Acid-saline sediments in shallow-lake environments in southwestern Australia host complex mineralogical suites representing long-term weathering and modern extreme acid saline chemistry. It is not known whether large-scale reflectance spectroscopy datasets from watersheds across the Yilgarn Craton show regional mineralogical variability. This study assesses over 2,500 spectra from datasets of shallow subsurface sediments by using automatic minima detections for spectral features of interest. Integrating microscopic and spectral observations show that proportionally similar mineral assemblages exist in a variety of recognizable textures. Spectral results indicate iron oxide and phyllosilicates are the most detected mineral types, alongside less common alunite, jarosite, and gypsum. The difference in detection abundance by percentage for mineral groups, particularly iron oxides, accounts for the largest regional variation observed in spectra. Spectral feature characteristics show significant regional variation for iron oxide, alunite, and hydrated mineral absorptions. The spectral observations align with previous mineralogical observations of these landscapes and the expected weathering evolution for granitoids, where Al-phyllosilicates and iron oxides are most prevalent. Observations of these mineral suites enhance understanding of regional differences and similarities in chemical precipitates and products of water-rock interaction in extreme acid-saline environments and have implications for studying sediments and rocks on Mars.

The Bonneville Salt Flats (BSF) of Utah, with a notable history in land-speed racing and resource extraction, presents a dynamic landscape shaped by both natural processes and anthropogenic activities. This study leverages Interferometric Synthetic Aperture Radar (InSAR) techniques to monitor the BSF, focusing on the potential of coherence as an indicator of surface changes. A total of 165 Sentinel-1 A&B coherence images, with perpendicular baselines under 100 meters and temporal baselines of 12, 24, and 36 days, were analyzed using spatially and temporally reduced statistics, along with median absolute deviation variance. The findings demonstrate consistently high coherence (>0.90) during dry conditions, contrasted by significantly lower coherence (<0.40) during periods of precipitation and flooding. Coherence showed moderate reduction (<0.70) in zones of recreational activities (driving & racing), highlighting the relative impact of land-use activities on the salt crust. Coherence observations indicate minimal difference during periods overlapping with and following official racing events compared to periods of racetrack preparation and general recreational use. Zones with the highest variability are linked to disturbances from recreation and resource extraction, while areas with minimal variability correspond to regions with thicker halite crust. The data also revealed that large precipitation events significantly influence coherence, with a clear power-law decrease in mean coherence as precipitation and floodwater accumulation increased. This research not only validates the use of coherence for monitoring environmental evolution and the influences of anthropogenic activities at the BSF but also supports the potential of future InSAR applications for accurate phase assessments during dry periods.

RadGEEToolbox is an open-source Python package for processing and analyzing multispectral and Synthetic Aperture Radar (SAR) imagery using Google Earth Engine (Gorelick et al., 2017). It supports Landsat TM/OLI, Sentinel-1 SAR, and Sentinel-2 MSI datasets, with plans to support additional platforms in the future (MODIS, VIIRS, etc). RadGEEToolbox provides a modular, streamlined workflow for landscape change detection, environmental monitoring, and land classification. It reduces the need for repetitive code while promoting reproducibility and efficiency. Features include subsetting,

The Bonneville Salt Flats (BSF) in northwestern Utah, USA, has experienced changes in area, thickness, and hydrology over the past century. This study investigates the relationship between multispectral Halite Index (HI) values, which are sensitive to halite moisture content, from Landsat and Sentinel‐2 imagery and groundwater depth (GWD) measured by nine piezometers, based on the principle that surface moisture in the halite crust is driven primarily by depth of groundwater and secondarily by atmospheric precipitation or humidity. Linear regressions reveal moderately strong correlations, and regression coefficients are used to calibrate HI values to GWD. Satellite‐calibrated GWD time series show temporal alignment with piezometer records, with a median absolute deviation less than 15 cm for seven of the nine piezometers. Spatial interpolations of regression coefficients are used to calibrate HI imagery to GWD imagery, highlighting the groundwater table's spatiotemporal variability and relation to climate. Groundwater depth is observed to be very sensitive to climatic conditions, as GWD across the crust scales with Palmer Drought Severity Index data. The methodology is tested for available piezometer data at the Badwater Basin, Salar de Uyuni, and Salar de Atacama to explore global applicability. The results from this study confirm the potential of multispectral remote sensing for monitoring GWD at the BSF and suggest the methodology could be transferable to similar salt crusts globally.