The ablative material ZURAM has been developed by the German Aerospace Center DLR. It is manufactured from a rigid carbon felt impregnated with phenolic resin. It has a low density of approximately 0.36 -0.4 g/cm³. Arc jet tests were carried out up to heat fluxes of 13.5 MW/m² indicating the potential of the material with recession rates of approximately 0.3 mm/s. To characterize the material in detail to facilitate the design for space vehicles, the complete set of thermal and mechanical material properties has to be established. This paper will present the determination of the mechanical properties related to the microstructure. A characterization in tension, compression and shear was carried out resulting in the respective moduli and strength values. It was found that the material has an anisotropic behavior. Since the material is rather delicate in comparison to other structural materials, stress and strain measurements were in part also based on optical measurements to not disturb the material response.

Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) in global drylands. They consist of poikilohydric organisms capable of adjusting their metabolic activities depending on the water availability. However, they, and with them, their ecosystem functions, are endangered by climate change and land-use intensification. Remote sensing (RS)-based studies estimated the BSC cover in global drylands through various multispectral indices, and few of them correlated the BSCs’ activity response to rainfall. However, the allocation of BSCs is not limited to drylands only as there are areas beyond where smaller patches have developed under intense human impact and frequent disturbance. Yet, those areas were not addressed in RS-based studies, raising the question of whether the methods developed in extensive drylands can be transferred easily. Our temperate climate study area, the ‘Lieberoser Heide’ in northeastern Germany, is home to the country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating multispectral Sentinel-2 (S2) data, indices derived from them, and topographic information to spatiotemporally map the BSC cover for the first time in Central Europe. We further monitored the BSC response to rainfall events over a period of around five years (June 2015 to end of December 2020). Therefore, we combined datasets of gridded NDVI as a measure of photosynthetic activity with daily precipitation data and conducted a change detection analysis. With an overall accuracy of 98.9%, our classification proved satisfactory. Detected changes in BSC activity between dry and wet conditions were found to be significant. Our study emphasizes a high transferability of established methods from extensive drylands to BSC-covered areas in the temperate climate. Therefore, we consider our study to provide essential impulses so that RS-based biocrust mapping in the future will be applied beyond the global drylands.

Although inclusion is the declared goal, the transition from a system based on special schools to an inclusive school system has only been progressing very slowly in individual countries. In an evolving school system, the existing special schools keep struggling to justify their existence. This study investigates the regional distribution effects based on official school data and shows the influence of a pull effect on special schools as a distance effect of special schools affecting the placement of students. For this purpose, official school statistics including all students at special and regular schools in the years 2010, 2015 and 2020 (N = 11 280 040) are evaluated in a spatiotemporal comparison using Educational Data Mining. In a hierarchical regression model on school placement in inclusive schools, the distance between primary and special schools has the highest influence (β = 0.48) on the inclusion rate (i.e., the proportion of students with special needs who are educated in regular schools in relation to all students with disabilities), along with the size (β = −0.14) and the density of special schools in a district (β = −0.12). The effects differ according to the population density of the region and are stronger in large cities. When the proportion of students with and without SEN in regular schools is considered (support rate), the density of special schools has the greatest impact on school placement (ß = 43.44). Self‐preservation of schools, traditional funding systems and regional differences between urban and rural areas are discussed as possible reasons.

On a daily basis, political decisions are made, often with their full extent of impact being unclear. Not seldom, the decisions and policy measures implemented result in direct or indirect unintended negative impacts, such as on the natural environment, which can vary in time, space, nature, and severity. To achieve a more sustainable world with equitable societies requires fundamental rethinking of our policymaking. It calls for informed decision making and a monitoring of political impact for which evidence-based knowledge is necessary. The most powerful tool to derive objective and systematic spatial information and, thus, add to transparent decisions is remote sensing (RS). This review analyses how spaceborne RS is used by the scientific community to provide evidence for the policymaking process. We reviewed 194 scientific publications from 2015 to 2020 and analysed them based on general insights (e.g., study area) and RS application-related information (e.g., RS data and products). Further, we classified the studies according to their degree of science–policy integration by determining their engagement with the political field and their potential contribution towards four stages of the policy cycle: problem identification/knowledge building, policy formulation, policy implementation, and policy monitoring and evaluation. Except for four studies, we found that studies had not directly involved or informed the policy field or policymaking process. Most studies contributed to the stage problem identification/knowledge building, followed by ex post policy impact assessment. To strengthen the use of RS for policy-relevant studies, the concept of the policy cycle is used to showcase opportunities of RS application for the policymaking process. Topics gaining importance and future requirements of RS at the science–policy interface are identified. If tackled, RS can be a powerful complement to provide policy-relevant evidence to shed light on the impact of political decisions and thus help promote sustainable development from the core.