuses on the detection and spatial characterization of microtopographic relief linked to archaeological remains using full-waveform (FW) Airborne Laser Scanning (ALS). ALS is an optical measurement technique for obtaining high-precision information on the Earth's surface including basic terrain mapping, such as Digital Terrain Model (DTM) and Digital Surface Model (DSM). In the field of cultural heritage management, ALS can provide detailed information useful for feature extraction, but the detection of archaeological microtopographic relief is still a challenge especially for vegetated and highly sloped areas. The investigation was carried out for the archaeological area of Monte Irsi (Southern Italy) characterized by dense herbaceous cover and complex topographical and morphological features, which make air/space prospection very difficult. Results from our investigations pointed out that ALS is a valuable data source to detect and map cultural features even under dense vegetation. (C) 2009 Elsevier Masson SAS. All rights reserved
Remote and close range sensing for the automatic identification and characterization of archaeological looting. The case of Peru
No full textLooting is the major source of artefacts for the antiquities market. Specific measures are needed to fight the whole chain of the illicit activities undertaken by criminal organizations (from the excavation to the selling of the artefacts), and they should be devised for each phase of such illegal activities. The development and use of appropriate technologies for the identification of the most 'vulnerable' sites, and the timely detection and automatic quantification of the extension of the looted areas are crucial steps for setting up a monitoring system working also for remote and inaccessible archaeological areas, often in regions affected by armed conflicts or characterized by flight restrictions. In this context, Earth Observation (EO) technologies can provide reliable information: (i) to quantify the looting phenomenon even if it is on an 'industrial scale' over large areas, and (ii) to set up a systematic monitoring tool to trace the illicit trade in antiquities. In this paper, an improvement of the Archaeological Looting Feature Extraction Approach (ALFEA) -developed by the same authors in 2018- is proposed to further improve the ability in the automatic identification and extraction of looting features for heterogeneous desert landscapes, characterized not only by looting patterns but also by archaeological micro-relief and emerging remains, as well as by natural geomorphological features and the presence of structures and dirt pathways, which exhibit a similar spectral behavior but dimensions, morphology, and/or geometric patterns different from those linked to looting. The improvement of ALFEA (ALFEA-I) was applied in significant test areas considered among the most important archaeological sites in Peru, (i) Pachacamac close to Lima, and (ii) Ventarron in the Lambayeque region Northern Peru. The first site is characterized by past clandestine excavations and looting is difficult to recognize both in situ and from satellite image; the second site is affected by more recent archaeological disturbances due to grave robberies, easier to identify from remote sensing data. The original ALFEA -composed of the sequential integration of spatial autocorrelation statistics, unsupervised classification, and segmentation- has been herein refined by adding a processing step based on multi-threshold parameters of segmentation, thus improving the performance in terms of extraction capability of looting features in case of heterogeneous areas. Tthe integration of satellite based data processing with unmanned aerial vehicle (UAV) based close range acquisitions has proved to be effective in enhancing the visibility of old looting features, crucial for the validation of ALFEA-I
Seasonal and yearly polarimetric time series analysis of Radarsat 2 quad pol data over the area around Rome
No full textPre-motor deficits in left spatial neglect: an EEG study on contingent negative variation (CNV) and response-related beta oscillatory activity
No full textRight Brain Damaged patients with left spatial neglect (N+), are characterised by poor allocation of attention in the contralesional left side of space. In a recent study (Lasaponara et al., 2018) we showed during orienting of spatial attention with endogenous central cues, both the EEG markers reflecting the early phases of orienting (Early Directing Attention Negativity) and those reflecting the late setting-up of sensory facilitation in the visual cortex (Late Directing Attention Positivity) are disturbed in N+ when these patients attend the left side of space. In the healthy brain, endogenous cues also elicit EEG activity related to the preparation of manual responses to upcoming spatial targets. Here, we wished to expand on our previous findings and investigate the EEG correlates of cue-related response preparation in N+ patients. To this aim we investigated the Contingent Negative Variation (CNV) response and the pre-motor Beta-oscillatory activity evoked by spatially informative central cues during the performance of a Posner task. Due to concomitant contralesional motor impairments, N+ an N- patients performed the task only with the ipsilesional right-hand. Compared to healthy controls and patients without neglect, N+ displayed a pathological suppression of CNV component that was independent of cue direction. In addition, the amplitude of the CNV in response to right-pointing cues was positively correlated with neglect severity in line bisection. N+ also displayed a pathological enhancement of pre-motor Beta oscillations over the left hemisphere during the time period that preceded manual responses to targets in the left side of space, particularly to invalidly cued ones. Synchronization in the Beta-band (ERS) was also correlated with lower detection rate and slower RTs to Invalid targets in the left side of space. These results provide new insights on the premotor components of the spatial orienting deficits suffered by patients with left spatial neglect and can help improving its diagnosis and rehabilitation
CyberPark 2000: protected aeras management pilot project. Satellite time series vegetation monitoring
No full textEVALUATION OF A NEW SATELLITE-BASED METHOD FOR FOREST FIRE DETECTION
No full textAdvanced Very High Resolution Radiometer (AVHRR)-based fire detection methods are considered in this work in order to assess their effective usefulness in the framework of civil programmes for fire risk and damage mitigation. The discussion is divided into the evaluation of the most commonly used methods and the description of a new fire detection procedure which is proposed in this paper. Commonly used detection methods are based on using absolute threshold values for decision tests. These values usually match only with very local, uniform (in space and time) situations, and are often inadequate when applied to heterogeneous, or simply different, geographical areas or seasons. A high number of false alarms, so high as to make the satellite-based product not operationally utilizable, is the main disadvantage of the fixed-threshold approach. The new fire-detection procedure proposed here makes use only of historical AVHRR data in order to automatically produce local (in space and time) threshold values, suitable for fire-event detection also in very critical situations. High fire discrimination capabilities with low false-alarm rates, simple unsupervised implementation and, above all, flexibility for automatic extension to completely different geographic areas and observation conditions, are the main advantages associated with this new technique. Results obtained for different Italian areas have been successfully compared with ground observations made by the Italian Forestry Service. Tests made over a long observation period show that, on cloud-free regions, more than 75% of significant forest fires are detected with less than 20% of false alarms
Erratum: Chen, F. et al. A Space View of Radar Archaeological Marks: First Applications of COSMO-SkyMed X-Band Data. Remote Sens. 2015, 7(1), 24–50
No full textIn this paper [1], the author, Rosa Lasaponara, should have been numbered as 1 and 6, instead of only 6.[...
On the Use of Google Earth Engine and Sentinel Data to Detect “Lost” Sections of Ancient Roads. The Case of Via Appia
No full textThe currently available tools and services as open
and free cloud resources to process big satellite data opened
up a new frontier of possibilities and applications including
archeological research. These new research opportunities also
pose several challenges to be faced, as, for example, the data
processing and interpretation. This letter is about the assessment
of different methods and data sources to support a visual
interpretation of EO imagery. Multitemporal Sentinel 1 and
Sentinel 2 data sets have been processed to assess their capability
in the detection of buried archeological remains related to some
lost sections of the ancient Via Appia road (herein selected
as case study). The very subtle and nonpermanent features
linked to buried archeological remains can be captured using
multitemporal (intra- and inter-year) satellite acquisitions, but
this requires strong hardware infrastructures or cloud facilities,
today also available as open and free tools as Google Earth Engine
(GEE). In this study, a total of 2948 Sentinel 1 and 743 Sentinel
2 images were selected (from February 2017 to August 2020)
and processed using GEE to enhance and unveil archeological
features. Outputs obtained from both Sentinel 1 and Sentinel
2 have been successfully compared with in situ analysis and
high-resolution Google Earth images
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