Abstract
HJ-1A/B NDVI (HJ NDVI) time-series data possess relatively high spatio-temporal resolution which is significant for the research on urban areas. However, its application is hindered by noise resulting from the restrictions of imaging quality and limits of the satellite platform. The NDVI noise reduction is necessary. Some noise-reduction techniques including the asymmetric Gaussian filter (AG), the double logistic filter (DL), the Savitzky-Golay (S-G) filter and the harmonic analysis (Hants) of NDVI time-series have been used to carry out the NDVI time series reconstruction, and based on the comparison results of different filter, S-G filter is the optimal in the application on urban areas. Finally,urban vegetation mapping is carried out based on the new HJ NDVI.
Highlights
Vegetation is of particular interest as it presents a versatile resource for effectively managing and moderating a variety of problems associated with urbanization
Four kinds of filters including S-G, asymmetric Gaussian filter (AG), double logistic filter (DL) and harmonic analysis of NDVI time-series (Hants) are used in the experiments, among which the first three can be processed using TIMESAT software [14]
For evergreen coniferous tree and deciduous broadleaved tree, the filter of size of 5 (S-G 5) is better than S-G 3 and for other two types, the filter of S-G 3 can get the better results; 3) The filtering results of AG and DL filter have a great similarity; 4) The filtering results of Hants are similar to the original data
Summary
Vegetation is of particular interest as it presents a versatile resource for effectively managing and moderating a variety of problems associated with urbanization. The remote sensing images of HJ have constituted nearly eight years of time-series data making it possible for urban application research due to relative high spatial and temporal resolution. Many researches focus on the establishment of high-quality NDVI time series using different filtering methods such as Savitzky-Golay (S-G) [8], Gaussian fitting method (AG) [9], the double logistic curve fitting method (DL) [10] and the harmonic analysis of NDVI time-series (Hants) [11]. These researches focus on the filtering effect of specific filter. Though there are researches which discussed the pros and cons of different filtering algorithms through quantitative comparative analysis [7, 8, 12, 13], it is lack of the specific application objective and an evaluation framework in urban area using relatively high-resolution NDVI time series
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