Scientific Applications of Imaging Spectroscopy from Laboratory to Spaceborne Observation Scale

Dear Colleagues,

In recent years, imaging spectroscopy or hyperspectral imaging (HSI) has found its way into many fields of research covering environmental and agronomical sciences, crops, forests, food science, natural sciences, medicine/biomedicine or material science. Newly developed scientific applications are fundamentally based on information retrieved from the hyperspectral data cube with three dimensions (two spatial and one spectral) taken entirely at one time (snapshot) or in parts in a very short collection time (scanning technology). The spectral dimension with dozens or hundreds of narrow spectral bands usually leads to continuous, non-spaced spectral measurements with a high sensitivity even to variables with limited spectral implications. In addition, HSI facilitates applications with spatially and, in the case of repeated measurements, temporally detailed data.

HSI is able to cover a large variety of observation scales ranging from hyperspectral microscopy imaging to spaceborne remote sensing. Close-range imaging instruments, either hand-held or tripod-mounted, support field studies even with challenging observation conditions, for example, the mapping of mainly vertical-oriented outcrops or soil profiles. The development of miniaturized hyperspectral sensors has fostered applications related to data acquisition with lightweight unmanned aerial vehicle (UAV) platforms. Spaceborne hyperspectral data acquisitions from earth observation satellite platforms (e.g., Hyperion on-board the EO-1 satellite, decommissioned in 2017, or the currently operational PRISMA and EnMAP satellites) allow for a wide range of applications in the fields of, for example, ecosystem research, agriculture, forestry, water management, geology or soil science, although spatially limited by the 30 m pixel size.

In view of the current developments in HSI, this Special Issue calls for studies from all research fields in which HSI plays a major role as the data source. The aim is to get a fresh insight into strategies and techniques of laboratory close-range, proximally as well as remotely sensed hyperspectral data acquisition, processing workflows, data mining and interpretation. Special focus is on, but is not limited to, the following topics:

• Technical aspects of HSI data acquisition also in combination with other instruments (multi-sensor data), allowing for data fusion and appropriately developed data analysis strategies;
• Statistical and computational methods (including machine- and deep-learning) for image analysis;
• Innovative applications intrinsically coupled to the specific hyperspectral data dimension and with a deep understanding of the physical principles behind the image exploitation;
• Scaling effects with a systematic consideration of different image acquisition scales and concepts of upscaling/downscaling mechanisms;
• Subpixel mapping methods exploiting the hyperspectral data dimension.

Prof. Dr. Michael Vohland
Dr. András Jung
Prof. Dr. Marion Pause
Guest Editors

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• hyperspectral imaging
• high-resolution imaging spectroscopy
• close-range
• proximal and remote sensing
• hyperspectral image analysis
• machine learning and data mining
• multi-sensor concepts
• subpixel analysis