A5082135242- Remote-Sensing Image Classification
- Remote Sensing in Agriculture
- Geochemistry and Geologic Mapping
- Remote Sensing and Land Use
- Aquatic Ecosystems and Biodiversity
- Calibration and Measurement Techniques
- Water Quality Monitoring and Analysis
- Soil Geostatistics and Mapping
- Water Quality Monitoring Technologies
- Infrared Target Detection Methodologies
- 3D Surveying and Cultural Heritage
- Archaeological Research and Protection
- Aquatic Ecosystems and Phytoplankton Dynamics
- Advanced Image Fusion Techniques
- Marine and coastal ecosystems
- Spectroscopy and Chemometric Analyses
- Environmental Changes in China
- Urban Heat Island Mitigation
- Land Use and Ecosystem Services
- Industrial Vision Systems and Defect Detection
- Smart Agriculture and AI
- Satellite Image Processing and Photogrammetry
- Maritime and Coastal Archaeology
- Karst Systems and Hydrogeology
- Ancient Mediterranean Archaeology and History
National Research Council
2010-2024
National Research Council - Institute of Methodologies for Environmental Analysis
2012-2024
Italian Resuscitation Council
2019-2020
IAC (United States)
2013
Istituto per le Applicazioni del Calcolo Mauro Picone
2013
Institute of Atmospheric Pollution Research
2007-2011
National Academies of Sciences, Engineering, and Medicine
2008-2009
The main objectives of the PRISMA (Hyperspectral Precursor Application Mission) mission are: implementation an Earth Observation pre-operative payload, in-orbit demonstration and qualification Italian state-of-the-art hyperspectral/panchromatic technology validation end-to-end data processing system able to support development new applications based on high spectral resolution images. aim paper is provide overview by describing current status program giving a brief outline work done till now...
Soil moisture hampers the estimation of soil variables such as clay content from remote and proximal sensing data, reducing strength relevant spectral absorption features. In present study, two different strategies have been evaluated for their ability to minimize influence on by using spectra acquired in a laboratory simulating satellite hyperspectral data. Simulated data were obtained according characteristics forthcoming imager board Italian PRISMA mission. The datasets split into four...
This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is evaluate added value hyperspectral in mapping a complex context. In this we used: (a) ALI and Hyperion satellite data, (b) LANDSAT ETM+ (c) MIVIS airborne data (d) high spatial resolution IKONOS imagery as reference. Venice city center shows therefore was chosen for testing spectral characteristics tissue. For purpose, object-oriented...
In March 2019, the PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral satellite was launched by Italian Space Agency (ASI), and it is currently operational on a global basis. The mission includes imager working in 400–2500 nm spectral range with 237 bands panchromatic (PAN) camera (400–750 nm). This paper presents an evaluation of top-of-atmosphere (TOA) L1 products using different situ measurements acquired over fragmented rural area Southern Italy (Pignola) between...
Claim management is a critical process for insurance companies, requiring fairness, transparency, and efficiency to maintain policyholder trust minimize financial impact. In our previous work, we introduced Insoore AI, an insurtech solution leveraging deep learning-based computer vision automate car damage recognition localization from user-provided pictures. While this approach demonstrated the potential of AI in claims management, it faced limitations terms performance computational due...
An experimental method to select the number of principal components in minimum noise fraction (MNF) is proposed process images measured by imagery sensors onboard aircraft or satellites. The based on an measurement spectrometers dark conditions from which structure can be estimated. To represent typical land and atmospheric variability, a significative data set synthetic noise-free real Multispectral Infrared Visible Imaging Spectrometer built. this purpose, subset spectra selected within...
Despite its high importance for crop yield prediction and monitoring, early-season mapping is severely hampered by the absence of timely ground truth. To cope with this issue, study aims at evaluating capability PRISMA hyperspectral satellite images compared Sentinel-2 multispectral imagery to produce early- in-season maps using consolidated machine deep learning algorithms. Results show that accuracy type classification meaningfully poor (14% in overall (OA)). The 1D-CNN algorithm, 89%,...
The SAP4PRISMA is a four year research project which aims at developing algorithms and products for the future PRISMA mission. started on May 2010 now entering his full activities as "PRISMA like" data set has been defined test areas were selected. paper describes main objectives realized in first 9 months of project.
The SAP4PRISMA project research activities aimed at supporting the Italian hyperspectral PRISMA mission by developing preliminary processing chains suitable for to obtain high level data products agriculture, land degradation, natural and human hazards.
Soil moisture (SM) plays a fundamental role in the terrestrial water cycle and agriculture, with key applications such as monitoring of crop growing hydrogeological management. In this study, calibration procedure was applied to estimate SM based on integration situ airborne thermal remote sensing data. To aim, April 2018, two campaigns were carried out TASI-600 multispectral sensor Petacciato (Molise, Italy) area. Simultaneously, soil samples collected different agricultural fields study...
The enhanced spectral and spatial resolutions of the remote sensors have increased need for highly performing preprocessing procedures. In this paper, a comprehensive approach, which simultaneously performs atmospheric topographic corrections includes second order such as adjacency effects, was presented. method, developed under assumption Lambertian surfaces, is physically based uses MODTRAN 4 radiative transfer model. use estimates quantities widely discussed in paper impact on sensing...
Claims management is a complex process through which an insurance company or responsible entity addresses and handles compensation requests from policyholders who have suffered damage losses. This entails several stages, including the notification of claim, assessment, settlement compensation, and, if necessary, dispute resolution. Fair, transparent timely claims crucial for maintaining policyholders’ trust while also limiting financial impact on insurer. Technological innovations, such as...
Anomalous pixel responses often seriously affect remote sensing applications, especially in the thermal spectral range. In this paper, a new method to identify and correct anomalous is presented. The was specifically developed handle with hyperspectral data based on statistical analysis of gray scale RX detector (RXD) image applied focal plane space rather than space. An iterative thresholding pixels automatic modality tuned. Moreover, band depth-based properly restore lost information...
This paper studies change detection of LWIR (Long Wave Infrared) hyperspectral imagery. Goal is to improve target acquisition and situation awareness in urban areas with respect conventional techniques. Hyperspectral broadband high-spatial-resolution data were collected during the DUCAS trials Zeebrugge, Belgium, June 2011. acquired using ITRES Thermal Airborne Spectrographic Imager TASI-600 that operates spectral range 8.0-11.5 μm (32 band configuration). Broadband two aeroplanemounted...
ImaACor is a tool for the simultaneous correction of remotely sensed data from atmospheric and topographic effects, including second-order corrections, such as adjacency effects. The implemented approach physically based uses MODTRAN computation main radiometric quantities. A user-friendly, comprehensive, exhaustive graphic interface allows user to choose different levels. various panels allow one set all parameters correctly characterize atmosphere define acquisition illumination...
Over the past decades, remote sensing satellite sensors have significantly increased their performance and, at same time, differed in characteristics. Therefore, making data repeatable over time and uniform with respect to different platforms has become one of most challenging issues obtain a representation intrinsic characteristics observed target. In this context, atmospheric correction role cleaning signal from unwanted contributions moving sensor radiance quantity more closely related...
The paper presents a comparison between an empirical algorithm and physics based model for the assessment of water compound concentrations by remote sensing hyperspectral data. At purpose series in situ measurements were carried out monthly, from June to October 2005, spectrally characterize "Sacca di Goro" (Italy) at spatial (horizontal vertical) temporal (daily seasonal) scales. results obtained application two different methods acquired data showed that appreciable improvement is...