From Multispectral to Hyperspectral: Cross-Sensor Intercomparison of Spectral Characteristics and Diversity Estimation in the Åmose Wetland Restoration Landscape

Imaging spectroscopy has become an essential tool for biodiversity monitoring, enabling the characterization of ecosystem composition, function, and diversity through spectral information, grounded in the spectral variation hypothesis. However, the growing diversity of sensors and platforms introduces both new opportunities and challenges for consistent biodiversity assessment from local to global scales. Differences in spectral resolution, spatial resolution, and signal-to-noise ratio can substantially affect the measured spectral response of the earth’s surface and, consequently, the estimation of spectral diversity. To address these issues, this study conducts a systematic cross-sensor comparison focusing on emerging spaceborne hyperspectral systems (PRISMA and EnMAP), the spaceborne multispectral system (Sentinel-2), and the airborne imaging spectrometer (AVIRIS-4), aiming to evaluate differences in spectral characteristics and diversity estimation for long-term and large-scale biodiversity monitoring. Specifically, a multi-source reflectance dataset was acquired over the Åmose wetland restoration landscape in Denmark in August 2025 and processed with BRDF and geometric co-registration corrections to eliminate undesired view-sun-angle and geometric differences between sensors. Then, spectral intercomparison was performed both for images before and after BRDF correction under unified spatial and spectral resolution by extracting reflectance spectra from several representative land use classes (including nature, intensive agriculture, extensive agriculture, coniferous forest, deciduous forest, water, and built-up) to identify reliable wavelength ranges for subsequent spectral diversity estimation. For the spectral diversity estimation, the high-resolution AVIRIS-4 data (1 m) were resampled to multiple coarser resolutions (e.g. 10, 20, 30, and 60 m). Spectral diversity metrics were computed at each resolution and compared with corresponding spaceborne sensors (PRISMA and EnMAP at 30 m and Sentinel-2 at 10 m and 20 m), revealing how spatial scale and sensor characteristics influence the estimation of spectral diversity. In addition, uncertainty analysis was employed to quantify the variability and assess the reliability of both spectral intercomparison and diversity estimation. In general, this study provides a framework for clarifying the differences in spectral response and spatial resolution of promising sensors for spectral diversity estimation to support consistent biodiversity monitoring. The outcomes contribute to the development of standardized approaches for cross-sensor spectral diversity estimation and uncertainty reduction in next-generation remote sensing of biodiversity.