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http://dx.doi.org/10.7780/kjrs.2009.25.2.95

Adaptive Reconstruction of NDVI Image Time Series for Monitoring Vegetation Changes  

Lee, Sang-Hoon (Kyungwon University)
Publication Information
Korean Journal of Remote Sensing / v.25, no.2, 2009 , pp. 95-105 More about this Journal
Abstract
Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.
Keywords
NDVI; time series; harmonic model; adaptive reconstruction; vegetation changes;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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