The expansion of bare sand surfaces indicates a tendency towards desertfication in certain periods as a result of the improper agricultural use of sand soils and of the significant changes in the climate in the past 30 years. The Normalised Sand Index (NSI) is a new index used to identify bare sand areas and their spatio-temporal evolution in SW Romania. Landsat scenes (1988, 2001, 2019), spectral and soil texture analysis (36 samples), covariates (e.g., soil map), and field observations allowed for the validation of the results. The performance of the NSI was compared with indices from the sand index family (e.g., Normalized Differential Sand Areas Index) and supervised classifications (e.g., Maximum Likelihood Classification) based on 47 random control square areas for which the soil texture is known. A statistical analysis of the NSI showed 23.6% (27,310.14 hectares) of bare sands in 1988, followed by an accelerated increase to 47.2% (54,737.73 hectares) in 2001 because of economic and land-use changes, and a lower increase by 2019, which reached 52.5% (60,852.42 hectares) due to reforestation programs. Compared to the NSI, the bare sand areas obtained with the tested indicator were almost 20% higher. The traditional classification shows smaller areas of bare sands but uses a higher complexity of land use classes, while the producer accuracy values are lower than those of the NSI. The new index has achieved a correct spatial delimitation of soils in the interdune-dune and major riverbed-interfluvial areas, but it is limited to the transition Arenosols-Chernozems by humus content and agrotechnical works. The new spectral index favours bare sand monitoring and is a fast and inexpensive method of observing the desertification trend of temperate sandy agroecosystems in the context of climate change.

Soil researchers are interested in a gaining better understanding of the soil system state by analyzing its properties and their dynamics in time as well as in relation to land use change. Tilled, abandoned, and forest soils were assessed regarding attribute–response relationships for the bulk density (BD), total porosity (TP), volumetric moisture (θv), and penetration resistance (PR) with the use of the interquartile ratio (IRI) integrated into a resilience formula and Shannon entropy indices. The IRI results differentiated soil properties according to agrotechnics (wheel track vs. between wheels) and the state of the system (tilled vs. abandoned vineyard). Entropy (En) indicated a high level of uncertainty for PR. The linear regression applied to the pairs of BD-TP, TP-θv, and PR-θv showed better results for the IRI weight (IRI_weight) compared to the entropy weight (En_weight) for the soil between the wheels. The soil of the abandoned vineyard showed a faster tendency toward resilience that was more pronounced in the tilled wheel tracks than in the area between the wheels. The IRI can thus be an alternative to entropy in the evaluation of the response of some soil properties according to their use. When integrated into a resilience formula, the IRI can estimate the dynamics of soil properties for abandoned land compared to reference soil.

The concentrations of PTEs and Fe₂O₃ increase from the sand fraction to the silt fraction, although the magnitude of this increase is not uniform (Zn > Cu > As > Pb), while SiO₂ content is not affected by particle size. In general, PTE concentrations are lower in wet samples than in dry samples. The ratio of the element concentration in the wet sample to that in the air-dried sample, together with the gravimetric moisture content (%), were plotted in central scatter plots, which allowed the identification of outliers. The inverse relationship observed between the concentration of certain elements and moisture content may be explained by the geochemical characteristics of the sample. Moisture in both manually and mechanically ground samples influences analytical ac-curacy, even when the processing time is identical. Triplicate samples indicate small-scale heterogeneity driven by post-depositional alteration of the tailings, as well as element associations (e.g., Fe₂O₃–As) dictated by the mineralogical composition of the source material (e.g., arsenopyrite).