#geostatistics — Public Fediverse posts on home.social

💧🌏 Greg Cocks @[email protected] · 2026-09-10 · 04:17 UTC

A Coastal Exposure Index For Ireland - Relative Hazard Exposure And The Protective Role Of Coastal Habitats
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https://doi.org/10.1007/s11069-026-08361-w <-- shared paper
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http://alturl.com/4e83i <-- shared webmap / data portal
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https://www.independent.ie/irish-news/revealed-researchers-pinpoint-county-facing-greatest-risk-of-coastal-erosion-as-sea-levels-rise/a/161113880.html <-- shared media article
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[“The index complements site-specific flood and erosion modelling.”]
H/T @kevin Walsh | PhD Researcher at University College Cork
“In this paper [1st link above], [the authors] seek to answer the question “what is the relative distribution of exposure to coastal hazards around the Irish coast, and where can coastal habitats potentially reduce exposure?”
The method [they] chose to achieve this was the Coastal Vulnerability Model (CVM), within the InVEST software suite. This involves combining the key physical and climatic variables which can show us where along the coast might be most adversely affected by extreme winds, powerful waves and surges, and sea level rise.
It also reveals the potential protection provided by coastal habitats, such as dunes and saltmarsh, as well as populations and sites of cultural heritage located within zones deemed “Very High Exposure”.
[They] tested variations to the model, including seeing how the results change when certain variables are left out, what happens if we add in other variables, and how ranking choices impact exposure distribution. The results show that these choices, especially the ranking methods, can have large impacts on hazard distribution and the overall interpretation of the results. However, [they] found that the CVM quintile based approach was most suitable for Ireland, as it reveals high exposure sites on the east coast, which tends to be overlooked when different methods are applied.
[The H/T] also prepared an interactive map, where you can view the results in detail [2nd link above]
There’s a lot of work ongoing in this space around Ireland, [they] hope this will be a valuable contribution towards sustainable management of our coastline…”
#spatialanalysis #exposure #coastal #hazards #mitigation #risk #Ireland #Irish #coast #CoastalVulnerabilityModel #CVM #InVEST #model #modeling #spatiotemporal #geostatistics #statistics #spatial #mapping #geomorphology #geology #climate #wind #wave #tidal #erosion #stormsurge #storms #ocean #sealevelrise #climatechange #extremeweather #dunes #saltmarshes #machair #seagrass #habitat #protection #vulnerability #parametersensitivity #exposure #sustainable #populationpressure #CoastalExposureIndex #culturalheritage #coastalzonemanagement #planning #policy #evidencebased #adaption #strategies

#spatialanalysis #exposure #coastal #hazards #mitigation #risk

💧🌏 Greg Cocks @[email protected] · 2026-08-18 · 03:21 UTC

Spatiotemporal Distribution, Climatic Factors, And Seasonal Precipitation Patterns Characterizing 66 Years Of Widespread Shallow Landslide Events In Piedmont (Northwestern Italy)
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https://doi.org/10.3389/feart.2026.1884300 <-- shared paper
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“Widespread shallow landslide events constitute one of the primary drivers of recurrent societal and economic losses in mountain regions. Although the influence of climate variability on landslide frequency and magnitude has been widely recognized, long-term, event-level analyses linking spatiotemporal landslide patterns to precipitation climatology at the regional scale remain scarce. This study presents a statistical analysis of 128 widespread shallow landslide events recorded in Piedmont, northwestern Italy, over the 66-year period 1960–2025, cross-referenced against the regional precipitation climatology. Events were characterized by season, primary physiographic unit, provincial coverage, and an ordinal magnitude index (scale 1–7) encoding combined spatial extent and estimated landslide count. Results indicate that no statistically significant monotonic trend in event frequency was detected over the study period (mean rate: 1.97 events yr⁻1); however, a moderate positive correlation was established between event magnitude and the number of provinces affected (R2 = 0.51, p < 0.00), validating the magnitude index as a proxy for spatial footprint. Mean event magnitude reached its highest value in the 2010s (3.71), while all five events of magnitude ≥ 6 occurred in autumn. The summer fraction of the catalogue increased markedly, from 6% in the 1960s to 31% in the 2000s and 25% in the 2020s, concurrent with stable or declining summer mean precipitation totals, consistent with Clausius–Clapeyron amplification of convective intensity under documented regional warming. Cross-analysis with regional records identifies three tiers of rainfall–landslide coupling: a stationary direct seasonal coupling; a non-stationary, strengthening intensity-mediated summer coupling; and a structural susceptibility-mediated spatial decoupling whereby the driest provinces generate the highest landslide occurrence frequencies due to the lower triggering thresholds characteristic of Tertiary Piedmont Basin sedimentary environments. A post-hoc assessment of the triggering thresholds used for regional shallow landslide early warning system demonstrates superior detection performance for high-magnitude autumn events (hit rate up to 89% for the 2000–2025 sub-period) and identifies sub-daily convective accumulation windows in summer as the primary domain requiring threshold recalibration…”
#massmovement #landslide #engineeringgeology #Italy #Piedmont #NorthernItaly #weather #rainfall #precipitation #climate #risk #hazard #corrleation #relationship #earlywarningsystems #damage #loss #community #infrastructure #mountain #spatiotemporal #mapping #spatialanalysis #statistics #geostatistics #climatology #regional #scale #weatherpatterns #physiography #geomorphology #water #hydrology #hydrogeomorphology #geology #soils

#massmovement #landslide #engineeringgeology #italy #piedmont #northernitaly

💧🌏 Greg Cocks @[email protected] · 2026-05-01 · 03:19 UTC

Missing [Survey, etc] Data Can Be A Geographic Phenomenon
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https://doi.org/10.1080/24694452.2026.2640220 <-- shared paper
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#GIS #mapping #spatial #DataScience #missing #data #spatial #AAG #autocorrelation #geographicallyweightedregression #GWR #imputation #missingdata #survey #surveynonresponse #incomplete #surveyquestions #ethnicity #income #spatialdata #alldataisspatial #UK #FinancialLives #geography #spatialanalysis #geostatistics #location #imputing #statistics #dataset #DataImputation #MissingData #DataCleaning #DataPreprocessing #DataWrangling #DataQuality #DataEngineering #FinancialData #FinancialAnalytics #FinincialModeling #FinDataScience

#gis #mapping #spatial #datascience #missing #data

💧🌏 Greg Cocks @[email protected] · 2026-04-22 · 05:02 UTC

Remote Sensing And GIS-Supported Framework Of Pre-Monsoon Drought Assessment In Bangladesh (2000–2022) Using CHIRPS-Based SPI-3 And MODIS-Derived Vegetation And Temperature Indices
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https://doi.org/10.1007/s12665-026-12848-x <-- shared paper
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H/T MD. ABDULLAH AL MAMUNM | Studying PhD in Rural and Environmental Sciences
“১ বছর ২০ দিন লেগে গেল! প্রথম ৪ জন রিভিউয়ারের প্রায় ৫০+ কমেন্টের পর মনে হয়েছিল আর এগোব না। তবে আমার সুপারভাইজার বলেছিলেন, “রিজেকশনের চেয়ে কমেন্ট ফেস করা ভালো।”
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#GIS #spatial #mapping #remotesensing #Bangladesh #earthobservation #water #hydrology #premoonsoon #moonsoon #drought #CHIRPS #MODIS #SPI #vegetation #temperature #indices #parameters #SPI #NDVI #VCI #TCI #VHI #monitoring #droughts #agriculture #farming #crop #cultivation #yield #foodsecurity #weather #rainfall #precipitation #Pearsoncorrelation #geostatistics #irrigation #watersecurity #foodsecurity #policy #planning