Remote Sensing

Remote Sensing for peaceful purposes aims at the improvement of human life. Rational usage of natural resources, food security and tackling of threats constitute core drivers for the development of sensors by the European (ESA), American (NASA) and other space agencies worldwide, as well as the design and development of remote sensing data processing methodologies.

VARLab innovates in this research with the development of services for monitoring and assessment of biodiversity and habitats, agriculture, sustainable development, change detection in land cover and land use, simulation and scenario analysis, as well as the incorporation of data from citizen observatories enhancing credibility and timeliness.

Indicative applications include, but are not limited to:

- Delineation of height categories for vegetated areas characterization through texture analysis of a single very high spatial resolution multispectral image. A number of texture features are produced, including local variance, entropy, and binary patterns. These features are processed through a variety of machine learning algorithms, potentially including dimensionality reduction, feature selection, multiple imputation of missing data, outlier removal, data normalization. Following processing, each land patch is assigned to the respective height category through a number of different supervised classifiers.

Relevant selected publications:

    1. Z. Petrou, I. Manakos, T. Stathaki, C. A. Mücher, M. Adamo, "Discrimination of vegetation height categories with passive satellite sensor imagery using texture analysis", 2015, IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 8(4), 1442–1455.
    2. C. A. Mücher, L. Roupioz, H. Kramer, M. M. B. Bogers, R. H. G. Jongman, R. M. Lucas, V. Kosmidou, Z. Petrou, I. Manakos, E. Padoa-Schioppa, M. Adamo, P. Blonda., "Synergy of Airborne LiDAR and Worldview-2 satellite imagery for land cover and habitat mapping: a BIOSOS-EODHAM case study for the Netherlands", 2015, International Journal of Applied Earth Observation and Geoinformation 37, 48–55.
    3. Z. Petrou, I. Manakos, T. Stathaki, C. Tarantino, M. Adamo, P. Blonda, "A vegetation height classification approach based on texture analysis of a single VHR image", Proceedings of the 35th International Symposium on Remote Sensing of Environment, 2014, IOP Conference Series: Earth and Environmental Science, 17, 012210 doi:10.1088/1755-1315/17/1/012210.
    4. S. Mucher, L. Roupioz, H. Kramer, M. Wolters, M. Bogers, R. Lucas, P. Bunting, Z. Petrou, V. Kosmidou, I. Manakos, E. Padoa-Schioppa, G.F. Ficetola, A. Bonardi, M. Adamo, P. Blonda, "LIDAR as a valuable information source for habitat mapping", GI_Forum conference, 2-5 July 2013, Salzburg, Austria, pp. 520–523.
    5. Z. Petrou, C. Tarantino, M. Adamo, P. Blonda, M. Petrou, "Estimation of Vegetation Height through Satellite Image Texture Analysis", International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia, pp. 321–326.

remotesensing

 

- Characterization of habitats based on land cover properties of patches and very high resolution satellite imagery. Having the land cover class of each patch expressed in the Land Cover Classification System (LCCS) as input, a number of spectral, texture, topological, morphological, and height features are extracted. The features are used to assign each patch to a habitat class expressed in the General Habitat Categories taxonomy, following either a supervised classification or a fuzzy evidential reasoning rule-based scheme taking into account noise afflicted data and uncertainty.

Relevant selected publications:

    1. R. Lucas, P. Blonda, P. Bunting, G. Jones, J. Inglada, M. Arias, V. Kosmidou, Z. Petrou, I. Manakos, M. Adamo, R. Charnock, C. Tarantino, C. A. Mücher, R. Jongman, H. Kramer, D. Arvor, J. P. Honrado, P. Mairota, "The Earth Observation Data for Habitat Monitoring (EODHAM) System", 2015, International Journal of Applied Earth Observation and Geoinformation 37, 17–28.
    2. Z. Petrou, V. Kosmidou, I. Manakos, T. Stathaki, M. Adamo, C. Tarantino, V. Tomaselli, P. Blonda, M. Petrou, "A rule-based classification methodology to handle uncertainty in habitat mapping employing evidential reasoning and fuzzy logic", 2014, Pattern Recognition Letters, 48, 24-33.
    3. M. Adamo, C. Tarantino, V. Tomaselli, V. Kosmidou, Z. Petrou, I. Manakos, R.M. Lucas, C.A. Mucher, G. Veronico, C. Marangi, V. De Pasquale, P. Blonda, "Expert knowledge for translating land cover/use maps to General Habitat Categories (GHC)", 2014, Landscape Ecol., 29(6), 1045-1067.
    4. V. Kosmidou, Z. Petrou, R.G.H. Bunce, C.A. Mucher, R.H.G. Jongman, M.M. Bogers, R.M. Lucas, V. Tomaselli, P. Blonda, E. Padoa-Schioppa, I. Manakos, M. Petrou, "Harmonization of the Land Cover Classification System (LCCS) with the General Habitat Categories (GHC) classification system", 2014, Ecol. Indic. 36, 290–300
    5. Z. Petrou, T. Stathaki, I. Manakos, M. Adamo, C. Tarantino, P. Blonda, "Land cover to habitat map conversion using remote sensing data: a supervised learning approach," in: IEEE Int. Geoscience and Remote Sensing Symp., IEEE, Quebec City, 2014, pp. 4683–4686.
    6. M. Adamo, C. Tarantino, V. Kosmidou, Z. Petrou, I. Manakos, V. Tomaselli, R. Lucas, S. Muncher, P. Blonda, "Disambiguation rules based on Earth Observation data for Land Cover to habitat map translation: a case study", GI_Forum conference, 2-5 July 2013, Salzburg, Austria, pp. 487–491.
    7. R. Lucas, G. Jones, P. Bunting, V. Kosmidou, Z. Petrou, J. Inglada, M. Adamo, C. A. Mucher, D. Arvor, "Land cover and habitat classification from earth observation data: A new approach from BIO_SOS", GI_Forum conference, 2–5 July 2013, Salzburg, Austria, pp. 516–519.
    8. M. Adamo, C. Tarantino, V. Kosmidou, Z. Petrou, I. Manakos, R. M. Lucas, V. Tomaselli, C. A. Mucher, P. Blonda, "Land cover to habitat map translation: Disambiguation rules based on Earth Observation data", in: IEEE Int. Geoscience and Remote Sensing Symp., IEEE, Melbourne, 2013. pp. 3817–3820.
    9. P. Blonda, P. Dimopoulos, R. H. G. Jongman, C. A. Mucher, H. Nagendra, D. Iasillo, A. Arnaud, P. Mairota, J. P. Honrado, E. Padoa-Schioppa, R. Lucas, P. Bunting, L. Durieux, S. Bollanos, L. Candela, J. Inglada, I. Manakos, "The BIO_SOS European Initiative for Habitat Monitoring", 33rd EARSeL annual Symposium Proceedings, Matera, Italy, 2013, 911 - 920.

remotesensing

 

- Extraction of biodiversity indicators through the use of remote sensing data. A number of indicators adopted by the European Union and international organizations can be estimated through the use of remote sensing data in an accurate and timely manner.

Indicative publications:

    1. Z. Petrou, I. Manakos, 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, 2015, DOI: 10.1007/s10531-015-0947-z, accepted for publication.
    2. Z. Petrou, M. Petrou, "A review of Remote Sensing methods for Biodiversity assessment and Bioindicator extraction", in the 2nd Int. Conf. on Space Technology, 15–17 September 2011, Athens, Greece. DOI: 10.1109/ICSpT.2011.6064679.

remotesensing

 

- Mapping and assessment of land cover Remote Sensing data constitute precious information for the understanding of land use and land cover (LULC) of various territories. VARLab is actively engaged in LULC mapping activities, change detection, precision agriculture, monitoring of land surface processes, and validation.

Indicative publications:

    1. Manakos, K. Chatzopoulos-Vouzoglanis, Z. Petrou, L. Filchev, A. Apostolakis, "Globalland30 Mapping Capacity of Land Surface Water in Thessaly, Greece", 2015, Land 4(1), 1-18.
    2. Manakos, M. Braun, "Land Use & land cover mapping in Europe - practices and trends", Remote Sensing and Digital Image Processing Book Series, 2014, Springer Verlag, 18, p.441.
    3. Manakos, S. Lavender, "Remote Sensing in Support of Geo-Information in Europe", Land Use and Land Cover Mapping in Europe - practices & trends, Remote Sensing and Digital Image Processing Book Series, 2014, Springer Verlag, 18, 3-10.
    4. Elatawneh, A. Wallner, I. Manakos, T. Schneider, T. Knoke, "Forest Cover Database Updates Using Multi-Seasonal RapidEye Data - Storm Event Assessment in the Bavarian Forest National Park", Forests 2014, 5, 1284-1303.
    5. C.G. Karydas, M. Petriolis, I. Manakos, "Evaluating alternative methods of soil erodibility mapping in the Mediterranean island of Crete.", Special Issue 'Soil Erosion: A Major Threat to Food Production and the Environment', Journal of Agriculture, 2013, 3(3), Pages 362-380.
    6. Manakos, "Remote Sensing in Europe: Status analysis and trends focusing on environment and agriculture", Journal of Aeronautics and Space Technologies, 2013, Vol.6, No. 1, Pages 1-5.

remotesensing