PRISMA imaging for land covers and surface materials composition in urban and rural areas adopting multiple endmember spectral mixture analysis (MESMA)

Abstract

Covers and surface materials composition of urban, peri-urban and rural landscapes is significant information for environmental, climate and human-ecosystems interaction monitoring and modeling, as well as for addressing specific urban planning and improving environmental management. In this study the multiple endmember spectral mixture analysis (MESMA) was exploited to overcome the low spatial resolution and spectral mixture of the hyperspectral (HS) satellite PRISMA (PRecursore IperSpettrale della Missione Applicativa). A multi-level detail large-scale mapping of complex urban and rural fractional composition of land covers and surface materials (LCSM) was carried out. High-resolution airborne data enabled the collection of pure endmembers for each impervious and pervious surface materials, also acting as a reference for assessing resulted sub-pixel fractional covers at the pixel scale. Absolute Errors (AE) have shown that MESMA is very promising for quantifying complex landscape composition at the sub-pixel level from PRISMA HS data (overall AE <=0.282; per-class AE < 0.336, with average values ​​even < 0.1 for some classes). Bias Errors (BE) instead attested that under- and overestimation errors for each class were contained in ±0.25 median values for all three levels of detail (i.e., number of classes) tested. These results demonstrate that the proposed framework integrating MESMA and PRISMA HS is a valuable tool to provide detailed land composition in complex landscapes to support urban planning and enhance environmental sustainability.