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    Personal information
    Contact information
    Candidate Profile
     Date Submitted:23-04-2016
     Last Modified:01-03-2017 (08:19)
    Job information
     Current job:Senior scientist
     Employment Term:Either
     Job location:Europe only
     Date available:immediately
     Industry:Consulting/Engineering Services
     Keywords• Remote sensing. • Computer vision. • Human vision. • Machine learning. • Artificial intelligence. • Software engineering. • Geographic information science. • Environmental science

    Scientific Disciplines of Interest

    •         Remote sensing.

    •         Computer vision.

    •         Human vision.

    •         Machine learning.

    •         Artificial intelligence.

    •         Software engineering.

    •         Geographic information science.

    •         Environmental science.



    Research Interests


    After more than ten years from the launch of the Global Earth Observation System of Systems (GEOSS) implementation plan for years 2005-2015, no EO data-derived Level 2 prototype product has ever been generated systematically at the ground segment. By definition, an EO data-derived Level 2 product encompasses a multi-spectral (MS) image corrected for atmospheric, adjacency and topographic effects into surface reflectance (SURF) values, in addition to a scene classification map (SCM), such as vegetation/non-vegetation and terrestrial/aquatic layers in the initial Dichotomous Phase of the Food and Agriculture Organization of the United Nations (FAO) - Land Cover Classification System (LCCS) taxonomy, in addition to cloud and cloud-shadow quality layers. My research activity is mainly focused on the development of automatic (requiring no user’s interaction) hybrid (combined deductive/top-down/physical model-based and inductive/bottom-up/statistical model-based) spaceborne/airborne EO image understanding systems, capable of  delivering as output EO Level 2 products in operating mode, at coarse to fine spatial resolution and large spatial extent, from national to global coverage. Wherever possible these hybrid computer vision systems search for biological plausibility as a value added. The proposed hybrid EO image understanding system’s architecture consists of three stages provided with a feedback connection. (I) A zero-stage MS image pre-processing (data enhancement) module, where radiometric calibration of digital numbers into top-of-atmosphere reflectance or SURF values is mandatory. (II) A pre-attentive vision module, comprising a physical model-based (deductive, prior knowledge-based) fully automatic, multi-sensor, multi-resolution, application-independent spectral decision-tree preliminary classification and segmentation first stage in operating mode, called Satellite Image Automatic Mapper™ (SIAM™, refer to the web page: (III) An attentive vision module. It comprises two phases. (A) A hybrid stratified (layered, driven-by-knowledge) FAO-LCCS Dichotomous Phase, plus thematic classes clouds and cloud shadows, in agreement with the EO Level 2 product requirements. The three FAO-LCCS Dichotomous Phase levels are: (a) vegetation/non-vegetation, (b) terrestrial/aquatic, (c) managed/natural or semi-natural. The eight FAO-LCCS Dichotomous land cover types are: (1) Cultivated and Managed Terrestrial (non-aquatic) Non-vegetated Areas. (2) Natural and Semi-Natural Terrestrial Vegetation. (3) Cultivated Aquatic or Regularly Flooded Areas. (4) Natural and Semi-Natural Aquatic or Regularly Flooded Vegetation. (5) Artificial Surfaces and Associated Areas. (6) Bare Areas. (7) Artificial Waterbodies, Snow and Ice. (8) Natural Waterbodies, Snow and Ice.  (B) An (infinite) battery of second-stage context-sensitive, application- and sensor-specific stratified (driven-by-first-stage-knowledge) feature extractors and one-class land cover classification modules, equivalent to the FAO-LCCS Modular Hierarchical Phase. (IV) A feedback mechanism between the pre-attentive vision first stage and the remote sensing image pre-processing stage zero. Existing applications of the proposed feedback system, employing SIAM™ as its pre-attentive vision first stage, to remote sensing image pre-processing (enhancement) problems, which are inherently ill-posed, i.e., equivalent to chicken-and-egg dilemma requiring prior knowledge in addition to data to become better posed for numerical treatment, are: (a) stratified atmospheric correction, (b) stratified bidirectional reflectance distribution function (BRDF) effects correction, (c) automatic stratified image topographic correction, (d) automatic stratified image mosaic enhancement, (e) automatic stratified image co-registration, etc.

    Existing applications of the proposed feedback system, employing SIAM™ as its pre-attentive vision first stage, to second-stage (high-level) classification problems include automatic burned area detection in time-series of 30 m resolution Landsat images and 250 m resolution MODIS images. The proposed hybrid feedback system for remote sensing image understanding also includes landscape fragmentation/connectivity analysis tools to be employed as input by ecosystem and land use modeling systems. In practice, this hybrid feedback spaceborne/airborne image understanding system estimates categorical and continuous variables from sensory data alternately and iteratively.

    A recent development of the SIAM™ deductive pre-classifier, called RGB Image Automatic Mapper™ (RGBIAM™), is input with a non-calibrated Red-Green-Blue image, such as those typically acquired by consumer-level color cameras mounted in smartphones and on drones, pre-processed with an original histogram stretching algorithm accomplishing color constancy. In common practice, the same SIAM™/RGBIAM™ deductive pre-classification technology is now available for mapping any multi-spectral image, whether or not radiometrically calibrated, either spaceborne, airborne or acquired at ground level, into an a priori dictionary of discrete and finite color names. In the output multi-level color map, whose legend is a prior dictionary of color names, each connected set of pixels featuring the same color label is a texture element (texel), recently called superpixel in the computer vision literature. Texel detection was called pre-attentional vision raw primal sketch by Marr (Vision, 1982). Perceptual spatial grouping of texels, known as texture segmentation, was called pre-attentional vision full primal sketch by Marr.

    With regard to the assessment and comparison of remote sensing data-derived products, in recent years I have developed original protocols for statistically significant and statistically consistent quality assessment of: (i) multi-spectral image pan-sharpening algorithms and (ii) thematic maps generated from very high resolution spaceborne/airborne images. Additional research interests encompass machine learning, with special emphasis on self-organizing topology-preserving inductive-data-learning networks capable of modeling non-stationary random processes. My current research interest is focused on developing second-stage stratified (driven-by-knowledge) spatiotemporal feature extractors (e.g., texture detectors) and application- and sensor-specific classification modules (e.g., cloud and cloud shadow detectors) in an automatic hybrid feedback Eo image understanding system implementation employing the SIAM™ deductive pre-classifier as its pre-attentive vision first stage.



    Teaching interests


    I am most interested to teach courses focused on multi-disciplinary concepts where the use of multimedia, numerical examples, case histories, personal anecdotes and real-life examples is recommended to illustrate concepts. Connections with other classes/disciplines should be highlighted whenever possible. I am committed to the use of assessment techniques to improve teaching and learning. I enjoy to supervise Ph.D. and M.S. students and/or participate to their dissertation committees.



    Professional references


    Prof. and Chair Christophere Justice, 2181A LeFrak Hall, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA. Email: cjustice(at)

    Prof. Luigi Boschetti, College of Natural Resources, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844-4264, USA. Email: luigi(at)

    Dr. Alessandro Annoni, Head of the Spatial Data Infrastructures Unit, EC Joint Research Center, Via Fermi, Ispra (Varese), Italy. Email: alessandro.annoni(at)

    Prof. Paolo Pavan, Engineering Department, University of Modena and Reggio Emilia, Italy. Email: paolo.pavan(at)

    Prof. Guido D’Urso, Department of Agricultural and Food Sciences, University of Naples “Federico II”, Via Università 100; 80055 PORTICI (Napoli), Italy. Email: guido.durso(at)

    Dr. Virginia Puzzolo, European Commission Research Executive Agency, Covent Garden Place Rogier, 16 1049 Brussels Belgium, Email: virginia.puzzolo(at)

    Prof. Stefan Lang, Head Integrated Spatial Analysis (ISA), Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Schillerstr. 30, Building 15, 3rd Floor, 5020 Salzburg, Austria, Email: stefan.lang(at)

    Prof. Thomas Blaschke, Deputy Director of the Department of Geoinformatics - Z_GIS, Integrated Spatial Analysis (ISA), University of Salzburg, Schillerstr. 30, 5020 Salzburg, Austria, Email: Thomas.Blaschke(at)



    Education and training


    1 March 2014 – 28 Feb. 2017

    Ph.D. in Agriculture and Agribusiness (Dottorato di Ricerca in Scienze Agrarie ed Agroalimentari, XXIX Ciclo, official starting date: 1 March 2014University of Naples “Federico II”, Department of Agricultural and Food Sciences (Dipartimento di Scienze Agrarie ed Agroalimentari). Proposed title of the Ph.D. research: Process and outcome innovations in Earth observation spaceborne/airborne image understanding for vegetation monitoring

    May 2000 - May 2002

    Post-doctoral fellowship, European Commission Joint Research Center (JRC), Ispra (Varese), Italy. Supervisor: G. De Grandi, JRC-IES-GEM.

    Oct. 1997 -  June 1999

    Post-doctoral fellowship, International Computer Science Institute (ICSI), Berkeley, California, USA. Supervisor: Prof. J. Feldman, ICSI and UC Berkeley.

    June 1993 – Feb. 1994

    1st Level Master in Software Engineering, Universita` di Padova and Purdue University, West Lafayette, Indiana, USA.

    Date: June 14, 1994.

    Feb. 1989

    Laurea degree (M.S.) in Electronic Engineering, specialization: computer science, Università degli Studi di Bologna, Italy. Final degree:  100/100.

    Title of the Laurea thesis (in italian): “Segmentation and classification of high resolution satellite images”. Supervisor: Prof. F. Bonfatti, Univ. of Bologna, Italy.

    Date: Feb. 22, 1989.

    July 1982

    Italian high school diploma in Electronics, Istituto Tecnico Industriale E. Fermi, Modena, Italy. Votazione 60/60.

    July 1981

    American high school diploma, Rex Putnam High School, Milwaukie, Oregon, USA.



    Competitive selection procedures


    •         May 2000. European Commission, procedure COM/R/A/01/2000 for selection of temporary agents (category A5), admitted to the reserve list in sector: Space applications and earth observation.

    •         Dec. 2013. German Academic Exchange Service (DAAD), Senior Scientist 1-month Fellowship No. 178: Advances in automatic real-time preclassification and segmentation, to be spent at the German Aerospace Center (DLR), Institute Remote Sensing Technology Institute Photogrammetry and Image Analysis, Oberpfaffenhofen, Weßling, Germany.

    •         Feb. 2014. 1st ranked in the competitive selection procedure for a Ph.D. position in Agriculture and Agribusiness, Universita’ degli Studi di Napoli Federico II, Department of Agricultural and Food Sciences.

    •         Dec. 2014, European Commission FP7 project (2010-2015) Experimentation in Ecosystem Research (ExpeER), Transnational Access (TNA) proposal, TNA site: Ben Gurion University of the Negev, Sde Boker Campus 84990, Israel, Period: 5 Feb. 2015 – 8 March 2015. Title of the ExpeER project proposal: Prior Spectral Knowledge for Ecosystem Service Monitoring and Understanding (PriorSpecK4ECOS).




    Research experience


    March-Aug. 2016

    Visiting scientist, Computer Vision Center (CVC), Universidad Autonoma de Barcelona (UAB), Barcelona, Spain.

    Feb.-March 2015

    FP7-ExpeER project proposal, Ph.D. fellowship, Ben Gurion University of the Negev, Sde Boker Campus 84990, Israel.

    Feb. 2014

    German Academic Exchange Service (DAAD), Senior Scientist Fellowship, German Aerospace Center (DLR), Institute of Remote Sensing Technology, Oberpfaffenhofen, Postfach 11 16, 82230 Weßling, Germany.

    July 2013 – Oct. 2014, April 2015 – Jan. 2016

    Senior researcher, involved with spaceborne/airborne multi-spectral image calibration, enhancement, pre-classification and classification, under the supervision of Dr Stefan Lang, Head Integrated Spatial Analysis (ISA), Department of Geoinformatics – Z_GIS, University of Salzburg, Schillerstr. 30, Building 15, 3rd Floor, 5020 Salzburg, Austria. Funding projects: the Copernicus (former GMES) Initiative, FP7-Space project G-SEXTANT (Consolidation of a standardized portfolio of Earth Observation products and pre-operational services in the frame of pre-defined scenarios, like humanitarian crises), July-Oct. 2014; Austrian Research Promotion Agency (FFG)-ASAP11 project call, AutoSentinel2/3 project (Knowledge-based pre-classification of Sentinel-2/3 images for operational product generation and content-based image retrieval), ID 848009, Apr. 2015 – Jan. 2016.

    July 2013 – July 2015

    Adjunct Associate Professor at the Dept. of Geographical Sciences, Univ. of Maryland, College Park, MD 20740, USA.

    Sept. 2010 – June 2013

    Research Associate Professor at the Dept. of Geographical Sciences, Univ. of Maryland, College Park, MD 20740, USA, involved with the automatic classification of Landsat Web-Enabled Data set (WELD) at continental and global spatial extents, in the framework of the NASA Land-Cover and Land-Use Change (LCLUC) Program.

    Feb. 2005 - Feb. 2009

    Scientific officer at the European Commission Joint Research Centre (EC-JRC), Ispra (Varese), affiliated to the Spatial Data Infrastructures (SDI) unit of the Institute for Environment and Sustainability (IES). The research activity focused on the development of operational remote sensing image understanding systems for vegetation monitoring, cloud detection, flood detection, fire detection, urban area monitoring at either local (regional), continental or global scale.

    Aug. 2003 - Oct. 2004

    Research associate in pattern recognition and image understanding at the Institute of Intelligent Systems for Automation (ISSIA)-National Research Council (CNR), Bari, Italy (Assegno di ricerca, bando n. 0740013, financed by EU, project LEWIS: Landslide Early-Warning Integrated System, n. EVG1-CT-2001-00055).

    June 2002 – June 2003

    Research associate in image understanding at ISSIA-CNR, Bari, Italy (Development of context-sensitive neuro-fuzzy clustering algorithms for multi-source image analysis)

    May 2000 - May 2002

    Post-doctoral researcher at the European Commission Joint Research Centre (EC-JRC), Ispra (Varese), Italy, affiliated to the Global Vegetation Monitoring (GVM) unit of the Institute for Environment and Sustainability (IES). Title of the research activity: "Development and validation of algorithms for the automatic thematic information extraction from wide area radar maps of forest ecosystems."

    June '99 - Apr. 2000

    Research associate in pattern recognition at the Istituto di Scienze dell'Atmosfera e del Clima (ISAC)-CNR, Bologna, Italy (Collaborazione professionale esterna, Prot. N. 464/99) (Assegno di ricerca, Prot. n. 13/00/AR).

    Dec. '97 - Jun. '99.

    Post-doctoral researcher at International Computer Science Institute (ICSI), Berkeley, CA (USA), affiliated to the Artificial Intelligence group led by Prof. J. Feldman, ICSI and UC Berkeley. Title of the research activity: "Scatter-partitioning neural networks for image segmentation."

    Mar. '93 - Dec. '97.

    Research associate at Istituto per lo studio delle Metodologie Geofisiche Ambientali (IMGA)-CNR, Modena, Italy. Main interests are: low-level visual processing, with special regard to texture analysis and neural network applications to unsupervised data quantization and clustering (contracts: CEE/CNR EV5V CT94 0440, CEE/CNR MAS3 CT95 0015, CNR/ASI ARS 96 13).

    Oct. ’96.

    Participation to the course: Learning in Graphical Models, NATO Advanced Study Institute, Ettore Maiorana Centre, Erice, Italy, September 27-October 7, 1996.

    Jan. '91 - Mar. '93.

    Consultant to the European Space Agency (ESA)-ESRIN in Frascati (Rome), Italy, responsible of the quality assessment of commercial geographic information systems (GISs) and of the development of raster modules in vector-based GISs (e.g., System9).

    Jun. '89 - Jan. '91

    Military service: Lieutenant in the Technical Corp, Istituto Geografico Militare, Florence, Italy, responsible for the development of satellite image segmentation and classification algorithms to be integrated with GIS (MicroStation by Intergraph).

    Feb. '89 - Jun. '89.

    Consultant to CIOC-CNR, Bologna, Italy, responsible for the development of object-oriented geographic information representation models and for the assessment of Geographic Information Systems (MicroStation by Intergraph).



    Professional experience


    Jan. 2003 – Dec. 2003

    ·         Name and address of employer: Surface Inspection s.r.l., Formigine (Modena), Italy.

    ·         Industrial sector: automatic ceramic tile inspection.

    ·         Position held:consultant.

    ·         Main activities and responsibilities: development of a software prototype for the automated classification of textured images of ceramic tiles acquired by the Flawmaster automatic file inspection system.

    Jan. 1991 -  Jan. 1993


    ·         Name and address of employer: Advance Computer Systems S.p.A., Roma.

    ·         Industrial sector: services for the remote sensing industry and agencies.

    ·         Position held:project manager.

    ·         Main activities and responsibilities: development of a satellite image Acquisition Planning Support Package (APS).

    ·         Position held: consultant to the European Space Agency, (ESA-ESRIN), Frascati, Italy.

    ·         Main activities and responsibilities: assessment and comparison of commercial geographic information systems (GISs).

    Jan. 2009 – to date

    Founder of Baraldi Consultancy in Remote Sensing di Andrea Baraldi, Ditta Individuale, Via Gian Maria Barbieri 23, Modena 41124, Italy, P.IVA 02907681205.

    Feb. 2009 – Oct. 2009

    ·         Name and address of employer: Sarmap s.a., Purasca, Swizterland.

    ·         Industrial sector: Automatic remote sensing image understanding system development.

    ·         Position held:supervisor and chief scientist.

    ·         Main activities and responsibilities: development of an operational software for the automatic understanding of remote sensing optical imagery.



    Teaching experience


    June 2-3, 2014

    Workshop for Ph.D. and MS students – Hands on the Satellite Image Automatic Mapper™ software toolbox, In collaboration with Prof. Thomas Blaschke, Prof. Stefan Lang and Dr. Dirk Tiede, Department of Geoinformatics - Z_GIS, Integrated Spatial Analysis (ISA), University of Salzburg.

    March – May 2014

    Visiting professor, University of Modena and Reggio E., Italy, Academic year in Electronic Engineering: 2013-1014, Teaching course (30 hours + testing) for M.S. and Ph.D. students in “Advanced Electronic Systems: Neuromorphic Engineering - Adaptive oxide electronics (memristors) for fabricating devices to mimic human brain functionalities”.  Hosting professor: Prof. P. Pavan.

    Feb. 2011

    Teaching assistant in the Spring 2011 Geog778B course, titled "Remote Sensing for Global Carbon Monitoring," University of Maryland, Department of Geographical Sciences, Teaching Professor: Dr. L. Boschetti.

    Dec. 2003

    Teaching assistant in "Tecniche avanzate di elaborazione dei segnali," corso di Laurea in Ingegneria e Telecomunicazioni, academic year 2003-2004, first semester, Univ. di Trento, Teaching Professor: Prof. L. Bruzzone. Titles of the laboratory experience:

    §  Inductive machine learning from a finite set of unlabeled data.

    §  Image multi-scale analysis: the Gaussian-Laplacian pyramid decomposition, multi-scale batteries of Gabor filters, multi-spectral image panchromatic-sharpening.

    Dec. 2002

    Teaching assistant in "Tecniche avanzate di elaborazione dei segnali," corso di Laurea in Ingegneria e Telecomunicazioni, academic year 2002-2003, first semester, Univ. di Trento, Teaching Professor: Prof. L. Bruzzone. Titles of the laboratory experience:

    §  Inductive machine learning from a finite set of unlabeled data.

    §  Taxonomy of supervised and unsupervised inductive data learning algorithms.

    §  Assessment of alternative unsupervised inductive data learning algorithms for data quantization, data clustering, topologically correct mapping, entropy maximization. Estimated quality indexes are: Ease of use, Effectiveness (e.g., accuracy), Robustness to changes in input dataset, Robustness to changes in input parameters, Robustness to noisy data, Efficiency (e.g., computation time), Maintainability/scalability, Timeliness, Costs (e.g., in manpower, computer power, etc.).


    Participation in training (mentoring)

    Past/  Current Trainee

    Trainee Name


    Academic Department and Institution

    Mentoring Period and Activity

    Title of Research Project / Language

    Current Position of Past Trainees /
    Source of Support of Current Trainees


    Martin Sudmanns


    Dep. of Geoinformatics, Z-GIS, Univ. Salzburg, Austria

    2016-2019, co-supervision

    Earth observation Image-Content Extraction and Semantic Content-Based Image Retrieval / English

    Ph.D. program, Z-GIS


    Martin Sudmanns


    Dep. of Geoinformatics, Z-GIS, Univ. Salzburg, Austria

    2015-2016, co-supervision

    Content-Based Image and Information Retrieval / English

    Ph.D. program, Z-GIS


    Csillik Ovidiu


    Dep. of Geoinformatics, Z-GIS, Univ. Salzburg, Austria

    2016-2018, co-supervision

    Geons – domain-specific regionalization of optimized latent variables / English

    Ph.D. program, Z-GIS


    Joao Vitor Baldini Soares


    Dep. of Computer Science, Univ. of Maryland, College Park, MD, USA

    2011-2014, co-supervision

    Software library of planar shape descriptors / English

    Post-doc, UMD


    Francesca Despini


    Dep. of Sanitary and Environmental Engineering, Univ. of Modena and Reggio E., Italy

    2012-2014, co-supervision

    Protocol for quality assessment and comparison of algorithms for panchromatic sharpening of multi-spectral images  / English

    Post-doc, Unimore


    Moreno Carullo


    Dep. of Informatics, Univ. of Insubria, Varese, Italy

    2008-2011, co-supervision

    Web content mining with multi-source machine learning for intelligent web agents / English

    eXtreme Programming Coach at 7Pixel, Varese, Italy


    Mattia Stasolla


    Dep. of Electronics, Computer Science and Electrical Engineering, Univ. of Pavia, Italy

    2006-2008, co-supervision

    Characterization and monitoring of urban settlements by means of VHR remote sensing images / English

    Researcher, Telecommunications & Remote Sensing Laboratory

    Dep. of Electronics ,  Uni. of Pavia


    Moreno Carullo


    Dep. of Informatics, Univ. of Insubria, Varese, Italy

    2007, co-supervision

    Sviluppo di un algoritmo di apprendimento supervisionato basato su Radial Basis Function Networks / Italian



    Lisa Trollo


    Dep. of Telecommunication Engineering, Univ. of Trento, Italy

    2006, co-supervision

    Metodo innovative per la segmentazione automatic 3D: Applicazione ad immagini TAC cardiache / Italian



    Michele Grandi


    Dep. of Telecommunication Engineering, Univ. of Trento, Italy

    2003, co-supervision

    Classificazione di immagini telerilevate ad alta risoluzione geometrica mediante filtri di Gabor e Support Vector Machine / Italian



    Daniele Sevegnani


    Dep. of Telecommunication Engineering, Univ. of Trento, Italy

    2003, co-supervision

    Classificazione di immagini telerilevate ad elevate risoluzione geometrica mediante un approccio gerarchico e multilivello innovativo / Italian




    Participation in European, international and

    national programmes - Summary



    Project’s name and comments, if any

    European Union’s Projects


    European Space Agency (ESA)’s projects

    KEI, CARD, SPA, SOSI, SRoKEO, IIM-TS. These ESA projects started from the year 2008 to present and are either finished or ongoing. They are all based on the original remote sensing image understanding system software modules provided by A. Baraldi; a litigation about intellectual property right violation is currently ongoing between A. Baraldi and MEEO srl, an Italian private held company which is the principal investigator or a participant in these projects.

    Austrian Research Promotion Agency (FFG)

    ASAP11 project call (AutoSentinel2/3 project).




    Participation in European, international and

    national programmes: number of teams in the programme and budget obtained by the candidate’s team


    Institution of affiliation

    Project Name and Identifier

    Funded by


    Own amount / Budget

    Other partners


    (WP Leader)

    Landslide Early-Warning Integrated System (LEWIS), EVG1-CT-2001-00055



    € 190.00 / ...

    Univ. Bari (PI), Canada Centre of Remote Sensing (CCRS),  Univ. of Surrey, Silogic, Planetek, Altamira

    MEEO srl Italy (PI)

    Knowledge-centred Earth Observation (KEO) Extensions and Installations (KEI)



    € 196.241


    MEEO srl Italy (PI)

    Classification Application-services and Reference Datasets (CARD), Letter of Invitation n° RES-POE/2007/525/LG/cb



    € 265.720


    MEEO srl Italy (PI)

    Support by Pre-classification to Specific Applications (SPA), Letter of Invitation n° RES-POE/2008/497/EC/sp



    € 469.903


    MEEO srl Italy (WP Leader)

    Spatial Observation Services and Infrastructure (SOSI), Letter of Invitation  n° RES-POE/2008/488/LG/cb



    € 29.996 / ...

    Siemens Austria (PI)

    MEEO srl Italy (PI)

    Support to the RoKEO PECS project (SRoKEO), Letter of Invitation  n° RES-POE/2008/292/cb



    € 79.704 / ...

    Romanian Space Agency

    MEEO srl Italy (PI)

    Image Information Mining - Time Series (IIM-TS)



    € 13.576 / ...

    Sarmap SA

    Baraldi Consultancy in Remote Sensing (WP leader)

    BIOdiversity Multi-Source Monitoring System: from Space TO Species (BIO-SOS), FP7-SPACE-2010-1



    € 360.000 /...

    ISSIA-CNR (PI),  Alterra, IRD, Uni. of Bari, ATREE, Planetek, ICETA, Univ. Of Aberystwyth, ASI, Uni. of Milano-Bicocca

    Univ. Salzburg, Z-GIS (PI)

    ASAP11 project call, AutoSentinel2/3 project (Knowledge-based pre-classification of Sentinel-2/3 images for operational product generation and content-based image retrieval), ID 848009



    € 125.580




    Professional society activities


    Jan. 2001-May 2006

    Associate editor of the IEEE Transactions on Neural Networks journal.

    Sep. 2012

    Program Committee, Workshop at the GIScience conference, 18-20 September 2012, Columbus, Ohio: Geographic object based multi-scale analysis: Developing a methodological framework for GIScience.

    Sept. 28, 2015 (invited)

    European Commission - European Space Expo, Milan, Italy, 18 Sept. – 4 Oct. 2015: Food and Space. Andrea Baraldi, “Agricultural Applications of Airborne/Spaceborne Images – If You Don’t Measure It, You Can’t Improve It,” University of Salzburg and University of Naples Federico II.



    List of awards for work and publications


    Sept. 2015

    ·         Winner of the T-Systems Big Data Challenge of the Copernicus Masters 2015, with the project and feasibility study titled: “Satellite Image Automatic Mapper™ (SIAM™)-Through-Time (SIAMT2) for spaceborne/airborne multi-spectral image time-sequence classification in operating mode and content-based image database retrieval” (Project ID 150688)”.

    ·         Final project title: Final project title: D. Tiede, A. Baraldi, M. Sudmanns, M. Belgiu, and S. Lang, “ImageQuerying (IQ): Off-the-shelf Image Content Extraction & Querying Across Time and Space”, Oct. 20, 2015, German Federal Ministry of Transport and Digital Infrastructure, Invalidenstraße 444, 10115 Berlin, Germany.

    ·         Quote by Dr. Jurry de la Mar, T-Systems International GmbH, Account Ditrector Global Accounts & International Business: “ImageQuerying is an innovative application that simplifies and accelerates the analysis of large EO image archives. The images and image time-series are automatically pre-classified and stored in a raster database, thus allowing users to perform geospatiotemporal semantic queries on large EO image archives via an easy-to-use grapic user interface. The application quickly transforms EO images into information, creating real value for the user.”

    ·         Awards Ceremony on Oct. 20, 2015 at the Satellite Masters Conference, 20-22 Oct. 2015, German Federal Ministry of Transport and Digital Infrastructure, Invalidenstraße 444, 10115 Berlin, Germany.

    May 2015

    IGARSS 2015, Milan, Italy, 27-31 July 2015. IEEE GRSS Data Fusion Contest, paper “Geospatial 2D AND 3D object-based classification and 3D reconstruction of ISO-containers depicted in a LiDAR dataset and aerial imagery of a harbor”, ranked 2nd.





    IEEE Trans. Fuzzy Systems. Reviewed papers:


    IEEE Trans. Neural Networks


    IEEE Trans. Image Processing


    IEEE Trans. Knowledge and Data Engineering


    IEEE Trans. Systems, Man, and Cybernetics


    IEEE Trans. Geoscience and Remote Sensing


    IEEE Geoscience and Remote Sensing Letters


    International Journal of Remote Sensing


    Fuzzy Sets and Systems


    Cybernetics and Systems


    Information Fusion Journal


    International Journal of Pattern Recognition and Artificial Intelligence


    Pattern Recognition Letters


    Photogrammetric Engineering & Remote Sensing


    Remote Sensing


    Remote Sensing of Environment, Elsevier


    International Society for Photogrammetry and Remote Sensing (ISPRS), Elsevier


    International Journal of Applied Earth Observation and Geoinformation (JAG), Elsevier


    Computers and Electronics in Agriculture, Elsevier


    Information Science


    Cold Regions Science and Technology




    Personal skills and





    Mother tongue


    Other languages


    Understanding english

    Speaking english

    Writing english



    Spoken interaction

    Spoken production


    C2- Proficient user

    C2- Proficient user

    C2- Proficient user

    C2- Proficient user

    C2- Proficient user


    Technical skills and competences

    Software engineering

    -       Analysis of the user requirements.

    -       Software planning.

    -       Data flow analysis.

    -       Structured system design.

    -       Software implementation.

    -       Software validation.

    Machine learning, artificial intelligence and pattern recognition

    -       Stationary environments (either finite or infinite data sets).

    o   Labeled (supervised) data learning.

    §  Function regression from continuous labeled data.

    §  Categorical data classification.

    o   Unlabeled (unsupervised) data learning.

    §  Unlabeled data clustering.

    §  Vector quantization.

    §  Probability density function estimation.

    -       Inductive machine learning (self-organizing networks) from non-stationary data sets.

    -       Prior knowledge-based systems (expert systems, static rule-based decision systems).

    o   Semantic networks (conceptual models) for spatio-temporal knowledge representation of the 4-D world-through-time.

    -       Hybrid inference systems, combining: i) top-down (deductive, knowledge-driven, model-based, learning-by-rule, coarse-to-fine) and ii) bottom-up (inductive, driven-without-knowledge, data-driven, learning-by-example, fine-to-coarse) inference systems.

    Multiple source data fusion

    Mixture of experts, mixture of classifiers, hybrid (inductive [bottom-up] and deductive [top-down]) decision systems, convergence-of-evidence approach.

    Computer vision

    -       Pre-attentive and attentive vision.

    -       (Ill-posed) inference of plausible symbolic descriptions of the (3-D) scene depicted in a (2-D) image.

    Image pre-processing, enhancement and feature extraction

    Radiometric calibration, edge-preserving image smoothing, multi-spectral image panchromatic-sharpening, (2-D) image feature extraction (e.g., geometric features (shape indexes), texture features, morphological features, autocorrelation estimation), inter-object relationships (spatial topological and non-topological relationships, temporal relationships).



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