Obesity and global warming are two major challenges that affect communities’ health and quality of life. Providing good walking environments, with appropriate pedestrian infrastructure, green areas and access to commercial retail and transport hubs favour liveable, healthy, and sustainable cities. The Lisbon City Hall has implemented an intervention program in the public space as a strategy to improve environmental quality and mitigate the effects of climate change. The program “A square in each neighbourhood” intends not only to reinforce the economic base of Lisbon, namely tourism, restaurants, commerce, and creative activities but also to promote physical activity and improve the quality of living of all citizens. For studying the impact of the public space quality on the walking environment, Campolide, a typical Lisbon neighbourhood, Portugal, which includes one of the requalified squares, was selected. A two-step methodology based on spatial modelling is proposed. In the first step, the public space quality was evaluated based on a set of 13 urban quality attributes. Attributes, intended for the street level, were collected from open data platforms and complemented with a field survey. Then, through spatial analysis, these attributes were used to build the Pedestrian Environment Quality Indicator and the Priority Intervention Indicator. Using these indicators, walking-friendly streets were mapped and the most critical sites that require priority intervention were identified to prepare for the requalification planning process. The street with the highest quality in the study area according to the dimensions evaluated - connectivity, convenience, comfort, cleanliness, and conviviality - has a great offer of trees, bus stops, commercial establishments, commercial diversity, crossings, paper bins/eco points and esplanades. On the opposite side of the rank, the street with the lowest quality has no trees or green areas, transport stops, benches and tables, or commercial activity. The urban quality indicators constitute a helpful tool for city planners and policymakers when planning sustainable living neighbourhoods.

Urban resilience assesses a city’s ability to withstand unknown risks. Scholars are not comprehensive in assessing urban resilience, and they lack consideration of population resilience. This study investigated 110 prefecture-level cities in the Yangtze River Economic Belt (YREB) as study areas. We calculated the YREB’s level of urban resilience based on the aspects of “economy-society-population-ecology-infrastructure”, which ensured that the comprehensive evaluation of urban resilience is complete and sufficient. The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data. Geodetectors were used to investigate the impact of several indicators, focusing on economic, social, population, ecological, and infrastructure factors, on urban resilience. The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018, and the average urban resilience of the YREB has risen from 0.2442 to 0.2560. The resilience gap between cities in the study region increased initially and then decreased. The dominant factor in the spatial differentiation of urban resilience was the economic factors, followed by the population factors. Urban resilience has been clarified and an evaluation index system is constructed, which can provide an effective reference for the evaluation of urban resilience among countries around the world. Based on this, factors that optimize urban resilience are configured, and the regional and national sustainable development can be promoted.

Researchers have been trying to identify the contributory factors behind pedestrian crash occurrences through studies at both microscopic and macroscopic levels. However, built environment-related factors have primarily been examined in developed countries, resulting in a limited understanding of the phenomenon in the context of developing countries. Methodologically, these studies mostly used global regression models, which failed to incorporate spatial autocorrelation and spatial heterogeneity. Additionally, some of these studies applied spatial regression models randomly without following a comprehensive logical framework behind their selections. Our study aimed to develop a comprehensive spatial regression modeling framework to examine the relationships between pedestrian crash occurrences and the built environment at the macroscopic level in a megacity, Dhaka, the capital of a developing country: Bangladesh. Using secondary pedestrian crash data, the study applied one global non-spatial model, two global spatial regression models, and two local spatial regression models following a comprehensive spatial regression modeling framework. The factors which significantly contributed to pedestrian crash occurrences in Dhaka were employed person density, mixed and recreational land use density, primary road density, major intersection density, and share of non-motorized modes. Except for the last factor, all the other ones were positively related to pedestrian crash density. Among the five models used in this study, the multiscale geographically weighted regression (MGWR) performed the best as it calibrated each local relationship with a distant spatial scale parameter. The findings and recommendations presented in this study would be useful for reducing pedestrian crashes and choosing the appropriate modeling technique for crash analysis.

Inquiries into rural households’ engagement with smallholder agriculture remain ambiguous and complex. For this reason, research on cultivation patterns has been informed by numerous articles published in recent decades. However, studies detailing the development and progress of deagrarianization remain understudied. In attempts to bridge this knowledge gap, the study aims to provide empirical insights into the trajectories of deagrarianization in South Africa. Studies published between 1996 and 2021 were retrieved from Clarivate Web of Science for analysis. A combination of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and bibliometric analysis was adopted to provide a comprehensive review of deagrarianization dynamics. The findings emphasize that the field of deagrarianization is gaining momentum as publications gradually emerge to indicate that although cultivation is dominant among rural households, there is a reduction in field cultivation and an increase in home-gardening in former homelands of South Africa. Furthermore, common keywords in deagrarianization literature, from a global, African and South African perspective include poverty and livelihoods. Considering that majority of deagrarianization studies analyze patterns, drivers and consequences of the phenomenon, future research needs to consider novel methodologies such as participatory GIS and new avenues that incorporate, but are not limited to, other livelihood issues such as social identities and food security. It is advised that strategies for enhancing rural development and agricultural policies focus on broader solutions that do not only sustain home-gardens but also revitalize both active and abandoned fields.

The Earth is experiencing unprecedented climate change. Vegetation phenology has already showed strong response to the global warming, which alters mass and energy fluxes on terrestrial ecosystems. With technology and method developments in remote sensing, computer science and citizen science, many recent phenology-related studies have been focused on macrophenology. In this perspective, we 1) reviewed the responses of vegetation phenology to climate change and its impacts on carbon cycling, and reported that the effect of shifted phenology on the terrestrial carbon fluxes is substantially different between spring and autumn; 2) elaborated how vegetation phenology affects ecohydrological processes at different scales, and further listed the key issues for each scale, i.e., focusing on seasonal effect, local feedbacks and regional vapor transport for individual, watershed and global respectively); 3) envisioned the potentials to improve current hydrological models by coupling vegetation phenology-related processes, in combining with machine learning, deep learning and scale transformation methods. We propose that comprehensive understanding of climate-macrophenology-hydrology interactions are essential and urgently needed for enhancing our understanding of the ecosystem response and its role in hydrological cycle under future climate change.

Urbanization and Sustainable Development Goals (SDGs) are important global issues in the current “Anthropocene”. Climate change and the COVID-19 pandemic have exacerbated global urban problems and hindered the ability to meet SDGs on time, while the broad interlinkages between urbanization and the SDGs remain poorly understood. This study shows that among the interlinkages of urbanization with 17 SDGs, synergies are observed with 151 targets (89%), among which 67 (40%) have stronger synergies, and trade-offs are observed with 66 targets (39%), among which 31 (18%) have stronger trade-offs. Furthermore, the synergies and trade-offs between urbanization and the achievement of SDGs are specifically analyzed based on four Fundamental interaction fields: (a) public health and social welfare equality; (b) energy consumption and economic growth; (c) natural resource use and ecological/environmental impacts; and (d) international cooperation for development. Finally, based on these analyses, we propose four recommendations for sustainable urbanization, including (a) shared well-being and spatial justice for urban and rural residents; (b) guiding green and low-carbon urban development; (c) building resilient cities; and (d) promoting multilateral cooperation in cities, which can contribute to the achievement of SDGs by 2030.

Using biomass from dedicated crops for energy production and natural vegetation regrowth are key elements in future climate change mitigation scenarios. However, there are still uncertainties about the mitigation potentials that can be achieved by the different land-based systems and how they perform relative to each other. In this study, we use harmonized future land use datasets to identify global land areas dedicated to second generation bioenergy crop production in 2050 under different climate scenarios. We then assess the global climate change mitigation potentials of using biomass for producing bioethanol with (BECCS) or without carbon capture and storage, biochar, or a synthetic fuel (e-methanol). For the latter, the electricity required to produce hydrogen for e-methanol synthesis is sourced from either wind power or the projected average electricity mix in 2050. Mitigation potential from natural regrowth on the identified land is also quantified. For all the cases, we modelled emissions of greenhouse gases from the life-cycle stages and use parameterized models to estimate local biomass growth rates. The identified land areas range from 1.95 to 13.8 million hectares and can provide from 30 to 178 mega ton (Mt) dry biomass annually from dedicated crops. Climate change mitigation potentials range from 11 to 257 MtCO₂-eq. yr⁻¹, depending on technological option and land availability. The largest mitigation is delivered by BECCS, but e-methanol can achieve similar findings when hydrogen is sourced from wind power. If hydrogen is produced from grid electricity, e-methanol can result in net positive emissions. E-methanol can also deliver more final energy than bioethanol (4.04 vs. 1.27 EJ yr⁻¹). Natural vegetation regrowth can generally achieve higher mitigation than bioethanol, but less than biochar. An optimal combination of BECCS and natural vegetation regrowth can achieve a larger mitigation, up to 281 MtCO₂-eq. yr⁻¹, indicating that integrated solutions can help to achieve successful land management strategies for climate change mitigation.

This article aims to show that virtual water has historically been an adaptation strategy that enabled some arid regions to develop a prosperous economy without putting pressure on their scarce water resources. Virtual water is referred to as the total amount of water that is consumed to produce goods and services. As an example, in arid central Iran, the deficiency in agricultural revenues was offset by more investment in local industries that enjoyed a perennial capacity to employ more workers. The revenues of local industries weaned the population from irrigated agriculture, since most of their raw materials and also food stuff were imported from other regions, bringing a remarkable amount of virtual water. This virtual water not only sustained the region’s inhabitants, but also set the stage for a powerful polity in the face of a rapid population growth between the 13th and 15th centuries AD. The resultant surplus products entailed a vast and safe network of roads, provided by both entrepreneurs and government. Therefore, it became possible to import more feedstock such as cocoons from water-abundant regions and then export silk textiles with considerable value-added. This article concludes that a similar model of virtual water can remedy the ongoing water crisis in central Iran, where groundwater reserves are overexploited, and many rural and urban centers are teetering on the edge of socio-ecological collapse. History holds an urgent lesson on sustainability for our today’s policy that stubbornly peruses agriculture and other high-water-demand sectors in an arid region whose development has always been dependent on virtual water.

Some cities worldwide have oil wells directly affecting the management of the territory. For example, La Libertad and Salinas districts contain 467 oil wells in urban areas representing a major land-use planning challenge. The objective is to apply the CLUE-S land use model in coastal cities with oil wells (Salinas-La Libertad), using geographic information systems considering environmental and security characteristics for territorial development. The stages of the study are: i) classification and categorisation of oil wells; ii) application of the GIS-CLUE-S method and visualisation of land use dynamics; iii) use the SWOT-TOWS matrix, for the analysis of the situation and the main factors affecting the territory. The results indicate high vulnerability in many urban sectors and those close to the coastline. Furthermore, the CLUE-S analysis shows that the population growth in the urban sector is close to oil well areas, making it a complex pole of human-industry interaction that impacts the management of the territory. This study synthesises three technical aspects: some oil wells do not comply with municipal ordinance regulations; identification of vulnerable zones due to environmental and security factors, which recommends a territorial reordering policy; as well as an education plan for the application of territorial ordering policies, with awareness and sustainability projections.