International Journal of Remote Sensing
Estimation of snow depth in the UK using the HUT snow emission model
International Journal of Remote Sensing
Remote-sensing image mining: detecting agents of land-use change in tropical forest areas
International Journal of Remote Sensing
Study of organic aerosols of phytogenic origin with fluorescent lidar
International Journal of Remote Sensing - The Remote Sensing Heritage of Academician Kirill Ya Kondratyev
Scaling effect in planetary waves over Antarctica
International Journal of Remote Sensing - The Remote Sensing Heritage of Academician Kirill Ya Kondratyev
International Journal of Remote Sensing
Feasibility of neural network approach in spectral mixture analysis of reflectance spectra
International Journal of Remote Sensing
Automatic smoke detection using satellite imagery: preparatory to smoke detection from Insat-3D
International Journal of Remote Sensing
Global mean values in linear spectral unmixing: double fallacy!
International Journal of Remote Sensing
Two improvement schemes of PAN modulation fusion methods for spectral distortion minimization
International Journal of Remote Sensing
International Journal of Remote Sensing
Remote monitoring of hypersaline environments in San Francisco Bay, CA, USA
International Journal of Remote Sensing
International Journal of Remote Sensing
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The physics laws, which govern the atmospheric phenomena, are mostly non-linear and therefore the application of the conventional Fourier spectral analysis on the time series of the atmospheric quantities reveals that these are usually non-stationary. Quite often these non-stationarities conceals the existing correlations and therefore new analytical techniques capable to eliminate non-stationarities in the data should be employed. The most recent analytical methods used along these lines are the wavelet techniques and the detrended fluctuation analysis. Much attention has been paid recently to the latter technique, which has already proved its usefulness in a large variety of complex systems. As a paradigm, the detrended fluctuation analysis is applied to the column ozone data. Specifically the zonally and globally averaged column ozone observations conducted by ground-based (1964-2004) and satellite-borne (1979-2003) instrumentation are employed to detect long-range correlations in column ozone time series. The results show that column ozone fluctuations exhibit persistent long-range power-law correlations for all time lags between 4 months – 11 years.