Zisis I. Petrou

postdoctoral research scholar | zpetrou@ccny.cuny.edu


ABOUT

I am postdoctoral research scholar at the City College of New York, City University of New York. I work for the Media Lab at the Department of Electrical Engineering, directed by Prof. Yingli Tian. My research interests focus on machine learning, deep learning, and computer vision on remote sensing and geospatial analysis. My latest activities involve motion estimation and prediction of Arctic sea ice through multimodal and multi-resolution satellite imagery.

profile photo


RESEARCH
Research Field
  • Remote sensing
  • Data science / analysis, predictive modeling
  • Machine learning, deep learning
  • Image processing, texture analysis
  • Reasoning with uncertainty
  • Supervised classification, dimensionality reduction, feature selection, multiple imputation, outlier removal
  • Regression analysis

Applications
  • Sea ice motion estimation and prediction
  • Land cover and habitat mapping
  • Biophysical parameter extraction


EDUCATION

Ph.D. in Remote Sensing, Machine Learning and Data Analysis
Electrical & Electronic Engineering Department, Imperial College London, London, UK
PhD Thesis: “Remote sensing methods for biodiversity monitoring with emphasis on vegetation height estimation and habitat classification”

OCTOBER 2010 – APRIL 2015

M.Sc. in Space Studies
International Space University, Strasbourg, France
M.Sc. Thesis: “Derivation of cloud properties from MODIS for the 3D visualization of atmospheric dynamics”

SEPTEMBER 2008 – AUGUST 2009

Diploma in Electrical and Computer Engineering (Equivalent to B.Sc. and M.Sc.)
Aristotle University of Thessaloniki, Greece
Master’s Thesis: “Estimation of Camera Motion using the recorded Image Sequence”

SEPTEMBER 2001 – JULY 2007


WORK EXPERIENCE

Remote sensing & computer vision – Postdoctoral Research Scholar
The City College of New York, New York, NY

I work on research, design and development of algorithms for sea ice motion tracking and prediction using multispectral passive satellite images.

FEBRUARY 2016 - CURRENT

Machine Learning & Data Science – Doctoral & Postdoctoral Research Fellow
Centre for Research and Technology Hellas (CE.R.T.H.), Thessaloniki, Greece

I developed machine and data analysis algorithms, mainly for remote sensing applications. Applications included land cover mapping, habitat classification, change detection, and landscape analysis. Additional activities included algorithms for search & retrieval of 3D objects and project proposal writing.

DECEMBER 2009 - JANUARY 2016

Computer Lab Assistant, Signal Processing labs
Imperial College London, UK

I taught and graded undergraduate students in Electrical and Electronic Engineering Department.

FEBRUARY 2011 - MAY 2011

Intern in remote sensing applications
German Aerospace Center (DLR), Oberpfaffenhofen, Germany

I extracted cloud height and thickness from MODIS satellite images using Linux scripts and open source software.

MAY 2009 - AUGUST 2009

Intern in website development
Tomas Bata University, Zlin, Czech Republic

I developed a website platform for the Department of Applied Informatics in HTML and CSS.

OCTOBER 2006 - DECEMBER 2006


AWARDS

  • Best paper award for young professional under 35 years at the 2 nd International Conference on Space Technology (ICST), Athens, 15–17 September 2011
  • Scholarship awarded by the European Space Agency (ESA) for M.Sc. studies (2008–2009)
  • Scholarship awarded by the Onassis Foundation during M.Sc. studies (2008–2009)


FIELDS OF EXPERTISE – LANGUAGES

  • Machine learning: (Semi-)supervised & unsupervised learning & deep learning (Random forests, Bagging, AdaBoost, SVM, Convolutional Neural Networks, Bayesian networks, k-means, ISODATA) | Dimensionality reduction (PCA, LDA, LPP, NPE, Isomap) | Feature selection (CFS, Best first, LFS, SFFS) | Multiple imputation (Amelia-II, IRMI) | Outlier removal (box plot, medcouple)
  • Statistical and predictive analysis and modeling | Recurrent Neural Nets | Long Short-Term Memory (LSTM) networks | Bayesian models | Probabilities | Differential equations
  • Deductive learning (fuzzy Dempster–Shafer classifiers)
  • Correlation models (Generalized Linear Models, Boosted Regression Trees, Neural Nets, Max. Entropy)
  • Programming languages: Python, R, MATLAB/Octave, Java, C/C++, Fortran, HTML
  • Database systems: SQL (MySQL, Oracle SQL)
  • Reviewer in several scientific journals
  • Languages: English (Excellent) | French (Good) | Italian (Good) | German (Basic) | Greek (Native)



PUBLICATIONS
Scientific journals
  1. I. Manakos, K. Chatzopoulos-Vouzoglanis, I. Gkinis, Z. I. Petrou, E. Stylianidis, G. Pozoukidou, “Assessing urban development trends in representative Local Administrative Units before and after the Greek economic crisis,” Remote Sensing Applications: Society and Environment. Accepted for publication.
  2. Y. Xian, Z. I. Petrou, Y. Tian, and W. N. Meier, “Super-resolved fine scale sea ice motion tracking,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 8, August 2017. DOI: 10.1109/TGRS.2017.2699081. [bibtex] [dataset]
  3. Z. I. Petrou and Y. Tian, “High resolution sea ice motion estimation with optical flow using satellite spectroradiometer data,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 3, pp. 1339–1350, March 2017. [link] [bibtex] [dataset]
  4. I. Manakos, E. Technitou, Z. I. Petrou, C. Karydas, V. Tomaselli, G. Veronico, and G. Mountrakis, “Multimodal knowledge base generation from very high resolution satellite imagery for habitat mapping,” European Journal of Remote Sensing, vol. 49, pp. 1033–1060, December 2016. [pdf] [link] [bibtex]
  5. Z. I. Petrou, I. Manakos, and T. Stathaki, “Remote sensing for biodiversity monitoring: A review of methods for biodiversity indicator extraction and assessment of progress towards international targets,” Biodiversity and Conservation, vol. 24, no. 10, pp. 2333–2363, Sep. 2015. [link] [bibtex]
  6. Z. I. Petrou, I. Manakos, T. Stathaki, C. A. Mücher, and M. Adamo, “Discrimination of vegetation height categories with passive satellite sensor imagery using texture analysis,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 8, no. 4, pp. 1442–1455, April 2015. [link] [bibtex]
  7. Z. I. Petrou, V. Kosmidou, I. Manakos, T. Stathaki, M. Adamo, C. Tarantino, V. Tomaselli, P. Blonda, and M. Petrou, “A rule-based classification methodology to handle uncertainty in habitat mapping employing evidential reasoning and fuzzy logic,” Pattern Recognition Letters, vol. 48, pp. 24–33, Oct. 2014. [link] [bibtex]
  8. R. Lucas, P. Blonda, P. Bunting, G. Jones, J. Inglada, M. Arias, V. Kosmidou, Z. I. Petrou, I. Manakos, M. Adamo, R. Charnock, C. Tarantino, C. A. Mücher, R. Jongman, H. Kramer, D. Arvor, J.P. Honrado, and Paola Mairota, “The Earth Observation Data for Habitat Monitoring (EODHaM) System,” International Journal of Applied Earth Observation and Geoinformation, vol. 37, pp. 17–28, May 2015. [link] [bibtex]
  9. C. A. Mücher, L. Roupioz, H. Kramer, M. M. B. Bogers, R. H. G. Jongman, R. M. Lucas, V. Kosmidou, Z. I. Petrou, I. Manakos, E. Padoa-Schioppa, M. Adamo, and P. Blonda, “Synergy of Airborne LiDAR and Wordldview-2 satellite imagery for land cover and habitat mapping: a BIOSOS-EODHAM case study for the Netherlands,” International Journal of Applied Earth Observation and Geoinformation, vol. 37, pp. 48–55, May 2015. [link] [bibtex]
  10. I. Manakos, K. Chatzopoulos-Vouzoglanis, Z. I. Petrou, L. Filchev, and A. Apostolakis, “Globalland30 Mapping Capacity of Land Surface Water in Thessaly, Greece,” Land, vol. 4, no. 1, pp. 1–18, Mar. 2015. [link] [bibtex]
  11. M. Adamo, C. Tarantino, V. Tomaselli, V. Kosmidou, Z. I. Petrou, I. Manakos, R. M. Lucas, C. A. Mücher, G. Veronico, C. Marangi, V. De Pasquale, and P. Blonda, “Expert knowledge for translating land cover/use maps to General Habitat Categories (GHC),” Landscape Ecology, vol. 29, no. 6, pp. 1045–1067, Jul. 2014. [link] [bibtex]
  12. V. Kosmidou, Z. I. Petrou, R. G. H. Bunce, C. A. Mücher, R.H.G. Jongman, M.M. Bogers, R.M. Lucas, V. Tomaselli, P. Blonda, E. Padoa-Schioppa, I. Manakos, and M. Petrou, “Harmonization of the Land Cover Classification System (LCCS) with the General Habitat Categories (GHC) classification system,” Ecological Indicators, vol. 36, pp. 290–300, Jan. 2014. [link] [bibtex]

Scientific conferences & meetings
  1. Z. I. Petrou and Y. Tian, “Prediction of sea ice motion with recurrent neural networks,” in IEEE International Geoscience and Remote Sensing Symposium 2017. Accepted for publication.
  2. Z. I. Petrou, Y. Xian, and Y. Tian, “Increasing spatial resolution of sea ice motion estimation,” in IEEE International Geoscience and Remote Sensing Symposium 2017. Accepted for publication.
  3. I. Manakos, E. Technitou, Z. I. Petrou, V. Tomaselli, G. Veronico, and C. Karydas, “Multi-modal knowledge base generation from remote sensing very high resolution imagery for habitat mapping,” in 6th EARSeL SIG LU/LC & 2nd EARSeL LULC/NASA LCLUC Workshop, Prague, 6–7 May 2016.
  4. Z. I. Petrou, T. Stathaki, I. Manakos, M. Adamo, C. Tarantino, and P. Blonda, “Land cover to habitat map conversion using remote sensing data: a supervised learning approach,” in IEEE International Geoscience and Remote Sensing Symposium, Quebec City, 13–18 Jul. 2014, pp. 4683–4686. [link]
  5. Z. I. Petrou, I. Manakos, T. Stathaki, C. Tarantino, M. Adamo, and P. Blonda, “A vegetation height classification approach based on texture analysis of a single VHR image,” in Proceedings of the 35th International Symposium on Remote Sensing of Environment, IOP Conference Series: Earth and Environmental Science, vol. 17, 2014, 012210, doi:10.1088/1755-1315/17/1/012210. [link]
  6. Z. I. Petrou, I. Manakos, T. Stathaki, C. Tarantino, M. Adamo, and P. Blonda, “Canopy height estimation through the use of texture analysis of a very high resolution satellite image,” Poster presentation at the 4th Advanced Training Course in Land Remote Sensing, ESA, Athens, 1–5 Jul. 2013. [pdf]
  7. Z. I. Petrou, C. Tarantino, M. Adamo, P. Blonda, and M. Petrou, “Estimation of vegetation height through satellite image texture analysis,” in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXIX-B8, Melbourne, 2012, pp. 321–326. [link]
  8. Z. I. Petrou and M. Petrou, “A review of remote sensing methods for biodiversity assessment and bioindicator extraction,” in Proceedings of the 2nd International Conference on Space Technology, IEEE, Athens, 15–17 Sep. 2011, DOI: 10.1109/ICSpT.2011.6064679. [link]
  9. M. Adamo, C. Tarantino, V. Kosmidou, Z. I. Petrou, I. Manakos, R. M. Lucas, V. Tomaselli, C. A. Mücher, and P. Blonda, “Land cover to habitat map translation: Disambiguation rules based on earth observation data,” in IEEE International Geoscience and Remote Sensing Symposium, IEEE, Melbourne, 2013. pp. 3817–3820. [link]
  10. M. Adamo, C. Tarantino, V. Kosmidou, Z. I. Petrou, I. Manakos, V. Tomaselli, R. Lucas, C. A. Mücher, and P. Blonda, “Exploitation of remote sensing data for land cover to habitat map translation: A case study,” in GI_Forum conference, Salzburg, 2–5 Jul. 2013, pp. 487–491. [pdf]
  11. R. Lucas, G. Jones, P. Bunting, V. Kosmidou, Z. I. Petrou, J. Inglada, M. Adamo, P. Blonda, C. A. Mücher, and D. Arvor, “Land cover and habitat classification from earth observation data: A new approach from BIO_SOS,” in GI_Forum conference, Salzburg, 2–5 Jul. 2013, pp. 516–519. [pdf]
  12. C. A. Mücher, L. Roupioz, H. Kramer, M. Wolters, M. Bogers, R. Lucas, P. Bunting, Z. I. Petrou, V. Kosmidou, I. Manakos, E. Padoa-Schioppa, G.F. Ficetola, A. Bonardi, M. Adamo, and P. Blonda, “LiDAR as a valuable information source for habitat mapping,” in GI_Forum conference, Salzburg, 2–5 Jul. 2013, pp. 520–523. [pdf]

Book Chapters
  1. C. A. Mücher, K. Calders, Z. I. Petrou, and J. Reiche, “Ecosystem structure,” in Sourcebook for Biodiversity Monitoring in Tropical Forests with Remote Sensing, GOFC-GOLD and GEO BON (Eds.), Report version UNCBD COP-13. GOFC-GOLD Land Cover Project Office, Wageningen University, The Netherlands, 2017. ISSN: 2542-6729, ch. 2.5, pp. 67–82. [link] [pdf (book)] [pdf (chapter)]


CONTACT

Email
zpetrou@ccny.cuny.edu

Address
Department of Electrical Engineering
The City College of New York
160 Convent Avenue
New York, NY 10031, USA

Phone
+1 212-650-8917

SOCIAL LINKS

ResearchGate profile Google Scholar citations