ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 2, pp. 100-111

Investigation of 3D structure of vegetation cover in yernik tundra using photography and automated image processing techniques

I.V. Matelenok 1 , V.V. Melentyev 1 
1 State University of Aerospace Instrumentation, Saint Petersburg, Russia
Accepted: 31.12.2017
DOI: 10.21046/2070-7401-2018-15-2-100-111
Simulation of radio wave propagation in multilayer media using current electrodynamic models requires the most complete information about vegetation properties including 3D structure. A new approach to evaluation of orientation and relative position of plant elements in vegetation cover formed by shrubs and dwarf-shrubs was proposed in the paper. It is based on multi-view photography of vegetation cover fragments. The approach is implemented in a new version of the instrument for surveying vegetation cover structure. Experiments for automatized retrieving spatial positions of plant elements in controlled conditions were carried out in frame of two-step testing. A field survey on sites in the Nenets Autonomous Area and Murmansk Region and succeeding cameral work have resulted in estimates of the orientation and collocation of the dwarf birch leaves. Comparative analysis showed an agreement between the values of the structure parameters obtained with the proposed approach and one of the alternative approaches. The obtained leaf angle distribution resembles spherical and plagiophile standard distributions, and ellipsoid density function is more appropriate to describe the data. Regional differences in leaf angle distribution for the studied vegetation cover are not detected. Three-dimensional graphic models of vegetation cover fragments are constructed on the basis of the data. Data representation allows to use it for modeling radio wave propagation, evaluating biomass accumulation and performing thermophysical calculations.
Keywords: digital photography, dwarf-shrub tundra, image processing, leaf angle distribution, leaf inclination angle, vegetation cover structure, electrodynamic models
Full text

References:

  1. Katulin M. S., Perevoshchikov L. L., Shumkov S. G., Sozdanie apparatno-programmnogo kompleksa dlya podvodnoi navigatsii s ispol’zovaniem mashinnogo zreniya (Prototyping of hardware and software application to underwater navigation using computer vision), Izvestiya TulGU. Tekhnicheskie nauki, 2015, No. 11-2, pp. 90–100.
  2. Matelenok I. V., Melentyev V. V., Programmno-apparatnyi kompleks dlya issledovaniya prostranstvennoi struktury napochvennogo pokrova lesov (Instrument for investigating of the spatial structure of forest ground covers), Aerokosmicheskie metody i geoinformatsionnye tekhnologii v lesovedenii, lesnom khozyaistve i ekologii (Aerospace Methods and GIS-Technologies in Forestry, Forest Management and Ecology), Proc. 6th All-Russian Conference, Moscow, 20–22 April 2016, Moscow: TsEPL RAN, 2016, pp. 138–143, available at: http://cepl.rssi.ru/wp-content/uploads/2016/04/.
  3. Campbell G. S., Derivation of an angle density function for canopies with ellipsoidal leaf angle distributions, Agricultural and forest meteorology, 1990, Vol. 49, No. 3, pp. 173–176.
  4. Chiu T., Sarabandi K., Electromagnetic scattering from short branching vegetation, IEEE Transactions on Geoscience and Remote Sensing, 2000, Vol. 38, No. 2, pp. 911–925.
  5. Duursma R., LeafAngle v1.2-1, 2014, available at: https://CRAN.R-project.org/package=LeafAngle.
  6. Huang H., Liao T. H., Tsang L., Njoku E. G., Colliander A., Jackson T., Yueh S., Combined active and passive microwave remote sensing of soil moisture for vegetated surfaces at L-band, Geoscience and Remote Sensing Symposium 2016, IEEE, 2016, pp. 1626–1629.
  7. Hutter M., Brewer N., Matching 2-D ellipses to 3-D circles with application to vehicle pose identification, Image and Vision Computing New Zealand: Proceedings of 24th International Conference 2009, IEEE, 2009, pp. 153–158.
  8. Juszak I., Erb A. M., Maximov T. C., Schaepman-Strub G., Arctic shrub effects on NDVI, summer albedo and soil shading, Remote Sensing of Environment, 2014, Vol. 153, pp. 79–89.
  9. Juszak I., Iturrate-Garcia M., Gastellu-Etchegorry J. P., Schaepman M. E., Maximov T. C., Schaepman-Strub G., Drivers of shortwave radiation fluxes in Arctic tundra across scales, Remote Sensing of Environment, 2017, Vol. 193, pp. 86–102.
  10. Macelloni G., Paloscia S., Pampaloni P., Marliani F., Gai M., The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops, IEEE Transactions on Geoscience and Remote Sensing, 2001, Vol. 39, No. 4, pp. 873–884.
  11. Nistér D., Stewénius H., Linear time maximally stable extremal regions, Computer Vision — ECCV 2008: 10th European Conference on Computer Vision, Proc. Conf., Marseille, 2008, pp. 183–196.
  12. Pearcy R. W., Duursma R. A., Falster D. S., Studying plant architecture with Y-plant and 3D digitising, PrometheusWiki, 2011, available at: http://prometheuswiki.publish.csiro.au/tiki-index.php?page=Studying+plant+architecture+with+Y-plant+and+3D+digitising.
  13. Pisek J., Ryu Y., Alikas K., Estimating leaf inclination and G-function from leveled digital camera photography in broadleaf canopies, Trees, 2011, Vol. 25, Issue 5, pp. 919–924.
  14. Zhang Y., Liu X., Su S., Wang C., Retrieving canopy height and density of paddy rice from Radarsat-2 images with a canopy scattering model, International J. of Applied Earth Observation and Geoinformation, 2014, Vol. 28, pp. 170–180.