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Proceedings Paper

A remote sensing technique for the assessment of stable interannual dynamical patterns of vegetation
Author(s): M. Y. Chernetskiy; A. P. Shevyrnogov; N. F. Ovchinnikova
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Paper Abstract

The time series of various parameters of satellite imagery (NDVI/EVI, temperature) during the growing season were considered in this work. This means that satellite images were considered not like a number of single scenes but like temporal sequences. Using time series enables estimating the integral phenological properties of vegetation. The basis of the developed technique is to use one of the methods of transformation of the multidimensional space in order to get the principal components. The technique is based on considering each dimension of the multidimensional space as satellite imagery for a specific date range. The technique automatically identifies spatial patterns of vegetation that are similar by phenology and growing conditions. Subsequent analysis allowed identification of the belonging of derived classes. Thus, the technique of revealing the spatial distribution of different dynamical vegetation patterns based on the phenological characteristics has been developed. The technique is based on a transformation of the multidimensional space of states of vegetation. Based on the developed technique, areas were obtained with similar interannual trends.

Paper Details

Date Published: 7 October 2011
PDF: 7 pages
Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 817420 (7 October 2011); doi: 10.1117/12.896748
Show Author Affiliations
M. Y. Chernetskiy, Institute of Biophysics (Russian Federation)
Siberian Federal Univ. (Russian Federation)
A. P. Shevyrnogov, Institute of Biophysics (Russian Federation)
Siberian Federal Univ. (Russian Federation)
N. F. Ovchinnikova, V.N. Sukachev Institute of Forest of SB RAS (United States)


Published in SPIE Proceedings Vol. 8174:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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