Climate change will increase the frequency and severity of hazard events such as heat waves, with important effects in several European regions. It is of importance to consider overall effects as well as specific impact on vulnerable population groups such as outdoor workers. The agricultural and construction sectors represent two strategic occupational fields that in relatively recent years involve an increasing number of migrant workers, and therefore require a better management of cultural aspects, that may interact with and impact on heat-related health risk. For this reason, the present study evaluated heat-stress perception and management among native and immigrant workers in Europe. As part of the EU’s Horizon 2020 HEAT-SHIELD project (grant agreement No. 668786), two agricultural and one construction companies, traditionally employing migrant workers, were evaluated with a questionnaire survey during the summer months of 2017. The data collected (104 case studies) were analyzed using descriptive statistics (Chi-squared tests) and the analysis of variance was performed with ANOVA test. From the results, migrant workers declared that work required greater effort than do native Italian workers (χ² = 17.1, p = 0.001) but reported less impact from heat on productivity (χ² = 10.6; p = 0.014) and thermal discomfort. In addition, migrant workers were mainly informed through written or oral communications, while native workers received information on heat-health issues through training courses. These findings are of importance for future information and mitigation actions to address socio-cultural gaps and reduce heat-stress vulnerability.

One of many possible climate change effects in temperate areas is the increase of frequency and severity of windstorms; thus, fast and cost efficient new methods are needed to evaluate wind-induced damages in forests. We present a method for assessing windstorm damages in forest landscapes based on a two-stage sampling strategy using single-date, post-event airborne laser scanning (ALS) data. ALS data are used for delineating damaged forest stands and for an initial evaluation of the volume of fallen trees. The total volume of fallen trees is then estimated using a two-stage model-assisted approach, where variables from ALS are used as auxiliary information in the difference estimator. In the first stage, a sample of the delineated forest stands is selected, and in the second stage the within-stand damages are estimated by means of line intercept sampling (LIS). The proposed method produces maps of windthrown areas, estimates of forest damages in terms of the total volume of fallen trees, and the uncertainty of the estimates. A case study is presented for a large windstorm that struck the Tuscany Region of Italy the night of the 4th and the 5th of March 2015 and caused extensive damages to trees in both forest and urban areas. The pure field-based estimates from LIS and the ALS-based estimates of stand-level fallen wood were very similar. Our positive results demonstrate the utility of the single-date approach for a fast assessment of windthrow damages in forest stands which is especially useful when pre-event ALS data are not available.