Statistics – Applications
Scientific paper
Sep 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011adspr..48..819c&link_type=abstract
Advances in Space Research, Volume 48, Issue 5, p. 819-825.
Statistics
Applications
Scientific paper
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.
Chernetskiy M.
Khodyayev A.
Pasko I.
Shevyrnogov A.
Slyusar N.
No associations
LandOfFree
A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1077799