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http://dx.doi.org/10.7780/kjrs.2014.30.4.8

An improved method of NDVI correction through pattern-response low-peak detection on time series  

Lee, Kyeong-Sang (Dept. of Spatial Information Engineering, Pukyong National University)
Han, Kyung-Soo (Dept. of Spatial Information Engineering, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.30, no.4, 2014 , pp. 505-510 More about this Journal
Abstract
Normalized Difference Vegetation Index (NDVI) is a major indicator for monitoring climate change and detecting vegetation coverage. In order to retrieve NDVI, it is preprocessed using cloud masking and atmospheric correction. However, the preprocessed NDVI still has abnormally low values known as noise which appears in the long-term time series due to rainfall, snow and incomplete cloud masking. An existing method of using polynomial regression has some problems such as overestimation and noise detectability. Thereby, this study suggests a simple method using amoving average approach for correcting NDVI noises using SPOT/VEGETATION S10 Product. The results of the moving average method were compared with those of the polynomial regression. The results showed that the moving average method is better than the former approach in correcting NDVI noise.
Keywords
Moving average; NDVI; SPOT; Noise; correction;
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Times Cited By KSCI : 2  (Citation Analysis)
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