Multifractal analysis for spatial characterization of high resolution Sentinel-2/MAJA products in Southwestern France

Abstract

Multifractal analysis was applied to evidence spatial properties, in particular scaling behaviour, of Sentinel-2 surface reflectances and optical indexes acquired over the Southwest region of France. Considering the significant impact of clouds on the spatial properties of optical products, no study to our knowledge has focused on the multifractal analysis of a series of images. Images with minimal cloud cover were identified for the whole year 2016 based on the MACCS-ATCOR Joint Algorithm (MAJA) cloud and shadow detection process. This allowed us to access the dynamics of the scaling properties of surface reflectances, contributing to demonstrate the potential of multifractals for spatial characterization. Different scaling regimes, separated by significant scale breaks, were evident in these data. Through simulations from the Universal Multifractal model, we could explain the scaling properties and especially the position of scale breaks observed in the images studied by two types of phenomena. First, a transition scale located between hundreds of meters and one kilometre was detected on power spectra, structure functions and statistical moments. This specific scale was related to the average size of the agricultural plots of the studied region, revealing the direct link between the scaling behaviour observed and the physical properties of the surface. Second, an instrumental phenomenon was detected on the power spectra, resulting in a systematic transition scale observed near the resolution of the sensor and revealing the impact of the acquisition system on the high frequencies of optical images. In this research work, theoretical and/or empirical validation arguments were provided as to the origin of the scales detected, contributing to demonstrate the value of multifractals to extract image texture from surface reflectance products.