A three-year study, designed to record the level of potentially toxic elements within the urban complex in the city of Volos, Greece, was carried out between 2018 and 2020. For the needs of the aforementioned study, 62 surface (0–15 cm) soil samples were collected each year (i.e., 186 samples in total) from an urban area of 3.65 km², and the average value of pseudo-total metal concentration was measured. Soil pollution indices, such as the contamination factor (CF) and the geo-accumulation index (Igeo), were estimated regarding each of the metals of interest. The respective thematic maps were constructed, and the spatial variability of the contamination degree was displayed. Higher values of the CF and Igeo were obtained near the heavy traffic roads and beside the railway station, the bus stations, and the commercial port. The maps based on the pollution indices, along with the database that was constructed using the appropriate mathematical tools of geostatistical analysis, may be a useful tool for monitoring, prediction, and continuous verification of contamination in the urban soils of Volos city.

In this study, a modelling approach for the estimation/prediction of wheat yield based on Sentinel-2 data is presented. Model development was accomplished through a two-step process: firstly, the capacity of Sentinel-2 vegetation indices (VIs) to follow plant ecophysiological parameters was established through measurements in a pilot field and secondly, the results of the first step were extended/evaluated in 31 fields, during two growing periods, to increase the applicability range and robustness of the models. Modelling results were examined against yield data collected by a combine harvester equipped with a yield-monitoring system. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were examined as plant signals and combined with Normalized Difference Water Index (NDWI) and/or Normalized Multiband Drought Index (NMDI) during the growth period or before sowing, as water and soil signals, respectively. The best performing model involved the EVI integral for the 20 April–31 May period as a plant signal and NMDI on 29 April and before sowing as water and soil signals, respectively (R² = 0.629, RMSE = 538). However, model versions with a single date and maximum seasonal VIs values as a plant signal, performed almost equally well. Since the maximum seasonal VIs values occurred during the last ten days of April, these model versions are suitable for yield prediction.