Towards a Semantic Sensor Spectral Data Framework: A Case for In-Situ Water Spectroradiometry

Spectral data are crucial for optical remote sensing, serving to calibrate and validate satellite data, as well as to generate models for biophysical and geo-physical variables. This data, essential for the growing field of hyperspectral geospatial data from sensors like PRISMA, enMAP, and PACE, can be sourced from in-situ measurements, laboratory data, and radiative transfer models. However, without a systematic way for data annotation and sharing, the valuable data generated by different observation missions remain isolated in data silos with few chances to be reused by others stakeholders. In this paper, we present an application ontology for managing observation data considering the full pipeline of the underlying measurement campaigns. The ontology is proposed as a key part of a Semantic Sensor Web (SSW) platform for FAIR-complaint data sharing. The proposal is based on the Semantic Sensor Network (SSN) ontology and meets World Wide Web Consortium (W3C) and Open Geospatial Consortium (OGC) standards like SensorML, O&M or GeoSPARQL. The presented approach is envisioned to support others observational projects beyond water quality, encompassing vegetation, minerals, and snow, among others, for various spectral data sources.