HISTORY, MEMORY AND GEOGRAPHY - AN HISTORICAL GIS ON THE OPERATION OF THE ITALIAN ARMY DURING THE RUSSIAN CAMPAIGN (1941-1943)

Attraverso l’analisi di documentazione testuale e cartografica, è stata realizzata una ricostruzione dinamica degli eventi legati alla partecipazione dell’Italia all’invasione nazista della Russia. Il progetto è stato realizzato utilizzando la tecnologia GIS, che ha consentito di integrare dati storici e geografici fornendo una modalità innovativa per la visualizzazione e l’interrogazione dei dati. È stato possibile stratificare i dati raccolti in una serie di livelli informativi, ricreando e rileggendo gli eventi storici. Una volta completato lo sviluppo del GIS è stato realizzato un webGIS per la consultazione online dei risultati del progetto.Through the analysis of documents and cartography, a dynamic reconstruction of historical events occurred during the participation of the Italian Army to the Nazi’s invasion of Russia was performed. The goal was reached using Geographic Information Systems (GIS) that allow to integrate geographic and historical data providing a new way for the visualization and querying of locations and shapes related to data. Through GIS, it is possible to “stratify” data collected in information levels and recreate and “re-read” historical events. After the development of the GIS, an online GIS was developed as an interface for consulting information via web

Spectroradiometric Laboratory Measures on Asphalt Concrete: Preliminary Results

AbstractThis paper presents the preliminary results of a project concerning the use of spectroradiometric measurements for the characterization of aggregates and asphalts mixtures commonly used for road paving.Radiometrical measurements, in the wavelength range between 350-2500nm, were performed on selected samples with different compositional characteristics; the relationships between spectral signatures and different bituminous mixtures samples were analyzed.The results suggest that spectroradiometrics analyses can be used to establish new efficient and fast road classification procedures to support activities of pavement management systems and interpretation of remote sensed images

Integration of Field and Laboratory Spectral Data with Multi-Resolution Remote Sensed Imagery for Asphalt Surface Differentiation

The ability to classify asphalt surfaces is an important goal for the selection of suitable non-variant targets as pseudo-invariant targets during the calibration/validation of remotely-sensed images. In addition, the possibility to recognize different types of asphalt surfaces on the images can help optimize road network management. This paper presents a multi-resolution study to improve asphalt surface differentiation using field spectroradiometric data, laboratory analysis and remote sensing imagery. Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) airborne data and multispectral images, such as Quickbird and Ikonos, were used. From scatter plots obtained by field data using λ = 460 and 740 nm, referring to MIVIS Bands 2 and 16 and Quickbird and Ikonos Bands 1 and 4, pixels corresponding to asphalt covering were identified, and the slope of their interpolation lines, assumed as asphalt lines, was calculated. These slopes, used as threshold values in the Spectral Angle Mapper (SAM) classifier, obtained an overall accuracy of 95% for Ikonos, 98% for Quickbird and 93% for MIVIS. Laboratory investigations confirm the existence of the asphalt line also for new asphalts, too

Radiometric investigation of different snow covers in Svalbard

This paper examines the relationship between reflectance and physical characteristics of the snow cover in the Arctic. Field data were acquired for different snow and ice surfaces during a survey carried out at Ny-Ålesund, Svalbard, in spring 1998. In each measurement reflectance in the spectral range 350 - 2500 nm, snow data (including temperature, grain size and shape, density and water content), surface layer morphology, and vertical profile of the snow pack were recorded detailed analysis of reflectance based on the physical was performed. Field reflectance data were also re-sampled at the spectral intervals of Landsat TM to compare the ability of identifying different snow targets at discrete wavelength intervals. This analysis shows that reliable data on snow structure and thickness are necessary to understand albedo changes of the snow surfaces

NDVI Analysis for Monitoring Land-Cover Evolution on Selected Deglaciated Areas in the Gran Paradiso Group (Italian Western Alps)

The ongoing climate warming is affecting high-elevation areas, reducing the extent and the duration of glacier and snow covers, driving a widespread greening effect on the Alpine region. The impact assessment requires therefore the integration of the geomorphological context with altitudinal and ecological features of the study areas. The proposed approach introduces chronologically-constrained zones as geomorphological evidence for selecting deglaciated areas in the alpine and non-alpine belts. In the present study, the protected and low-anthropic-impacted areas of the Gran Paradiso Group (Italian Western Alps) were analysed using Landsat NDVI time series (1984–2022 CE). The obtained results highlighted a progressive greening even at a higher altitude, albeit not ubiquitous. The detected NDVI trends showed, moreover, how the local factors trigger the greening in low-elevation areas. Spectral reflectance showed a general decrease over time, evidencing the progressive colonisation of recently deglaciated surfaces. The results improved the discrimination between different greening rates in the deglaciated areas of the Alpine regions. The geomorphological-driven approach showed significant potential to support the comprehension of these processes, especially for fast-changing areas such as the high mountain regions

Spectral curves of surface reflectance in some antarctic regions

Four surface reflectance models of solar radiation were determined by examining several sets of field measurements taken for clear-sky conditions at various sites in Antarctica. Each model consists of the mean spectral curve of surface reflectance in the 0.25–2.7 μm wavelength range and of the dependence curve of total albedo on the solar elevation angle h, within the range from 5◦ to 55◦. The TNB (Terra Nova Bay) model refers to a rocky terrain where granites are predominant; the NIS (Nansen Ice Sheet) model to a glacier surface made uneven by sastrugi and streaked by irregular fractures; the HAP (High Altitude Plateau) model to a flat ice surface covered by fresh snow and scored by light sastrugi; and the RIS (Ross Ice Shelf) model to an area covered by the sea ice pack presenting many discontinuities in the reflectance features, due to melt water lakes, puddles, refrozen ice and snow pots. The reflectance curve obtained for the TNB model presents gradually increasing values as wavelength increases through the visible spectral range and almost constant values at infrared wavelengths, giving a total albedo value equal to 0.264 at h = 30◦, which increases by about 80% through the lower range of h and decreases by 12% through the upper range. The reflectance curves of the NIS, HAP and RIS models are all peaked at visible wavelengths and exhibit decreasing values throughout the infrared spectral range, giving values of total albedo equal to 0.464, 0.738 and 0.426 at h = 30◦, respectively. These values were estimated to increase by 8–14% as h decreases from 30◦ to 5◦ and to decrease by 2–4% only as h increases from 30◦ to 55◦

Toward a Multidisciplinary Strategy for the Classification and Reuse of Iron and Manganese Mining Wastes

The aim of this paper is to evaluate an integrated multidisciplinary strategy for the characterization of mining waste, their possible recycling and reuse. The use of Fe-Mn rich wastes in arsenic removal and phosphorus recovery from water and the phytoextraction potential of metals and their possible recovery from biomass are evaluated

Overview: Integrative and Comprehensive Understanding on Polar Environments (iCUPE) – concept and initial results

The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project “iCUPE – integrative and Comprehensive Understanding on Polar Environments” to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining in situ observations, satellite remote sensing Earth observations (EOs), and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns, and satellites to deliver data products, metrics, and indicators to stakeholders concerning the environmental status, availability, and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and the provision of novel data in atmospheric pollution, local sources and transboundary transport, the characterization of arctic surfaces and their changes, an assessment of the concentrations and impacts of heavy metals and persistent organic pollutants and their cycling, the quantification of emissions from natural resource extraction, and the validation and optimization of satellite Earth observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of the integration of comprehensive in situ observations, satellite remote sensing, and multi-scale modeling in the Arctic context

Overview : Integrative and Comprehensive Understanding on Polar Environments (iCUPE) - concept and initial results

The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project "iCUPE - integrative and Comprehensive Understanding on Polar Environments" to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining in situ observations, satellite remote sensing Earth observations (EOs), and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns, and satellites to deliver data products, metrics, and indicators to stakeholders concerning the environmental status, availability, and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and the provision of novel data in atmospheric pollution, local sources and transboundary transport, the characterization of arctic surfaces and their changes, an assessment of the concentrations and impacts of heavy metals and persistent organic pollutants and their cycling, the quantification of emissions from natural resource extraction, and the validation and optimization of satellite Earth observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of the integration of comprehensive in situ observations, satellite remote sensing, and multi-scale modeling in the Arctic context.Peer reviewe