Open AccessDifferentiating geology and tectonics using a spatial autocorrelation technique for the hypsometric integral
Author(s) -
PérezPeña J. V.,
Azañón J. M.,
BoothRea G.,
Azor A.,
Delgado J.
Publication year - 2009
Publication title -
journal of geophysical research: earth surface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2008jf001092
Subject(s) - geology , tectonics , structural basin , lithology , digital elevation model , spatial analysis , spatial distribution , elevation (ballistics) , seismology , geomorphology , landform , paleontology , remote sensing , geometry , mathematics
Hypsometry is thought to be sensitive to tectonic uplift rates and lithology differences. In this study we calculated hypsometric integrals (HIs) using as topographic sources two digital elevation models of 10 and 90 m of pixel resolution in the Granada basin (SE of Spain). The HI spatial distributions do not show clear spatial patterns and do not correlate with basin parameters as mean elevation or relief amplitude. However, when exploratory spatial data analysis is applied to the data distributions through local indices of spatial autocorrelation, clear hot spots are visible that improve the geologic meaning of the HI. The distributions are robust and independent of the model resolution but are scale influenced. The application of this new method to the Granada basin shows a strong correlation between the main distribution of active normal faults in the basin and the clusters of high or low HI values obtained in our analysis. Clusters with high HI values define the uplifted footwalls of these faults and regions uplifted in relation with rollover anticlines or where epeirogenic uplift has not been counteracted by local extension. Once the method was adjusted in the Granada basin, we tested its applicability in an area of known contractive tectonic activity, central Otago, New Zealand, showing that the meaning of HI values is improved by using the autocorrelation techniques.