Health can be influenced by multiple environmental exposures & their interactions, and how we can consider them within a spatial machine learning (ML) model; check out the 📢new paper exploring these complex aspects using explainable AI tools! (1/3)

RT @DrMariaNeira: Dear @COP29_AZ negotiators, please remember: . Our health is NOT negotiable. #COP29 @WHO @RockefellerFdn @wellcometrust….

RT @robmarkcole: 📢TorchGeo 0.6.0 is now released!.This adds 18 new datasets, 15 new datamodules, and 27 new pre-trained models, encompassin….

RT @ScholarshipfPhd: How to choose good research topic?

RT @NFrantzeskaki: 5 days left to our #urban #nature and #health event: - there is still time to register!.

Finally, we observed that the high CC-risk grass patches are primarily located in areas of higher socioeconomic deprivation. Indicating loss of ecosystem function for the most vulnerable population group under increasing climate change pressure (4/4).

Our result showed that grass patches lose considerable evapotranspiration capacity due to water stress, that most vulnerable areas are in high-density urban zones, and that groundwater access may reduce the pressure if watered during high water stress conditions (3/4).

In this study, we modeled the risk of grass layers in Greater Manchester. We applied the IPCC risk framework to locate the risk of grasses to water stress, urban fragmentation, and adaptive capacity due to groundwater access (2/4).

Green infrastructure (GI)🌱 provides ecosystem services to offset the effect of climate change (CC), but what if they cannot function? How can we measure the risk GI from CC? Check out our (Jeremy Carter, @Mell_GIPlanning) new paper exploring these (1/4):

RT @LancetCountdown: ⚡ PUBLISHED TODAY: The 2024 Europe Report of the Lancet Countdown finds:. 🌡️ Heat related deaths rising, disproportion….

RT @ajbailey24: @NFrantzeskaki @smlabib and I are hiring a post-doc with experience in qualitative methods! .

RT @ISGLOBALorg: #JobOffer💼 | We're looking for a motivated PhD student to conduct #HealthImpact assessments of urban planning scenarios in….

The nonlinear relations & exposure interactions are critical to understanding the sweet & sour spots of exposures & their influence on health outcomes (3/3)

This study showed using ML for health data analysis for environmental exposures (e.g., air pollution, greenspace) is not free of spatial autocorrelations & typical ML modeling structure may be sub-optimal as they might over or underestimate the influences of exposures (2/3).

RT @Yuchenn_: Thrilled to share our latest publication in @ijgis! 🎉 Our review dives into how street view imagery and cutting-edge visual i….

While Geo-tagged 🌍Street View Images 📸 are super useful for different research, commercial data's legal & copyright aspects can cause challenges in using them. We (W/ @HelbichMarco, M. Danish, @bricker) explored these in this 📢new paper! Check it out:

RT @NobelPrize: 2002 economic sciences laureate Daniel Kahneman has passed away aged 90. He was awarded the prize for integrating insights….

RT @NFrantzeskaki: #JobAlert Do you want to advance research on #urban #naturebasedsolutions? This #4years #PostDoc Research position may b….

RT @NFrantzeskaki: Embracing #Urban #Nature for #Health - join our @UniUtrecht @sUUstainability day event - register in the link: . https://….

RT @cordezbar: Having a #urban #trees in front of one's home was strongly and positively associated with #Wellbeing….