## 1 Introduction
The latter are retrieved either from spectral libraries [1; 2; 3; 4; 5; 6] or they are extracted from the image itself by detecting the relatively \"purest\" pixels (corresponding to physical materials) via suitable algorithms [8; 9; 12; 14; 15; 16; 17; 18; 19]. SU results in a set of fractions (abundances) images, which indicate the degree of presence of each endmember within each pixel. It should be noted here that, in contrast to the SI \"scalar\" rationale, the vector-based processing in SU provides richer representational capabilities. It is clear that the ultimate success of SU depends heavily on the appropriate selection of endmembers. Although several SU approaches have been proposed in literature, when working with multispectral images, the most widely used are those adopting the linear mixing model (LMM), where the spectral signature (vector) of each pixel is assumed to be expressed as a linear combination of a set of endmember signatures (vectors). The coefficients (abundances) of this combination can be estimated through various unmixing procedures, such as the constrained/unconstrained least squares methods [65]. Focusing on the study of hydrothermal alteration zones, several SU approaches have been proposed such as partial unmixing (e.g., Matched Filtering (MF), Mixture Tuned Matched Filtering (MTMF), Constrained Energy Minimization (CEM) algorithms, etc.) [8; 17; 20] and the full spectral unmixing [13]. Most of these studies assume constrained linear spectral unmixing models, imposing positivity and/or sum-to-one constraints [7; 8; 13; 14; 20]. However, studies that utilize the unconstrained version of LMM have also showed efficient results [9; 11; 22; 23]. In literature, spectral unmixing has been applied to map hydrothermal alteration using both multispectral and hyperspectral data. Concerning multispectral data, most relevant studies employ ASTER data [7; 8; 9; 10; 11; 12; 13; 17; 20; 21; 22; 23; 66; 67] and few studies employ Landsat-8/OLI data [14; 15; 66] while very few employ Sentinel-2 MSI data [16; 66]. However, these studies mainly concern mapping of alteration mineralogy. The aim of the present study was to propose a methodology based on spectral unmixing that provides a detailed description of the argillic zone of a hydrothermal field. More specifically, we developed a method based on spectral unmixing where argillic alteration is represented by a single endmember (representing clays) and the (nearly) non-altered primary volcanic lithologies, namely two lava flows types (basic and acidic compositions) and loose materials (alluvial/beach deposits, scree, pyroclastic deposits), are represented by three endmembers. We also use one endmember representing elemental sulfur that is present in fumarolic vents hosted by the active hydrothermal craters. The proposed methodology was applied in the south part of Lakki plain inside the Nisyros volcano caldera (Greece) using Sentinel-2 MSI, Landsat-8/OLI, and ASTER satellite multispectral data. Specifically, it was applied separately to each one of the three datasets. The evaluation of the results was conducted on the basis of the only available reference information about the alteration in this area, which is a sketch map provided by [68]. The sketch map was digitized and georeferenced to a relative classification map. The novelty of the present study relies on (1) the methodology proposed, (2) the production of a map of the hydrothermal field of the Nisyros caldera, and (3) the provision of quantitative estimations of the primary volcanic lithologies' areas in the Nisyros caldera affected by alteration and the areas of specific lithost stratigraphic units affected by strong alteration. The present paper is organized as follows. Section 2 focuses on the description of the study area presenting the general geological background and the structure of the hydrothermal field within the caldera of the Nisyros volcano. Section 3 describes the three under-examination multispectral datasets from ASTER, Landsat-8/OLI, and Sentinel-2 satellites.