#factors — Public Fediverse posts on home.social

💧🌏 Greg Cocks @[email protected] · 2026-08-18 · 02:56 UTC

The Portrait of Flood Risk in Italy - Past, Present and Future, From 1870 to 2100
--
https://doi.org/10.1029/2026GL122987 <-- shared paper
--
“ABSTRACT: Among European countries, Italy ranks as one of the most susceptible to flood risk. While this figure is already substantial, climate change and rapid urbanization in flood-prone areas have been identified as the two main drivers expected to elevate the number of individuals at risk. This study offers a comprehensive assessment of these two drivers of flood risk in Italy over 230 years, from 1870 to 2100, focusing on how they interact to increase risk. Using the large-scale flood risk model RESCUE-FR, [the authors] analyze[d] the population at risk under the 200-year return period scenario to provide a targeted assessment of population risk, how it has evolved in the past, and its projection in the future. [Their] findings indicate that while historical flood risk in Italy has primarily been influenced by population growth and migration into at-risk areas, future projections suggest that climate change will become the dominant driver of flood risk.
PLAIN LANGUAGE SUMMARY: Italy is one of the European countries most at risk of flooding. This study examines the impact of two risk factors on flood risk in Italy over the long term, from 1870 to 2100: climate change and the evolution of population in areas prone to flooding. Using a large-scale flood risk model, [they] simulated different scenarios for different time periods, such as with and without climate change, to estimate how each factor contributes to the number of people exposed to floods in the past and future. [Their] results show that population growth and migration into flood-prone areas were the main reasons for the increased risk in the past. In the future, however, climate change is likely to become the dominant factor, putting more people at risk. Understanding how these factors interact can help communities to plan more effectively for floods and reduce the number of people affected…”
#flood #flooding #risk #hazard #Italy #Europe #national #history #historic #cost #damage #infrastructure #floodrisk #population #urbanisation #development #climatechange #extremeweather #dominantfactor #floodprone #national #regional #spatialanalysis #spatiotemporal #model #RESCUEFR #modeling #factors #parameters #drivers #publicsafety

#flood #flooding #risk #hazard #italy #europe

💧🌏 Greg Cocks @[email protected] · 2026-08-14 · 03:20 UTC

Geospatial Analysis of Carbon Offset Projects - A Broader Scientific Outlook
--
https://www.eldhollow.com/blogs/geospatial-analysis-of-carbon-offset-projects <-- shared technical blog
--
[this post should not be considered an endorsement of a particular organisation, rather scrutinising the spatial use case & technical approach]
H/T @kyle Arvisais | Forest Carbon Scientist
“Geospatial analysis is at the core of [the H/T’s company’s] project quality assessments, and [the author is] constantly finding ways to make the pipeline better and ways to use it. [They are] obviously not the only one who uses these types of tools, but to be perfectly honest, the quality of models [they have] seen over the years has been all over the place.
This blog makes a casual introduction to [their] pipeline while talking about the field at large…”
--
“The world has committed to protecting and restoring nature at an unprecedented scale. Whether that commitment delivers what it promises comes down project execution on the ground. Local socioeconomics and forest ecology intertwine to create complex challenges for projects to overcome during implementation, and at the end of the day, projects boil all of these complexities down to one single unit: the carbon credit. So the question becomes: can we actually measure what is happening to a forest, accurately and honestly, and everywhere at once?
For a long time, the honest answer has been no. Historically, many forest carbon projects overstated their impact. Usually it was because the baseline was too generous, or because the measurements underneath were flawed. For anyone with a stake in nature markets, that uncertainty is one of the core risks.
Robust geospatial analysis can help mitigate that risk. If you treat a carbon credit as what it really is, a scientific claim, then we can hold it to that standard and assess it objectively. [Their] geospatial pipeline turns satellite data and ground truth data into models about how much forest is standing, how it is changing, and what might put it at risk in the future. The pipeline does this anywhere on Earth…”
#GIS #spatial #mapping #usecase #carbonoffset #spatialanalysis #spatiotemporal #qualityassessment #objectivity #projectpipeline #model #modeling #application #nature #environment #ecosystems #ecology #local #regional #factors #socioeconomics #forestecology #vegetation #forest #tree #carboncredit #climatechange #climatecrisis #forestcarbonprojects #global