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#hydrospatial

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Public *
💧🌏 Greg Cocks

Surveying Lake Titicaca [2024]
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hydro-international.com/conten <-- shared technical article
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[A very comprehensive hydrographic and shallow geophysical study and mapping effort of Lake Titicaca…]
“In October 2024, officers from the Category “A” Specialization Programme in Hydrography for Naval Officers of the Peruvian Navy conducted their complex multidisciplinary field project at Lake Titicaca at Puno in Peru, which is the highest navigable lake in the world (3,800 metres above sea level). The purpose of this survey was to address issues in the lacustrine environment due to hydrological processes that have occurred in recent years in this water body.…”
#GIS #spatial #mapping #hydrospatial #hydrology #hydrography #LakeTiticaca #Bolvia #Puno #Peru #PeruvianNavy #lake #remotesensing #survey #lacustrine #vertical #multibeam #echsounder #sonar #geomatics #cartography #QGIS

Public
💧🌏 Greg Cocks

Postfire Debris-Flow Hazards
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usgs.gov/programs/landslide-ha <-- shared technical article / overview
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alturl.com/po3yj <-- USGS Post-Fire Debris Flow Hazard Assessment Viewer
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earthquake.usgs.gov/arcgis/res <-- Post-Fire Debris-Flow Hazards USGS spatial data / GIS Services
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#GIS #spatial #mapping #USGS #LandslideHazardsProgram #NaturalHazards #3DEP #NGP #NationalGeospatialProgram #GIRT #GeospatialInformationResponseTeam #GIS #geology #hydrospatial #hydrology #landslides #debrisflows #fires #postfire #lidar #elevationdata #hazardassessments #preparedness #massmovement #engineeringgeology #risk #hazards #impacts #cost #economics #geomorphology #geomorphometry #spatialanalysis #spatiotemporal #remotesensing #soil #model #modeling #LosAngeles #LA #LosAngelesfires #California #wildfires #opendata
@USGS

photo - A home damaged by the January 9, 2018 debris flow event in Montecito, California. The event was triggered by heavy rain on the Thomas Fire burn area above Montecito. This home is located near Buena Vista Creek.
screen shot centered on LA - USGS Post-Fire Debris Flow Hazard Assessment Viewer (web map)
photo - Debris Flow in Cable Canyon following the 2003 Old Fire in the San Bernardino Mountains, California
photo - Post-fire debris flow depositing ash and sediment on a steep hillside, 2021 Dixie Fire in northern CA
Public
💧🌏 Greg Cocks

New USGS Dataset Uncovers The Santiam River’s Underwater Topography To Aid In Fish Habitat And Water Flow Management
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usgs.gov/news/national-news-re <-- shared article
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apps.nationalmap.gov/lidar-exp <-- USGS 3DEP LiDAR Explorer (open data)
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#GIS #spatial #mapping #remotesensing #LiDAR #topobathymetry #topobathy #example #usecase #wildfires #rivermanagement #climatechange #waterresources #SantiamRiver #Oregon #KlamathRiver #PotomacRiver #ColoradoRiver #USGS #USACE #3DEP #opendata #topography #elevation #3DTNM #water #hydrology #hydrospatial #pilotproject #prototype #infrastructure #navigation #engineering #riverbed #sediment #sedimentation #habitat #river #waterbody #flowmanagement #dams #salmon #steelhead #fish #WillametteValley #flood #flooding #risk #hazard #model #modeling #FIM #watersupply #agriculture
@USGS @USACE

screen shot - 3DEP LiDAR Explorer - Santiam River, OR's topobathy dataset(s)
imagery - Topobathymetric digital elevation model of the Santiam River in the Willamette Valley southeast of Salem, Oregon. The trees and dry land are shown as a lidar point cloud colored based on aerial imagery.
drone photo - oblique - The North Santiam drains from the Cascade Range and through the Willamette Valley foothills where it combines with the South Santiam before joining the Willamette River near Salem. The river in this section has numerous gravel bars and secondary channels and is flanked by agricultural lands and floodplain forests.
map - Topobathymetric digital elevation model of the Santiam River in the Willamette Valley southeast of Salem, Oregon.
Public
💧🌏 Greg Cocks

The Great Dismal Swamp Has Released Millions Of Tons Of Carbon Since The Colonial Era, Research Finds
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whro.org/environment/2024-11-0 <-- shared article
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doi.org/10.1029/2024JG008137 <-- shared paper
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#GIS #spatial #mapping #climatechange #GreatDismalSwamp #carbon #NorthCarolina #Virginia #USA #engineering #water #hydrology #swamp #habitat #biodiversity #humanimpacts #carbondioxide #landuse #change #wetlands #peatlands #carbonsink #methane #model #spatialanalysis #spatiotemporal #research #peat #peatswamp #drainage #ditches #engineering #reclamation #peatfire #mitigation #ecosystem #carbonloss #hydrospatial

photo - A researcher moves through the Great Dismal Swamp in Virginia.
Schematic - ash mass concept. For a column of peat exposed to drainage, the surface peat is exposed to more oxidation and therefore carbon is lost but the ash content is conserved. This demonstrates how carbon loss can be calculated using the remaining ash in the peat column. The terms correspond to the terms in Equations 1-5, with r = reference layer and i = impacted layer. The dashed line in the second column indicates the loss. The loss in thickness due to shallow subsidence results from the difference in the bulk densities, whereas the secondary subsidence results from the loss in elevation due to oxidation, driven by the differences in ash mass.
Maps - coring locations, ditches by age, dominant vegetation communities. Contours correspond to estimated peat depths based on Oaks and Whitehead (1979). Coring locations are indicated by the following numbers: 1. GDS519, 2. GDS520, 3. GDSW1, 4. GDS77, 5. GDS83, 6. GDS528, 7. Interior-South, 8. Interior-North, 9. GDS96, 10. GDS-P + H, 11. GDS542, 12. GDS-04-14-2022-1A, 13. GDS-04-14-2022-1B. (a) Map of Great Dismal Swamp National Wildlife Refuge (GDS NWR) showing coring locations and binned ages of ditch, canal, and railroad installation, (b) Map of GDS NWR showing dominant vegetation communities within GDS NWR. The “early successional” (marsh) area to the southeast of Lake Drummond corresponds to the area burned in both 2008 and 2011. The area bounded by shading represents the Great Dismal Swamp NWR boundary.
charts - Carbon stocks and accumulation at GDS sites. (a) Carbon stocks for all sites, including two calculations for heavily impacted sites (GDS-W1, GDS-77, and GDS-P&H). Stars indicate calculations from ash mass from the lower depths of each of those cores, while the other (b) calculation for these sites indicates the lower ash mass calculation using the average of other less disturbed sites. Burn scar cores calculations are down to the first charcoal peak (a) and down to the second peak (b) for GDS-Interior-North and South. (b) Carbon accumulation and loss rates for cores with vegetation reconstructions. Negative values indicate carbon loss values.
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💧🌏 Greg Cocks

New [2018] 30 Metre Resolution Global Shoreline Vector And Associated Global Islands Database For The Development Of Standardized Ecological Coastal Units
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doi.org/10.1080/1755876X.2018. <-- shared 2018 paper
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#GIS #spatial #mapping #coast #coastline #global #shoreline #landsat #remotesensing #spatialanalysis #extraction #AI #machinelearning #GSV #GSHSS #ecology #terrestrial #marine #ECU #waters #GEO #GoogleEarthEngine #MBON #BluePlanet #water #hydrography #hydrospatial #GroupOnEarthObservations
@GroupOnEarthObservations #islands @GEOSEC2025

maps - Top – The GSV along the Florida keys in the United States. The continental mainland of North America is shown in tan, islands > 1 km2 in area are shown in green, and islands < 1 km2 are shown in red. These landmasses are depicted at a 1:1,000,000 scale. Bottom – For cartographic reference, the same area of the Florida Keys
maps/landsat image - A visual comparison of the GSV and the GSHHS (Wessel and Smith Citation1996) for an archipelago at the westernmost end of the Florida Keys, United States. The underlying image is from a 1:65,000 level zoom of Esri's World Image Basemap. The yellow lines represent shorelines from the GSHHS, and the red lines depict GSV shorelines. Only the largest polygon shown is > 1 km2. The GSV shows improvement in the visual fit of the coastline vectors to the shore.
photo - shoreline, Florida Keys, USA
annonated map - Illustrative example of the ecological coastal units (ECUs) spatial analytical framework showing the new Global Shoreline Vector (GSV) along a stretch of coast in northeastern Puerto Rico. The GSV is shown with regularly spaced segments attributed and symbolised, in this case, by sinuosity. Perpendicular transects placed at segment intervals are also shown. The segments and transects represent potential spatial objects which could be attributed with data and used to delineate ECUs. The proposed ecological zonation is also shown, including offshore (a) and nearshore (b) coastal waters separated by the 30 m depth contour, and coastal land areas (c) between the GSV and the inland limit of the coastal plain.
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💧🌏 Greg Cocks

Daniel Coe’s Astonishing River Cartography
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orionmagazine.org/article/dani <-- shared media article
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dancoecarto.com/work <-- his website
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[those in the spatial hydrology ‘world’ have long been incredibly impressed by Dan Coe’s imagery and cartography, here is a wonderful article on cartography & science with his visual arts quality]
“Cartographer Daniel Coe uses relative elevation data, primarily from plane-mounted lasers called lidar, to visualize Earth’s natural features, like rivers and floodplains. His stunning river maps reveal stories hidden in historical sediment and past channels carved by the water, as it twists and turns through both landscape and time…”
#GIS #spatial #mapping #DanielCoe #cartography #hydrospatial #river #riverine #imagery #representation #map #representation #science #remotesensing #LiDAR #sedimentation #flooding #riverchannel #change #spatiotemporal #gischat
#DanielCoe #fluvial #geomorphology

LiDAR-derived river cartography - Mississippi Delta, USA
LiDAR-derived river cartography - Murray River, Australia
LiDAR-derived river cartography - bends in the North Fork Shenandoah River, Virginia, USA
LiDAR-derived river cartography - Tulsequah River, British Columbia, Canada
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💧🌏 Greg Cocks

U.S. Sea Level Change - Rising Seas, Changing Coasts [web resources/ Federal website]
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sealevel.globalchange.gov/ <-- shared web resource
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nasa.gov/earth/climate-change/ <-- NASA press release
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#GIS #spatial #mapping #spatialanalysis #spatiotemporal #risk #hazard #infrastructure #habitats #ecosystems #sealevel #sealevelrise #SLR #climatechange #webresources #spatialdata #opendata #coast #coastal #communities #USGCRP #US #USA #model #modeling #projections #flooding #innundation #water #hydrology #hydrospatial #interactive #multimedia #educational #management #planning #impacts #humanimpacts #coastalengineering #geomorphometry
@USEPA @fema @nasa @NOAA @USACEHQ @DeptofDefense @USGS @DHSgov

charts and text related to sea level rise, Puerto Rico
chart and text - satellite altimetry and tidal gauge measurements over time, Puerto Rico
screen shot - https://sealevel.globalchange.gov/ web page
aerial image - house at risk of the ocean, East Coast USA
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💧🌏 Greg Cocks

The Detection Of A Massive Harmful Algal Bloom In The Arctic Prompts Real-Time Advisories To Western Alaskan Communities
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phys.org/news/2024-07-massive- <-- shared technical article
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doi.org/10.1002/lol2.10421 <-- shared paper
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#GIS #spatial #mapping #sampling #publichealth #ecosystem #habitat #climatechange #harmful #agalbloom #HAB #polar #marine #healthimpacts #toxins #Arctic #water #hydrospatial #sampling #model #modeling #BeringStrait #magnitude #scale #density #toxicity #coast #coastal #remote #communities #FirstNation #risk #hazard #response #monitoring #hazardassessment #communication #realtime #advisories #Alaska #WesternAlaska #maritime #subsistence #harvest #fisheries #tracking #spatiotemporal #spatialanalysis #WHOI #PST #algae #foodchain #foodweb #mortality #impacts #subsidence #eventresponse #waterquality

model / map - the HAB (harmful algal bloom), Bering Strait, off Alaska coast
photo - A dashboard image from the IFCB shows high concentrations of the Alexandrium (dark round cells) found in a Bering Strait water sample.
maps - Regional map and progression of the 2022 Alexandrium catenella bloom based on near-surface cell densities. (A) Map of the region depicting major water bodies, land masses, and the maritime boundary with Russia. Alaskan communities within designated regional boroughs are indicated by colored points; regional hub communities are labeled in bold. Bloom observations are grouped by the outbound and return transit of each survey, where the gray dots are the shipboard data points; (B) 22 July–08 August, (C) 08–14 August, (D) 17–31 August, (E) 31 August–06 September. Graduated color scale indicates A. catenella cell density calculated from annotated IFCB imagery; observations are interpolated using a gridding routine that puts more weight along the isobaths (Davis 1998), since the flow on the Chukchi shelf is largely guided by the bathymetry. Locations of the regional hub communities are labeled, and an asterisk is used in (D) to indicate location of highest cell density measured in the bloom (174,000 cells L−1).
schematic - Timeline and structure of information flow from the shipboard IFCB to the regional coastal response. Steps in this process included: Data Collection (seconds to minutes), HAB Assessment (minutes to hours), Stakeholder Coordination and Advisory Development (24–48 h, see Supplementary Materials for advisory text), and Community Mobilization (days, weeks, continuing).
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💧🌏 Greg Cocks

The Vanishing Islands That Failed to Vanish [Maldives]
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nytimes.com/interactive/2024/0 <-- shared media article
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[be sure that many tropical islands ARE vanishing, like Tuvalu, and indeed many in the Maldives; this study is working to see why some are not or are not as fast as modeled (the extensive coastal engineering around the capital Male notwithstanding)]
#GIS #spatial #mapping #Maldives #climatechange #IndianOcean #model #modeling #coast #coastal #coastalengineering #SLR #sealevel #sealevelrise #tropicalisland #risk #hazard #mitigation #marine #ocean #hydrospatial #remotesensing #elevation #research #ontheground #spatialanalysis #spatiotemporal

photo - Curt Storlazzi installed a device to measure currents at a depth of 65 feet.
photo - The Maldives government have adapted infrastructure in capital city Malé to the threats of climate change, including beginning to build a wall around the city.
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