#topography — Public Fediverse posts on home.social

Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
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https://doi.org/10.1016/j.jhydrol.2026.135999 <-- shared paper
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https://youtu.be/VHzYLvSYR7k?si=5oGGPeH6T0dFusfY <-- recent overview video created about the research
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https://doi.org/10.1016/j.wroa.2025.100396 <-- share (earlier) paper
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H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
“… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
[The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”
#publichealth #risk #hazard #watersecurity #Floodrisk #Humanhealthrisk #Urbanflooding #Hydrodynamicmodelling #waterquality #model #modeling #SupportVectorRegression #flood #flooding #urban #city #sewage #pathogens #contaminant #disease #streets #community #quantification #remotesensing #GIS #spatial #mapping #earthobservation #spatialanalysis #water #hydrology #climatechange #extremeweather #spatiotemporal #AI #machineleraning #fateandtransport #hydrodynamic #microbial #rainfall #drainage #streamflow #topography #hydrogeomorphology #Delhi #India #floodplain

#publichealth #risk #hazard #watersecurity #floodrisk #humanhealthrisk

Chris Bond @[email protected] · 2026-07-21 · 18:31 UTC

#1340 W.G.V. Balchin - Cornwall: An Illustrated Essay on the History of the Landscape. Hodder and Stoughton, London, 1954, 1st edition.

#WGVBalchin #HodderAndStoughton #Cornwall #Topography #Geography #Landscape #BookOfTheDay

#wgvbalchin #hodderandstoughton #cornwall #topography #geography #landscape

OptimusPrimeBot @[email protected] · 2026-07-21 · 05:10 UTC

Why Maine’s Sandy Shorelines Turn Jagged 🌎🛰️

#Topography

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:Why+Maine%E2%80%99s+Sandy+Shorelines+Turn+Jagged+%281257693%29.jpg

#topography

OptimusPrimeBot @[email protected] · 2026-07-20 · 05:12 UTC

Shaping the Emerald City 🌎🛰️

#Topography

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:Shaping+the+Emerald+City+%281256907%29.jpg

#topography

Thomas Weibel @[email protected] · 2026-07-17 · 07:15 UTC

World map with real-time day-night boundaries using 20k #opensource #emojis: Hello world!

https://www.thomasweibel.ch/emoji-world/

#OpenSource #emoji #worldemojiday #openmoji #worldmap #map #worldclock #mapping #geography #gis #topography #opendata #openscience #glamhack #digitalhumanities #linguistics #daynight #astronomy

#opensource #emoji #worldemojiday #openmoji #worldmap #map

OptimusPrimeBot @[email protected] · 2026-07-17 · 05:17 UTC

A Tide-Fueled Trove of Biodiversity in Guinea-Bissau 🌎🛰️

#Earth'sSurfaceandInterior #Topography #Wildlife

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:A+Tide-Fueled+Trove+of+Biodiversity+in+Guinea-Bissau+%281257016+-+lrg%29.jpg

#earth #topography #wildlife

OptimusPrimeBot @[email protected] · 2026-07-14 · 10:27 UTC

Fans of the Arctic 🌎🛰️

#Glaciers&IceSheets #SurfaceWater #Topography

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:Fans_of_the_Arctic_%281256070_-_wide_oli2_20250801%29.jpg

#glaciers #surfacewater #topography

💧🌏 Greg Cocks @[email protected] · 2026-07-02 · 01:32 UTC

Advancing Detailed Flood Hazard Identification in Alberta, Canada - Insights from Two Recent Flood Studies
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https://doi.org/10.3390/w18131592 <-- shared paper
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“The increasing frequency of floods and the severity of their consequences for public safety, infrastructure, and the economy demand improved methods for flood hazard identification. Flood studies that include flood hazard mapping are critical tools for informing emergency response and flood recovery, as well as for land use and mitigation planning. The methodology for such flood studies has evolved, and access to more powerful computational resources and high-resolution base data has contributed to the increased use of two-dimensional hydraulic modelling, where one-dimensional modelling previously was the default. However, local-scale flood studies face real-world constraints, including sparse data, challenging hydrologic conditions, and budget limitations, which can hinder the application of advanced techniques. This study addresses these challenges through innovative, practice-driven solutions in two case studies in Alberta, Canada: a small, partly channelised prairie stream network (Wolf Creek, Lacombe) and a laterally dynamic river on a distributary delta (Swan River, Kinuso). Three core components of flood hazard studies are described: field survey data collection, regional hydrology assessment, and hydraulic modelling. Key findings include demonstrating that LiDAR-derived terrain models alone cannot capture channel conveyance, the importance of low-flow calibration in the absence of high-water marks, the selection of a modelling methodology based on bathymetric and topographic features within a study area, and the development of inflow hydrographs for unsteady-state simulation in flat floodplains…”
#FloodMapping #FloodRisk #Hydrology #HydraulicModeling #HECRAS #WaterResources #Alberta #Resilience #RiverSurvey #spatialanlaysis #spatiotemporal #floodhazardmapping #HECRAS #model #modeling #remotesensing #LiDAR #bathymetry #floodfrequencyanalysis #unsteadysimulation #FHIMP #FHIP #WoldCreek #Lacombe #SwanRiver #Kinuso #Alberta #Canada #localscale #provincialfloodstudy # prairie #stream #river #flood #flooding #water #hydrology #risk #hazard #watershed #publicsafety #cost #damage #economics #infrastructure #use #practicedriven #floodhazard #survey #hydraulic #terrainmodels #hydrogeomorphology #topography #elevation #floodplain
@Alberta Environment and Protected Areas | @Government of Alberta | @Barr Engineering

#floodmapping #floodrisk #hydrology #hydraulicmodeling #hecras #waterresources

💧🌏 Greg Cocks @[email protected] · 2026-07-01 · 04:17 UTC

The Romans Have A Reputation For Building Straight Roads…
[mapping with remote sensing, etc --> open data]
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https://www.livescience.com/archaeology/romans/how-did-the-romans-build-such-straight-roads <-- shared technical article
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https://doi.org/10.1038/s41597-025-06140-z <-- shared paper, “Itiner-e: A high-resolution dataset of roads of the Roman Empire”
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https://itiner-e.org/ <-- shared webmap “Itiner-e – The Digital Atlas of Ancient Roads”
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https://youtu.be/OTSe7MsJXbo?si=nWl8PZHNmyL_yXEJ <-- shated Itiner-e overview/animation video
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https://youtu.be/ge9XV2eKLvQ?si=OwPWoocT4nVG9gaV <-- shared video, “Roman Surveyors - The Engineers Who Shaped Rome"
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[at high school my favourite subject was Ancient History, witha focus on the Roman Empire, with the formidable Mr. Marriot! @Edgewater College, Pakuranga]
“Itiner-e aims to host the most detailed open digital dataset of roads in the entire Roman Empire. The data creation is a collaborative ongoing project edited by a scholarly community. Itiner-e allows you to view, query and download roads. Each road segment has a URI that allows it to be cited and linked by external resources. It also includes a route-finding tool to explore travel itineries and times in the ancient world (beta version)…”
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“The Roman Empire’s road system was critical for structuring the movement of people, goods and ideas, and sustaining imperial control. Yet, it remains incompletely mapped and poorly integrated across sources despite centuries of research. [They] present Itiner-e, the most detailed and comprehensive open digital dataset of roads in the entire Roman Empire. It was created by identifying roads from archaeological and historical sources, locating them using modern and historical topographic maps and remote sensing, and digitising them with road segment-level metadata and certainty categories. The dataset nearly doubles the known length of Roman roads through increased coverage and spatial precision, and reveals that the location of only 2.737% are known with certainty. This resource is transformative for understanding how mobility shaped connectivity, administration, and even disease transmission in the ancient world, and for studies of the millennia-long development of terrestrial mobility in the region…”
#ancienthistory #rome #roman #road #agrimensores #gromatici #survey #surveying #instruments #transportation #empire #messenger #administration #military #legions #soldiers #construction #mapping #remotesensing #Itinere #opendata #spatial #RomanEmpire #archaeology #history #topography #connectivity #terrestrial #mobility #webmap #GIS #mapping #research #network #segment #URI #routing #trade #economics
@Itiner-e

#ancienthistory #rome #roman #road #agrimensores #gromatici

Journal of Plant Ecology @[email protected] · 2026-06-28 · 14:07 UTC

【🎉Latest accepted article】
How do forest type, environment, and #Biodiversity jointly shape tropical understory #LitterCharacteristics?

#TropicalForest | #EnvironmentalDrivers | #Topography | #ManagementIntensity

https://doi.org/10.1093/jpe/rtag141

#biodiversity #littercharacteristics #tropicalforest #environmentaldrivers #topography #managementintensity

💧🌏 Greg Cocks @[email protected] · 2026-06-13 · 05:44 UTC

Late Miocene Euphrates River Drained Into A Partially Desiccated Eastern Mediterranean
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https://doi.org/10.1038/s41561-026-01962-x <-- shared paper
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[the paleogeographic reconstruction is outstanding, including the strength and information conveyed so well in that figure, kudos!]
H/T @lina Jakaitė-Darkšė
“Although the Euphrates River - stretching ~3,000 km across Western Asia - has shaped the region’s geology for millions of years, the timing of its origin and the evolution of its course remain enigmatic. So far, two contrasting hypotheses have been proposed to explain the fluvial system’s Late Neogene path: termination in Anatolia at a palaeo-lake or the Mediterranean, or a southeastward continuation to Arabia. Here [they] use seismic-reflection and topographic data to show that two previously identified sedimentary accumulations - deposited during the terminal phase of the Late Miocene Messinian salinity crisis - resulted from dual riverine systems that drained into a partially desiccated eastern Mediterranean before avulsing toward the Persian Gulf and converging to form the modern Euphrates River. From probabilistic sediment-budget modelling, [they] show that although the latest Messinian drainage basins were an order of magnitude smaller than their present-day extents, the total palaeo-discharge exceeded that of the modern Tigris, Euphrates and Nile rivers combined, indicating intense palaeo-precipitation and high palaeo-relief. These results suggest that plate-margin deformation both controlled the fluvial avulsions that diverted the Euphrates River from the Anatolian–Eurasian Plate to the Arabian Plate, and established the conditions necessary for the development of the alluvial Fertile Crescent…”
#water #hydrology #hydrography #paleogeography #Euphrates #river #Miocene #reconstruction #spatialreconstruction #geology #change #erosion #MiddleEast #spatialanalysis #spatiotemporal #Neogene #Anatolia #paleolake #Mediterranean #Arabia #Messinian #remotesensing #model #modeling #topography #hydrogeomorphology #geomorphology #PersianGulf #sediment #paleodischarge #volume #Tigris #elevation #platetectonics #structuralgeology #platemargin #fluvial #avulsion #FertileCrescent

#water #hydrology #hydrography #paleogeography #euphrates #river

💧🌏 Greg Cocks @[email protected] · 2026-06-11 · 23:55 UTC

Urban Flood Observations [UFO] - A Hand-Labeled Training And Validation Dataset Of Post-Flood Inundation
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https://doi.org/10.48550/arXiv.2604.23066 <-- shared paper
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https://zenodo.org/records/19698577 <-- shared dataset
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H/T @Rohit Mukherjee
“UFO includes 215 high-resolution PlanetScope image chips and corresponding labels from 14 global flood events, with a focus on urban environments. The labels capture visible surface water in post-flood scenes.
Labeling floods from space is hard, especially in urban areas. Building shadows, narrow channels, wet soil, complex drainage features, and mixed pixels all make it difficult. [They] spent a lot of time refining the labels, and [they] think they can be useful for benchmarking flood-mapping methods and for training flood models (if you have PlanetScope access).
As an initial benchmark, [they have] trained a SegFormer model on the dataset and achieved a mean IoU of 77.3% under leave-one-event-out validation, where each flood event was held out entirely from training…”
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“Urban flooding affects lives and infrastructure worldwide. Mapping inundation in complex urban environments from satellite imagery remains challenging due to limited spatial resolution, infrequent acquisitions, and cloud cover. [They] present Urban Flood Observations (UFO), a global, hand-labeled dataset of post-flood inundation in diverse urban settings. UFO comprises 215 image chips (1024 by 1024 pixels) from 14 flood events between 2017 and 2021, derived from 3 metre PlanetScope imagery. Each chip is annotated with two classes: 'inundated' (all visible surface water, including floodwater and pre-existing water bodies (permanent or seasonal)) and 'non-inundated'. To demonstrate the dataset's utility, [they have] trained a segmentation model using leave-one-event-out cross-validation, achieving a mean Intersection over Union (IoU) of 77.3. [They] also used UFO to evaluate two widely used surface water products, the Sentinel-1-based NASA IMPACT model and Google's 10 m Dynamic World water class, which yielded IoUs of 44.1 and 48.1, respectively. UFO is publicly available to support the development and validation of urban inundation mapping methods…”
#UrbanFloodObservations #Urban #Flood #Observations #flooding #UFO #PlanetScope #remotesensing #GIS #spatial #mapping #opensource #opendata #floodmapping #model #modeling #floodmodels #infrastructure #water #hydrology #extremeweather #hydrography #humanimpacts #cost #economics #risk #hazard #segmentationmodel #elevation #topography #surfacewater #satellite #senteniel #IMPACT #testcases