Jakub NowosadThe spcosa package provides an R framework for spatial coverage sampling.
Explore examples at https://git.wur.nl/Walvo001/spcosa
Physalia-coursesIt is a real privilege to learn about #SpatialStatistics in R from Prof. @edzer !
Participants over the next 5 days will learn spatial stats, sampling, geostatistics, regression, ML, and big-data methods.
https://www.physalia-courses.org/courses-workshops/spatial-statistics/
RE: https://ecoevo.social/@physaliacourses2/115463879241980538
Only 2 seats left for the #SpatialStatistics with R course!
#Rstats
Instructor: @edzer
💧🌏 Greg CocksBURGER - A Bottom-Up Regionalization Approach for Global Sub-Daily Intensity-Duration-Frequency Data
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https://doi.org/10.1029/2024WR039773 <-- shared paper
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https://zenodo.org/records/15473689 <-- shared dataset
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"KEY POINTS
• BURGER is the first global IDF data set derived from observations of sub-daily rainfall
• Sub-daily rainfall intensities are computed with the Simplified Metastatistical Extreme Value (SMEV) approach for a range of return periods
• BURGER intensities compare well with expected intensities, indicated by an interquartile range of the percentage bias between −5% and 5%..”
#GIS #spatial #data #mapping #global #exteremeweather #precipitation #rainfall #gauge #intensity #model #modeling #spatialanalysis #spatiotemporal #BURGER #geostatistics #spatialstatistics # statistics #GSDR #IDF #remotesensing #earthobservation #machinelearning #AI #weather #climate #prediction #usecase #flood #risk #hazard #SMEV #accuracy #metrology
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https://doi.org/10.1029/2024WR039773 <-- shared paper
--
https://zenodo.org/records/15473689 <-- shared dataset
--
"KEY POINTS
• BURGER is the first global IDF data set derived from observations of sub-daily rainfall
• Sub-daily rainfall intensities are computed with the Simplified Metastatistical Extreme Value (SMEV) approach for a range of return periods
• BURGER intensities compare well with expected intensities, indicated by an interquartile range of the percentage bias between −5% and 5%..”
#GIS #spatial #data #mapping #global #exteremeweather #precipitation #rainfall #gauge #intensity #model #modeling #spatialanalysis #spatiotemporal #BURGER #geostatistics #spatialstatistics # statistics #GSDR #IDF #remotesensing #earthobservation #machinelearning #AI #weather #climate #prediction #usecase #flood #risk #hazard #SMEV #accuracy #metrology
WorldPopProject🚨 Population Data and #Vaccine Mapping in Focus at Key Global Conferences
👉 WorldPop researchers presented their work at two major international gatherings this month – placing the spotlight on the power of data to drive progress across health and development in West and Central #Africa.
Satellite-Based Spatial-Statistical Modeling Of Daily Stream Water Temperatures At The CONUS Scale
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https://doi.org/10.1016/j.jhydrol.2025.133321 <-- shared paper
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#GIS #spatial #mapping #Streamtemperature #Rivertemperature #Watertemperature #Statisticalmodel #Satellite #remotesensing #ContiguousUnitedStates #CONUS #Lower48th #spatialstatistics #geostatistics #earthobservation #water #hydrology #stream #river #temperature #surfacewater #model #modeling ##seasons #weather #TempEst2 #climate #urban #natural #rural #ecoregions #ecosystems #streamgage #USGS #fedscience
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https://doi.org/10.1016/j.jhydrol.2025.133321 <-- shared paper
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#GIS #spatial #mapping #Streamtemperature #Rivertemperature #Watertemperature #Statisticalmodel #Satellite #remotesensing #ContiguousUnitedStates #CONUS #Lower48th #spatialstatistics #geostatistics #earthobservation #water #hydrology #stream #river #temperature #surfacewater #model #modeling ##seasons #weather #TempEst2 #climate #urban #natural #rural #ecoregions #ecosystems #streamgage #USGS #fedscience
EMBL EventsIs your current biological image analysis producing inaccurate results? Apply for #EMBOBioImage and fix that! 🔬✨ Learn theoretical advancements and the practical skills to apply them.
📩 Apply by 4 June
🗓️ 14 – 19 September
📍 EMBL Heidelberg and Virtual
➡️ https://s.embl.org/bia25-01-ma
#EMBLEvents #bioimageanalysis #spatialstatistics #artificialintelligence #computervision #microscopydata
Assessing The Vertical Accuracy Of Digital Elevation Models By Quality Level And Land Cover
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https://doi.org/10.1080/2150704X.2024.2368924 <-- shared paper
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#GIS #spatial #mapping #USGS #3dep #elevation #LiDAR #vertical #accuracy #precision #risk #hazard #coast #coastal #landcover #landuse #flood #flooding #stormsurge #geostatistics #spatialstatistics
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https://doi.org/10.1080/2150704X.2024.2368924 <-- shared paper
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#GIS #spatial #mapping #USGS #3dep #elevation #LiDAR #vertical #accuracy #precision #risk #hazard #coast #coastal #landcover #landuse #flood #flooding #stormsurge #geostatistics #spatialstatistics
Assessing Landslide Risk in Prince William Sound
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https://www.usgs.gov/news/featured-story/assessing-landslide-risks-prince-william-sound <-- shared technical article
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https://pubs.usgs.gov/publication/ofr20231099 <-- shared USGS open file report (OFR)
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#GIS #spatial #mapping #remotesensing #3dep #ifsar #elevation #geology #engineeringgeology #massmovement #landslide #risk #hazard #tsunami #Alaska #PrinceWilliamSound #naturalhazard #climatechange #glaciers #slopes #glacial #sediment #instability #slopestability #coast #coastal #monitoring #model #modeling #statistics #geostatistics #spatialstatistics #ChugachMountains #tsunamigenic #NationalTsunamiWarningCenter #spatialanalysis #geomorphology #geomorphometry
@USGS
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https://www.usgs.gov/news/featured-story/assessing-landslide-risks-prince-william-sound <-- shared technical article
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https://pubs.usgs.gov/publication/ofr20231099 <-- shared USGS open file report (OFR)
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#GIS #spatial #mapping #remotesensing #3dep #ifsar #elevation #geology #engineeringgeology #massmovement #landslide #risk #hazard #tsunami #Alaska #PrinceWilliamSound #naturalhazard #climatechange #glaciers #slopes #glacial #sediment #instability #slopestability #coast #coastal #monitoring #model #modeling #statistics #geostatistics #spatialstatistics #ChugachMountains #tsunamigenic #NationalTsunamiWarningCenter #spatialanalysis #geomorphology #geomorphometry
@USGS
Spatially Balanced Sampling And Ground-Level Imagery For Vegetation Monitoring On Reclaimed Well Pads
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https://doi.org/10.1111/rec.12956 <-- shared paper
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#GIS #spatial #mapping #energy #oilandgas #oilandgasindustry #oilandgasexploration #wellpads #reclamation #spatialanalysis #naturalgas #development #northamerica #USWest #landuse #ownership #stakeholders #vegetation #metric #esosystem #SamplePoint #systematic #sampling #imageanalysis #remotesensing #spatialstatistics #monitoring #regulations #seeding #costs #naturalresources #standardprotocols #defensibility #costsavings #observerbias #GPS #camera #Wyoming #WY
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https://doi.org/10.1111/rec.12956 <-- shared paper
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#GIS #spatial #mapping #energy #oilandgas #oilandgasindustry #oilandgasexploration #wellpads #reclamation #spatialanalysis #naturalgas #development #northamerica #USWest #landuse #ownership #stakeholders #vegetation #metric #esosystem #SamplePoint #systematic #sampling #imageanalysis #remotesensing #spatialstatistics #monitoring #regulations #seeding #costs #naturalresources #standardprotocols #defensibility #costsavings #observerbias #GPS #camera #Wyoming #WY