Chilean geography exposes the country to high-level risks such as earthquakes and tsunamis. The disasters of 1930, 1960, 2010, and 2014 testify to the continuous link between human survival and disasters. However, new hazards have appeared ever since -i.e. flood waterlogging, wildfires, and landslides-, highlighting the relationship between current land uses and space occupation with increasing levels of disaster risk. This research aims to determine relations and responsibilities of the Chilean developmental approach in urban planning and territorial governance processes that have created new territories prone to disaster risk. We resort to a longitudinal analysis from 1930 to 2018 at the Gran Concepción metropolitan area as a proxy of Chilean industrialization and economic development approaches. To do so, we developed mixed-approach descriptive research, for which we collected data from national development policies and documented land occupation processes during pre-dictatorship, dictatorship and post-dictatorship periods. Semi-structured interviews with decision-makers involved in current territorial policy were also carried out. The findings show how territorial governance resulted from political visions around different development paths, wherein the concept of risk is weakly perceived among decision-makers. This perception is linked to narrow economic goals and the understanding of land as a barely regulated marketable asset, profoundly affected by segregated urban planning.Public health emergencies, especially major infectious diseases, may cause global crises. Timely and effective communication is essential for response to such incidents. https://www.selleckchem.com/products/azd7545.html However, the emergency response to such incidents usually lasts longer and break out repeatedly, and the existing static emergency communication network (ECN) analysis cannot fully reflect the dynamic information interaction between organizations during the emergency process. Therefore, this article takes the recent COVID-19 epidemic in Hubei, China as a case, and uses social network analysis to reveal the dynamic evolution of communication networks, positions, roles, and tasks of organizations from the time dimension. The results show that (1) the ECN has changed from concentrated to decentralized over time; (2) the positions and roles of participating organizations in the ECN has changed, but there are still a few key organizations that at the central position in all phases of emergency communication; (3) the core tasks have changed due to caused by public health emergencies.The peri-urban interface (PUI) exhibits characteristic qualities of both urban and rural regions, and this complexity has meant that risk assessments and long-term planning for PUI are lagging, despite these areas representing new developing settlement frontiers. This study aims to address this knowledge gap by modifying an existing approach to quantify and assess flood risk. The risk triangle framework was used to map exposure, vulnerability and biophysical variables; however, in a novel application, the risk triangle framework was adapted by presuming that there is a variation in the degree of exposure, vulnerability and biophysical variables. Within Australia and globally, PUIs are often coastal, and flood risk associated with rainfall and coastal inundation poses considerable risk to communities in the PUI; these risks will be further exacerbated should projections of increasing frequency of extreme rainfall events and accelerating sea-level rise eventuate. An indicator-based approach using the risk triangle framework that maps flood hazard, exposure and vulnerability was used to integrate the biophysical and socio-economic flooding risk for communities in PUI of the St Georges Basin and Sussex Inlet catchments of south-eastern Australia. Integrating the flood risk triangle with future scenarios of demographic and climate change, and considering factors that contribute to PUI flood risk, facilitated the identification of planning strategies that would reduce the future rate of increase in flood risk. These planning strategies are useful for natural resource managers and land use planners across Australia and globally, who are tasked with balancing socio-economic prosperity for a changing population, whilst maintaining and enhancing ecosystem services and values. The indicator-based approach used in this study provides a cost-effective first-pass risk assessment and is a valuable tool for decision makers planning for flood risk across PUIs in NSW and globally.While weather stations generally capture near-surface ambient air temperature (Ta) at a high temporal resolution to calculate daily values (i.e., daily minimum, mean, and maximum Ta), their fixed locations can limit their spatial coverage and resolution even in densely populated urban areas. As a result, data from weather stations alone may be inadequate for Ta-related epidemiology particularly when the stations are not located in the areas of interest for human exposure assessment. To address this limitation in the Megalopolis of Central Mexico (MCM), we developed the first spatiotemporally resolved hybrid satellite-based land use regression Ta model for the region, home to nearly 30 million people and includes Mexico City and seven more metropolitan areas. Our model predicted daily minimum, mean, and maximum Ta for the years 2003-2019. We used data from 120 weather stations and Land Surface Temperature (LST) data from NASA's MODIS instruments on the Aqua and Terra satellites on a 1 × 1 km grid. We generated a satellite-hybrid mixed-effects model for each year, regressing Ta measurements against land use terms, day-specific random intercepts, and fixed and random LST slopes. We assessed model performance using 10-fold cross-validation at withheld stations. Across all years, the root-mean-square error ranged from 0.92 to 1.92 K and the R 2 ranged from .78 to .95. To demonstrate the utility of our model for health research, we evaluated the total number of days in the year 2010 when residents ≥65 years old were exposed to Ta extremes (above 30°C or below 5°C). Our model provides much needed high-quality Ta estimates for epidemiology studies in the MCM region.