The Urban Heat Islands (UHI) effect is a microclimatic phenomenon that especially affects urban areas. It is associated with significant temperature increases in the local microclimate, and may amplify heat waves. Due to their intensity, UHI causes not only thermal discomfort, but also reductions in the levels of life quality. This paper reviews the important role of green infrastructure as a means through which the intensity of UHI may be reduced, along with their negative impact on human comfort and wellbeing. Apart from a comprehensive review of the available literature, the paper reports on an analysis of case studies in a set of 14 cities in 13 countries representing various geographical regions and climate zones. The results obtained suggest that whereas UHI is a common phenomenon, green infrastructure in urban areas may under some conditions ameliorate their impacts. In addition, the study revealed that the scope and impacts of UHI are not uniform: depending on peculiarities of urban morphologies, they pose different challenges linked to the microclimate peculiar to each city. The implications of this paper are threefold. Firstly, it reiterates the complex interrelations of UHIs, heat waves and climate change. Secondly, it outlines the fact that keeping and increasing urban green resources leads to additional various benefits that may directly or indirectly reduce the impacts of UHI. Finally, the paper reiterates the need for city planners to pay more attention to possible UHI effects when initiating new building projects or when adjusting current ones.

As global warming continues to intensify, the relationship between diurnal temperature range (DTR) and vegetation productivity continues to change over time. However, the impact of DTR changes on vegetation activities remains uncertain. Thus, further study about how DTR changes affect the physiological activities of plants is also urgently needed. In this study, we employed copula function theory to analyze the impact of DTR on Normalized Difference Vegetation Index (NDVI) values during the spring, summer, and autumn seasons from 1982 to 2014 for various land types in the Inner Mongolia Plain (IMP), China. The results showed that the relationship between DTR and NDVI in the IMP was characterized by correlation at the upper tail and asymptotical independence at the lower tail. This demonstrated that the DTR had little effect on NDVI when they reached their minimum value. However, it has a significant impact on NDVI at its maximum values. This study provides valuable insight into the dynamic impact of monthly DTR on different land use types under climate change.

The entire cascade of scenario generation, global and regional climate modeling, as well as concrete measures towards climate adaptation are subject to uncertainties. An exact prediction of how the climate will change in the coming years, and how it will affect land use, is not possible. There is thus a perceived need to identify ways via which uncertainties can be addressed. Based on the need to address the research gap in this area, this paper reports the findings of a study on uncertainty in a climate change adaptation context, and how it is perceived. It consists of a multi-stakeholder survey among climate change professionals, including academic staff at universities, representatives from international agencies, members of NGOs, policymakers, and representatives of industry from 50 countries, including a balanced representation of industrialized and developing nations. The results obtained suggest that uncertainties are often a hindrance to engagement in climate change adaptation efforts, and to land management. Furthermore, there is a range of tools to reduce climate change adaptation uncertainties, whose deployment may help to address them. The paper concludes by providing a list of lessons learned and suggestions as to how uncertainty can be better communicated, and by doing so, how a reduction in the levels of climate change vulnerability may be achieved, and how land management may be fostered.

Using GIMMS NDVI3g+ data (1982–2022) together with ERA5-Land temperature and precipitation, this study examined long-term vegetation dynamics in the Indus River Basin (IRB) and used a residual trend framework for cautious first-order attribution. Basin-averaged NDVI increased significantly at 0.0061 per decade (p < 0.05), and 65.5% of the basin showed greening, mainly in irrigated croplands and river-adjacent agricultural zones, whereas 12.6% showed degradation concentrated in rapidly urbanizing areas, cryosphere margins, and desert fringes. Partial correlation and residual analyses indicate that climate-related enhancement was most evident in upper-elevation cryosphere transition zones and some lower-basin barren lands, whereas non-climatic residual effects were especially important in intensively managed agricultural landscapes. Because the attribution model includes only temperature and precipitation, the residual component is interpreted here as a non-climatic residual rather than a direct measure of human activity. The study, therefore, provides a spatially explicit basin-wide assessment of vegetation change while highlighting the uncertainty and interpretation limits of residual-based attribution.