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A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring / M. Chernetskiy [et al.] // Advances in Space Research. - 2011. - Vol. 48, Is. 5. - P819-825, DOI 10.1016/j.asr.2011.04.032 . - ISSN 0273-1177
Кл.слова (ненормированные):
EVI -- Forestry -- MODIS -- NDVI -- Remote sensing -- Vegetation phenology -- Accurate measurement -- Annual time series -- Carbon exchange -- Data series -- Dynamic state -- Enhanced vegetation index -- EVI -- Forest vegetation -- Global scale -- Growth dynamics -- Interannual variability -- Moderate resolution imaging spectroradiometer -- MODIS -- NDVI -- Normalized difference vegetation index -- Principal components analysis -- Remote sensing applications -- Remote sensing data -- Satellite data -- Spatial structure -- Spring season -- Terrestrial ecosystems -- Vegetation dynamics -- Vegetation phenology -- Biology -- Climate models -- Dynamics -- Ecosystems -- Estimation -- Forestry -- Monitoring -- Principal component analysis -- Radiometers -- Remote sensing -- Satellite imagery -- Timber -- Time series -- User interfaces -- Vegetation -- Carbon -- Ecosystems -- Forests -- Image Analysis -- Plants -- Remote Sensing -- Time Series Analysis
Аннотация: Remote sensing applications have greatly enhanced ability to monitor and manage in the areas of forestry. Accurate measurements of regional and global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate-biosphere interactions. Study of vegetation phenology is required for understanding of variability in ecosystem. In this paper, monitoring of vegetation dynamics using time series of satellite data is presented. Vegetation variability (vegetation rate) in different topoclimatic areas is investigated. Original software using IDL interactive language for processing of satellite long-term data series was developed. To investigate growth dynamics vegetation rate inferred from remote sensing was used. All estimations based on annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Vegetation rate for Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) was calculated using MODIS data. The time series covers spring seasons of each of 9 years, from 2000 to 2008. Comparison of EVI and NDVI derived growth rates has shown that NDVI derived rates reveal spatial structure better. Using long-term data of vegetation rates variance was estimated that helps to reveal areas with anomalous growth rate. Such estimation shows sensitivity degree of different areas to different topoclimatic conditions. Woods of heights depend on spatial topoclimatic variability unlike woods of lowlands. Principal components analysis shows vegetation with different rate conditions. Also it reveals vegetation of same type in areas with different conditions. It was demonstrated that using of methods for estimating the dynamic state of vegetation based on remote sensing data enables successful monitoring of vegetation phenology. В© 2011 COSPAR. Published by Elsevier Ltd. All rights reserved.

Scopus
Держатели документа:
Institute of Biophysics of SB RAS, Akademgorodok 50/50, Krasnoyarsk 660036, Russian Federation : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Chernetskiy, M.; Pasko, I.; Shevyrnogov, A.; Slyusar, N.; Khodyayev, A.

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