The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing number of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9 and Sentinel-2, and planned future missions, like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA)’s Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from reference systems to client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.

Detecting changes in coral and seagrass habitat composition from satellite imagery places exceptionally high demands on sensor design due to low underwater reflectance signals and variable water column conditions. Recent multispectral satellite-based attempts to assess such changes across large spatial extents illustrate this challenge through an inability to reliably distinguish live coral from algae, often resulting in broad confidence intervals. This study quantifies the radiometric sensitivity requirements for detecting 10% absolute changes in live coral and seagrass fractional cover from spaceborne imaging spectroscopy using representative parameters for an aquatic imaging spectrometer. The analysis combined representative benthic spectra with realistic, management-relevant co-occurrence scenarios informed by extensive regional knowledge and field measurements from Fiji, Australia, and the Solomon Islands to evaluate detection performance across depths from 0 to 30 m. We show that live coral is the most demanding of the benthic targets evaluated because of its low reflectance and spectral similarity to algal cover types, requiring SNRs of approximately 300–700 to detect 10% absolute changes in cover at depths up to 10 m. In contrast, the greater spectral separation between seagrass and adjacent sandy substrates allows detection of 10% absolute changes in cover to depths exceeding 20 m in clear water. These results highlight the importance of high radiometric sensitivity and contiguous spectral sampling for future aquatic imaging spectrometers intended to monitor benthic change. Approaches that increase effective SNR, such as ground motion compensation (GMC), can extend the depth and confidence with which changes in benthic composition are detected, supporting a transition from broad-area habitat mapping toward quantitative monitoring of benthic change from space.

The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing constellation of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9, Sentinel-2, and planned future missions like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA) Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from Reference systems to Client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.

While remote sensing has been widely used to estimate vegetation biochemical and structural properties, relatively little work has systematically and experimentally linked vegetative fuel spectral reflectance to independently measured fuel combustibility, free-spreading fire behaviour, and fire emissions. This limits the development and validation of remote sensing products for operational wildland fire applications. We present a pilot-study evaluation of an experimental method that integrates imaging spectroscopy with free-spreading fires in a combustion wind tunnel to investigate relationships between wildland fuel spectral reflectance and combustibility, fire behaviour, and fire emissions. The pilot study used three common Australian fuels at two combustibility levels. Pre- and post-burn imaging spectroscopy observations (400–2500 nm) were collected during 26 experiments, alongside measurements of fuel biochemistry, calorimetry, moisture, rate of spread, combustion efficiency, and gaseous and particulate emissions. Statistically significant differences between fuel type and combustibility were found in fuel moisture, rate of spread, and emissions, with corresponding differences evident in the spectral signatures. Partial least squares regression (PLSR) indicated that pre-fire spectral information was informative for predicting several fire behaviour and emissions metrics. These results demonstrate the feasibility of the proposed methodology and provide a foundation for extending it to a wider range of wildland fuels. Data generated using this methodology have the potential to improve interpretation of remote sensing datasets and inform the design of future satellite instruments, with potential applications in assessing fuel condition, predicting fire behaviour, and estimating wildland fire emissions.