Article

Article name ESTIMATES OF CHANGES OF STRUCTURAL PARAMETERS OF FOREST ECOSYSTEMS IN DECODING HIGH RESOLUTION SATELLITE IMAGES
Authors

Yuri F. Rozhkov, PhD, Deputy Director of the State Nature Reserve" Olekminsky"; 678100, Olekminsk, st. Filatova, 6; e-mail: olekmazap-nauka@yandex.ru
Maria Yu. Kondakova, PhD, Senior Researcher, Hydrochemical Institute; 344090, Rostov-on-Don, Stachki Avenue, 198; e-mail: vesna-dm@mail.ru

Reference to article

Rozhkov Yu.F., Kondakova M.Yu. 2016. Estimates of changes of structural parameters of forest ecosystems in decoding high resolution satellite images. Nature Conservation Research 1(1): 98–107. https://dx.doi.org/10.24189/ncr.2016.008

Section Research articles
DOI https://dx.doi.org/10.24189/ncr.2016.008
Abstract

Aim of this study was to assess the possibility of using of the parameter of symmetry of pixel distribution in the forest condition monitoring. Multispectral satellite imagery and their fragments of high and medium resolution (Landsat TM/ЕТМ+, Aster, Spot, IRS), which have been made in 1995–2011, were processed in two stages. At the first stage, uncontrolled classification has been carried out using the method ISODATA (Iterative Self-Organizing Data Analysis Technigue). At the second stage, parameter of symmetry of pixel distribution was calculated. The results of classification were divided into two halves. Classes with lower optical density of the reflected light were concentrated in the upper half while classes with higher optical density of the reflected light were concentrated in the bottom half.
The prospects for using the parameter symmetry of pixel distribution aim to assess the degree of forest disturbance after the fire impact was demonstrated. Disturbed forest areas a have larger sum of pixels in the bottom half of the classification results compared with the upper half. In contrast, undisturbed forest areas have a larger or equal sum of pixels in the upper half of the classification results compared with the bottom half.
The prospects for using the parameter symmetry of pixel distribution in monitoring of seasonal changes of forest status were demonstrated. Comparison of two forest fragments with dominance of larch and Siberian pine showed that during the autumn months (September, October) after needle fall and leaf fall, there is a sharp decrease of the parameter "symmetry of pixel distribution" within the fragment with dominance of larch due to the increase of the proportion of pixels with high optical density. Seasonal changes in the parameter of symmetry of pixels distribution were less pronounced for the forest fragment with dominance of Siberian pine. We considered the prospect to use the parameter of symmetry of pixel distribution in the long-term monitoring of forest ecosystems status ( for example of the forest restoration process after fire impact). The rate of forest recovery was determined within the burned fragment with an area of 6.98 km2

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Keywords

classification ISODATA, interpretation of satellite images, the symmetry of pixel distribution

Artice information

Submitted at 01.02.2016

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References

ArcVi ew Image Analysis. Guidelines for the user. 1998. Moscow: Data+. 270 р. [In Russian].
Escuin S. [et al.]. 2008. Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference
Vegetation Index) derived from Landsat TM/ETM images. Journal of Remote Sensing 29: 1053–1073.
Hall R.J. [et al.]. 2006. Modeling forest stand structure attributes using Landsat ETM+ data: application to mapping of aboveground biomass and stand volume. Forest ecology and management 225: 378–390.
Hudak A.T. [et al.]. 2007. Relationship of multispectral satellite imagery to immediate fire effects. Journal of Fire ecology 3: 64–90.
Jadunandan Dash, Curran P.J. 2004. MTCI: The MERIS Terrestrial chlorophyll index. ENVISAT Symposium Proceedings.
Austria, Salzzburg.
Krankina O.N. [et al.]. 2004. Carbon stores, thinks, and sources in forests of northwestern Russia can we reconcile forest inventories with remote sensing results? Climate change 67: 257–272.
Rozhkov Yu.F., Kondakova M.Yu. 2014. Assessment of forest ecosystems violations after forest fires using interpretation of space images. Fundamental research 9 (9): 2018–2022 [In Russian].