Nume MacAroon Ⓥ @nm

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**Greg Cocks** @GregCocks@techhub.social · Apr 16

Greg Cocks @GregCocks@techhub.social

RiverREM - Generating River Relative Elevation Model (REM) Visualisations
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https://github.com/OpenTopography/RiverREM <-- shared GitHub repository
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https://opentopography.github.io/RiverREM/ <-- shared documentation
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https://opentopography.org/blog/new-package-automates-river-relative-elevation-model-rem-generation <-- shared Open Topography blog post about RiverREM
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H/T Heidi Luchsinger / Open Topography
[this post should not be considered as an endorsement of this product aka caveat emptor]
#GIS #spatial #mapping #remotesensing #earthobservation #Python #LiDAR #RiverREM #visualisation #hydrology #water #river #rivervalley #floodplain #terraces #GitHub #opensource #opendata #DEM #REM #model #modeling #RiverRelativeModel #documentation #tutorial #learning #tool #elevation #raster #sinuosity #drainage

**George Silva** @georgesilva@mastodon.social · Apr 3 *

Apr 3 *

George Silva @georgesilva@mastodon.social

This is a TLDR of the presentation I did at #foss4g in Belém, last year.

Check it out: https://george-silva.hashnode.dev/efficient-methods-for-generating-zonal-statistics-in-gis

#gis #remotesensing #raster

**Greg Cocks** @GregCocks@techhub.social · Mar 18

Mar 18

Greg Cocks @GregCocks@techhub.social

New Map Of Landscape Beneath Antarctica Unveiled
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https://phys.org/news/2025-03-landscape-beneath-antarctica-unveiled.html <-- shared technical article
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https://doi.org/10.1038/s41597-025-04672-y <-- shared paper
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#GIS #spatial #mapping #Bedmap3 #icebed #surface #thickness #gridded #datasets #Antarctica #raster #model #modeling #landscape #elevation #icesheet #survey #remotesensing #earthobservation #climatechange #warming #climate #melt #melting #seafloor #subglacial #geophysical #survey #topography #geology #bathymetry #topobathy #BritishAntarcticSurvey
@BritishAntarcticSurvey

schematic / flow chart - Schematic showing the Bedmp3 source datasets (white boxes) combining to make intermediate products (blue boxes) and ultimately the final set of grids (orange boxes) and their uncertainties (yellow boxes). Note that the surface grid has a uniform estimated uncertainty (Section Uncertainty estimates).

maps - Bedmap3 grids of (a) bed topography and (b) surface elevation, in metres above sea level (g104c geoid), and (c) ice thickness in metres. Locations labelled in (b) are referred to in the text

The BedMachine v3 bed has some subjective advantages over Bedmap3 where glacier flow is relatively fast, but survey data are sparse. (a) Surface flow speed43; (b) BedMachine v3 bed topography; (c) Bedmap3 bed topography, both overlaid on shaded relief and with survey data shown as grey lines. The black dotted line highlights a trough under slow-flowing ice that is more smoothly continuous in Bedmap3. The white oval highlights the trough of a relatively fast-flowing ice stream that in BedMachine v3 is more smoothly streamlined and subjectively more realistic than in Bedmap3, given the typical streamlined form of deglaciated ice stream landscapes. An objective test of bed accuracy in this area requires more survey data.

maps - The Bedmap3 survey dataset allows us to calibrate the more continuous and extensive freeboard-based ice shelf thickness grid. (a) Pointwise ice thickness biases between 119,000 survey measurements and the freeboard-derived ice thickness grid47 on the Ross Ice Shelf, showing coherent patterns of bias; (b) these pointwise offsets median-filtered over a 20 km radius; (c) spline-interpolated calibration grid of the filtered offsets in (b); (d) bias-corrected version of the freeboard-derived ice thickness grid after subtraction of the calibration grid in (c).

**Greg Cocks** @GregCocks@techhub.social · Feb 19 *

Feb 19 *

Greg Cocks @GregCocks@techhub.social

Introduction To Remote Sensing And Geographical Information Systems [GIS]
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https://www.nateko.lu.se/sites/nateko.lu.se.sv/files/remote_sensing_and_gis_20111212.pdf <-- shared link to paper/publication
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[I have yet to dig into this myself, but it looks very promising]
#GIS #spatial #mapping #remotesensing #earthobservation #learning #onlinelearning #tutorial #education #learning #elearning #onlineclasses #distancelearning #school #virtuallearning #learn #edtech #digitallearning #students #remotelearning #student #onlinetraining #training #technology #spatialdata #spatialanalysis #spatiotemporal #concepts #satellite #imagery #aerialimagery #raster #vector #introduction #101

graphics - the chain of satellite data acquisition

cover - paper/publication - Introduction To Remote Sensing And Geographical Information Systems [GIS]

aerial photos - examples of a progression of aerial imagery (resolution, etc) from 1940 to 2010

LiDAR example - Laguna Creek, California, USA

**ראַף** @raf@babka.social · Feb 10

Feb 10

ראַף @raf@babka.social

Does anyone remember that equation that makes lines in pixel art look straight and not jagged?

#pixelartists #raster

**Greg Cocks** @GregCocks@techhub.social · Feb 7

Feb 7

Greg Cocks @GregCocks@techhub.social

Mapping Antarctica's Hidden Ice-Free Lands - A Blueprint For Conservation
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https://phys.org/news/2025-01-antarctica-hidden-ice-free-blueprint.html <-- shared technical article
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https://doi.org/10.1038/s41597-025-04424-y <-- shared paper / spatial dataset
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#GIS #spatial #inventory #mapping #Antarctic #ecosystems #wilderness #biodiversity #environmental #icefree #landcover #climatechange #humanimpacts #habitat #opendata #bioregional #abiotic #spatialmodel #biogeography #raster #model #modeling #spatialdata #futureproofing

work flow diagram - Amalgamation rules for Bioregional Ecosystem Types. Decision tree for lumping candidate bioregional combinations of Habitat Complex and ACBR into the final Bioregional Ecosystem Types. At least 5% of pixels in the candidate unit in question need to be next to a pixel of another unit to be considered “adjacent”. Red arrows are followed upward if the condition is not met, and green arrows are followed downward if it is.

Graphic representation of the hierarchical classification process. Large, coloured cells (top row) represent Tier 1 Major Environmental Units (E1-E5); nested cells (middle rows) represent Tier 2, Habitat Complexes (including Distinct Overlay Ecosystems); and dark blue circles (bottom row) represent Tier 3, Bioregional Ecosystem Types. Geothermal Major Environmental Units are represented as red, orange, and pink nested cells. Penguin breeding areas are represented as a green cell nested within E1. The Lakes Major Environmental Unit (L) has one Habitat Complex (L1) represented by light blue cells. Antarctic Conservation Biogeographic Regions (ACBRs) in Tier 3 are illustrated by semi-transparent horizontal bands. Numbers and sizes of cells and circles are not to scale and are intended for illustration purposes only. Circles representing Bioregional Ecosystem Types have been placed to indicate that not all combinations exist, and existing combinations vary in size.

maps - Spatial distribution of Habitat Complexes within each Major Environmental Unit (top left to bottom right): E1 mild lowlands; E2 midland mesic environments; E3 midland dry sunny environments; E4 rugged high mountains; E5 highland windy plateaus; and G1-G3 geothermal ecosystems with L1 lake ecosystems. Dark grey pixels on each map indicate distribution of ice-free areas assigned to other Major Environmental Units.

**Greg Cocks** @GregCocks@techhub.social · Jan 8

Jan 8

Greg Cocks @GregCocks@techhub.social

Adding 3D Elevation Program's Dynamic Elevation Web Coverage Services To ArcGIS Pro And AGOL [training video]
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https://www.usgs.gov/ngp-user-engagement-office/news/new-training-video-dynamic-elevation-service-arcgis-pro-and-agol <-- shared technical article
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https://youtu.be/sDEMHT2CmZw?si=u90-966VvslM6RXc <-- shared video
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https://www.usgs.gov/3d-elevation-program/about-3dep-products-services <-- about 3DEP products & services
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https://apps.nationalmap.gov/services/ <-- link to USGS National Map Web Services
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#GIS #spatial #mapping #elevation #LiDAR #ifSAR #3dep #ArcGISPro #AGOL #training #video #learning #NationalMap #services #raster #topography #opendata #DynamicElevationWebCoverageService #DigitalElevationModels #DEM #DTM #onlinelearning #tutorial
@USGS

screen shot - ArcGIS Pro - 3D view of landsurface elevation data

screen shot - USGS training video - Adding 3D Elevation Program's Dynamic Elevation Web Coverage Services To ArcGIS Pro And AGOL

map - ifSAR data of ground surface created by poster, near Kaktovik Alaska on the Beaufort Sea / Arctic

**Greg Cocks** @GregCocks@techhub.social · Nov 25, 2024

Nov 25, 2024

Greg Cocks @GregCocks@techhub.social

How Much And How Many? – Global Terrestrial Biomass And Species Richness
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https://www.pathfindergeospatial.ca/ <-- map generator, Dave Taylor, Pathfinder Geospatial
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https://doi.org/10.34892/rh7v-hg80 <-- shared dataset - Above And Below Ground Biomass Carbon, UNEP-WCMC (UN Environment Programme World Conservation Monitoring Centre)
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https://doi.org/10.1038/s41597-020-0444-4 <-- shared paper
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https://doi.org/10.1016/j.tree.2011.09.007 <-- shared paper
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[sharing of this map should not be considered as an endorsement of Pathfinder, just a personal and professional appreciation of this – and indeed many other maps - they generate]
“Biomass measured as above- and below-ground terrestrial carbon storage (tonnes of carbon per hectare) for c. 2010…
Species Richness is the number of species ranges estimated to occur in each grid cell…”
#GIS #spatial #mapping #cartography #giomass #species #richness #TerrestrialBiomass #SpeciesRichness #global #opendata #carbon #raster
@PathfinderGeospatial @DaveTaylor

global map - How Much And How Many? – Global Terrestrial Biomass And Species Richness - Pathfinder Geospatial

**Sean Jarrett** @jarrettinho@mapstodon.space · Sep 14, 2023

Sep 14, 2023

Sean Jarrett @jarrettinho@mapstodon.space

I want to run an unsupervised classification of a single band #raster layer in #qgis version 3.28.10. There used to be a SAGA Cluster Analysis for Grids tool. There also doesn't appear to be a suitable plugin. Can anyone help #gischat #gis