1,721,047 research outputs found
Satellite and close range analysis for the surveillance and knowledge improvement of the Nasca geoglyphs
Full text linkTraditionally 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 textCyberPark 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
Potential of quad pol C-band, single and dual pol L-band SAR to identify buried archaeological features
No full textMulti-frequency, polarimetric SAR analysis for archaeological prospection
No full textThe aim of this study is to assess the sensitivity to buried archaeological structures of C- and L-band Synthetic Aperture Radar (SAR) in various polarisations. In particular, single and dual polarised data from the Phased Array type L-band SAR (PALSAR) sensor on-board the Advanced Land Observing Satellite (ALOS) is used, together with quadruple polarised (quad pol) data from the SAR sensor on Radarsat-2. The study region includes an isolated area of open fields in the eastern outskirts of Rome where buried structures are documented to exist. Processing of the SAR data involved multitemporal averaging, analysis of target decompositions, study of the polarimetric signatures over areas of suspected buried structures and changes of the polarimetric bases in an attempt to enhance their visibility. Various ancillary datasets were obtained for the analysis, including geological and lithological charts, meteorological data, Digital Elevation Models (DEMs), optical imagery and an archaeological chart.
For the Radarsat-2 data analysis, results show that the technique of identifying the polarimetric bases that yield greatest backscatter over anomaly features, and subsequently changing the polarimetric bases of the time series, succeeded in highlighting features of interest in the study area. It appeared possible that some of the features could correspond with structures documented on the reference archaeological chart, but there was not a clear match between the chart and the results of the Radarsat-2 analysis. A similar conclusion was reached for the PALSAR data analysis. For the PALSAR data, the volcanic nature of the soil may have hindered the visibility of traces of buried features. Given the limitations of the accuracy of the archaeological chart and the spatial resolution of both the SAR datasets, further validation would be required to draw any precise conclusions on the sensitivity of the SAR data to buried structures. Such a validation could include geophysical prospection or excavation
Google earth engine as multi-sensor open-source tool for supporting the preservation of archaeological areas: The case study of flood and fire mapping in metaponto, italy
Full text linkIn recent years, the impact of Climate change, anthropogenic and natural hazards (such as earthquakes, landslides, floods, tsunamis, fires) has dramatically increased and adversely affected modern and past human buildings including outstanding cultural properties and UNESCO heritage sites. Research about protection/monitoring of cultural heritage is crucial to preserve our cultural properties and (with them also) our history and identity. This paper is focused on the use of the open-source Google Earth Engine tool herein used to analyze flood and fire events which affected the area of Metaponto (southern Italy), near the homonymous Greek-Roman archaeological site. The use of the Google Earth Engine has allowed the supervised and unsupervised classification of areas affected by flooding (2013–2020) and fire (2017) in the past years, obtaining remarkable results and useful information for setting up strategies to mitigate damage and support the preservation of areas and landscape rich in cultural and natural heritage
Ground-based, aerial and satellite remote sensing to investigate archaeological and palaeoenvironmental featrures: the study case of Tavoliere (Apulia, Italy)
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