1,721,082 research outputs found
Detection of archaeological crop marks by using satellite QuickBird multispectral imagery
Full text linkThe capability of satellite QuickBird imagery for the identification of archaeological crop marks is herein presented and discussed for two test sites located in the South of Italy. The selected sites, dating back to Middle Ages, were buried under surfaces covered by herbaceous plants characterized by a different phenological status (dry/green) when the satellite data were acquired.
The methodological approach adopted for the enhancement and extraction of crop marks is mainly based on the use of data fusion and edge detection algorithm. The main remarkable differences found for the two archaeological sites can be suitably linked to the different state of vegetation that caused a different spectral response. In particular, near infrared (NIR) spectral channel was able to better enhance crop marks observed for dry vegetation; whereas, Normalized Difference Vegetation Index (NDVI) was found to be more capable to better enhance crop marks observed for green vegetation
On the Reuse of Multiscale LiDAR Data to Investigate the Resilience in the Late Medieval Time: the Case Study of Basilicata in South of Italy
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Quantifying urban sprawl with spatial autocorrelation techniques using multi-temporal satellite data
No full textThis study deals with the use of satellite TM multi-temporal data coupled with statistical analyses to quantitatively estimate urban expansion and soil consumption for small towns in southern Italy. The investigated area is close to Bari and was selected because highly representative for Italian urban areas. To cope with the fact that small changes have to be captured and extracted from TM multi-temporal data sets, we adopted the use of spectral indices to emphasize occurring changes, and geospatial data analysis to reveal spatial patterns. Analyses have been carried out using global and local spatial autocorrelation, applied to multi-date NASA Landsat images acquired in 1999 and 2009 and available free of charge. Moreover, in this paper each step of data processing has been carried out using free or open source software tools, such as, operating system (Linux Ubuntu), GIS software (GRASS GIS and Quantum GIS) and software for statistical analysis of data (R). This aspect is very important, since it puts no limits and allows everybody to carry out spatial analyses on remote sensing data. This approach can be very useful to assess and map land cover change and soil degradation, even for small urbanized areas, as in the case of Italy, where recently an increasing number of devastating flash floods have been recorded. These events have been mainly linked to urban expansion and soil consumption and have caused loss of human lives along with enormous damages to urban settlements, bridges, roads, agricultural activities, etc. In these cases, remote sensing can provide reliable operational low cost tools to assess, quantify and map risk areas
Evaluation of urban sprawl from space using open source technologies
No full textUp to nowadays, satellite data have become increasingly available, thus offering a low cost or even free of charge unique tool, with a great potential for quantitative assessment of urban expansion and urban sprawl, as well as for monitoring of land use changes and soil consumption. This growing observational capacity has also highlighted the need for research efforts aimed at exploring the potential offered by data processing methods and algorithms, in order to exploit as much as possible this invaluable space-based data source.
The work herein presented concerns an application study on the process of urban sprawl conducted with the use of satellite ASTER data. The selected test site is highly significant, being it a coastal zone (with the presence of sand and rocks) characterized by a fragmented ecosystem and small towns, with an increasing rate of urbanization and soil consumption. In order to produce synthetic maps of urban areas, ASTER images were classified using two automatic classifiers, Maximum Likelihood (MLC) and Support Vector Machines (SVMs) applied by changing setting parameters, with the aim to compare their respective performances in terms of robustness, speed and accuracy. All process steps have been developed integrating Geographical Information System and Remote Sensing, and adopting free and open source software.
Results pointed out that the SVM classifier with RBF kernel was generally the best choice (with accuracy higher than 90%) among all the configurations compared, and the use of multiple bands globally improves classification. One of the critical elements found in this case study is given by the presence of sand and sand mixed with rocks. The use of different configurations for the SVMs, i.e. different kernels and values of the setting parameters, allowed us to calibrate the classifier also to cope with a specific need, as in our case, to achieve a reliable discrimination of sand from urban area
Multitemporal 2016-2018 Sentinel-2 Data Enhancement for Landscape Archaeology: The Case Study of the Foggia Province, Southern Italy
No full textThis paper is focused on the use of satellite Sentinel-2 data for assessing their capability in the identification of archaeological buried remains. We selected the “Tavoliere delle Puglie” (Foggia, Italy) as a test area because it is characterized by a long human frequentation and is very rich in archaeological remains. The investigations were performed using multi-temporal Sentinel-2 data and spectral indices, commonly used in satellite-based archaeology, and herein analyzed in known archaeological areas to capture the spectral signatures of soil and crop marks and characterize their temporal behavior using Time Series Analysis and Spectral Un-mixing. Tasseled Cap Transformation and Principal Component Analysis have been also adopted to enhance archaeological features. Results from investigations were compared with independent data sources and enabled us to (i) characterize the spectral signatures of soil and crop marks, (ii) assess the performance of the diverse spectral channels and indices, and (iii) identify the best period of the year to capture the archaeological proxy indicators. Additional very important results of our investigations were (i) the discovery of unknown archaeological areas and (ii) the setup of a database of archaeological features devised ad hoc to characterize and categorize the diverse typologies of archaeological remains detected using Sentinel-2 Data
Big Earth Data for Cultural Heritage in the Copernicus Era
Full text linkDigital 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
Towards an operative use of remote sensing for exploring the past using satellite data: The case study of Hierapolis (Turkey)
Full text linkThis paper is focused on the presentation and discussion of an object oriented approach, applied to the Hierapolis
(Turkey) site, to automatically detect the subtle features linked to buried archaeological remains. The data processing
is applied twice: (i) first, globally at the whole image and, (ii) second, at the significant subsets identified
by global analysis, in order to refine the previously obtained categorization. Object oriented approaches are usually
based on two main steps: i) first the segmentation, ii) then the classification. Herein, we first performed the
unsupervised classification step and, then, the segmentation. This choice is given by the specificity of archaeological
issue, in particular: (i) the subtle features/targets to be identified are partially or totally unknown and characterized
by a very small spectral separability from the background, and therefore (ii) the discrimination
between archaeological class and substrates likely suffers significant confusion. To cope with these issues, the
first step is based on an unsupervised classification, which provides a first ‘rough’ categorization of pixels; the
second step, based on the segmentation, enables us to extract the geometric shape, and, in turn, to only categorize
as archaeological class those pixels belonging to geometrically (rectangular and linear) shaped clusters. Outputs
from this classification identify rectangular and linear features of archaeological interest whose size suggested
that they may be a farm and some sectors of an aqueduct, respectively. Results from satellite based analysis
were successfully evaluated by georadar and geomagnetic prospection along with field survey. From georadar
and geomagnetic prospection we were able i) to confirm the presence of buried remains and ii) to detail and
characterize these archaeological features at the subsoil level as well as to define the local stratigraphy. From
field surveywe dated the detected buried remains to a period spanning from Imperial Roman to early Byzantine
historical times
Assessing Fire Severity in Semiarid Environments with the DNBR and RDNBR Indices
Full text linkFil: Ghermandi, Luciana. Laboratorio Ecotono, Instituto Nacional de Investigaciones en Biodiversidad y Medioambiente (CONICET - UNCo); Argentina.Fil: Lanorte, Antonio. CNR-IMAA; Italia.Fil: Oddi, Facundo J. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.Fil: Lasaponara, Rosa. CNR-IMAA; Italia.Fil: Oddi, Facundo J. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.Available remote sensing historical Landsat TM images allow identifying of first order effects of
wildfires also in huge and inaccessible regions. In this paper the usefulness of the best known satellitederived
severity indices was tested on a large wildfire occurred in January 1999 in a steppe of
Northwestern Patagonia. The main objective of the work was to analyze and compare the behavior of
dNBR and RdNBR in their ability to discriminate the degrees of fire severity in semiarid ecosystems
principally dominated by herbaceous vegetation. For this purpose the values of the two indexes were
compared in all vegetation communities (shrubl and, meadow, grassland and forestation). To interpret the
results, we considered the variability of the principal factors that influence the fire severity, as fire intensity,
fire duration and vegetation susceptibility to fire. The analysis showed that the interaction between fire and
vegetation changes the fire effects because the vegetation parameter as fuel load, moisture content,
species composition, horizontal continuity and the topography affect the fire behavior and then the fire
severity. Furthermore the results suggest that dNBR and RdNBR provide substantially different
information respectively related to the effects on soil and vegetation. This work is an important
contribution to the utilization of fire severity indexes in ecosystems dominated by herbaceous species that
change more subtly the post-fire biomass than ecosystems dominated by woody species.true
Claustrum interius et exterius preparavit. Nuovi dati e nuove ipotesi sull’impianto architettonico di San Vincenzo al Volturno fra IX e XI secolo alla luce di recenti indagini diagnostiche e archeologiche (2013-2019)
No full textNell'ambito di un contributo che illustra i risultati delle ricerche archeologiche nel chiostro di San Vincenzo al Volturno, e in particolare le fasi di IX-XI secolo, la parte a firma di Daniele Ferraiuolo affronta l'analisi di un'olla in ceramica con incisioni e avanza alcune proposte sulla sua datazione e destinazione d'uso
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