Articles | Volume 24, issue 2
Nonlin. Processes Geophys., 24, 141–155, 2017

Special issue: Multifractal analysis in soil systems

Nonlin. Processes Geophys., 24, 141–155, 2017
Research article
16 Mar 2017
Research article | 16 Mar 2017

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

Carmelo Alonso et al.

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Cited articles

Aguado, P. L., Del Monte, J. P., Moratiel, R., and Tarquis, A. M.: Spatial Characterization of Landscapes through Multifractal Analysis of DEM, The Scientific World Journal, 2014, 563038,, 2014.
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Ben-Ze'ev, E., Karnieli, A., Agam, N., Kaufman, Y., and Holben, B.: Assessing Vegetation Condition In The Presence Of Biomass Burning Smoke By Applying The Aerosol-Free Vegetation Index (AFRI) On MODIS Images, Int. J. Remote Sens., 27, 3203–3221, 2006.
Carlson, T. N. and Ripley, D. A.: On the relation between NDVI, Fractional Vegetation Cover, and Leaf Area Index, Remote Sens. Environ., 62, 241–252, 1997.

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
NDVI and EVI vegetation indexes, estimated from satellite images, can been used to estimate root zone soil moisture. However, depending on the spatial and radiometric resolution of the sensors used, estimations could change. In this work, images taken by satellites IKONOS-2 and LANDSAT-7 of the same location are compared on the four bands involved in these vegetation indexes. The results show that spatial resolution has a similar scaling effect in the four bands, but not radiometric resolution.