#30daymapchallenge2024 — Public Fediverse posts

#30DayMapChallenge Day 30: The final map
When you work at Kontur even your art is geospatial. Tied together the world, one nail at a time📌.

#30DayMapChallenge2024 #artmaps

#30DayMapChallenge Day 25: Heat
These maps compare the rising climate heat risk in the Amazon with forest health🌡️🌳. The results show how increasing temperatures and wildfire risks are closing in, rapidly degrading this vital ecosystem.
#foresthealth #KonturAtlas #30DayMapChallenge2024 

#30DayMapChallenge Day 23: Memory
This map by Noel Gorelick, co-founder of #GoogleEarthEngine & newest Kontur team member, combines Hansen Global Tree Cover/Loss dataset & 80+ workshop locations (from memory) that helped Earth Engine "map" its impact 🌲🌍.
#30DayMapChallenge2024

#30DayMapChallenge Day 23: Memory
This map by Noel Gorelick, co-founder of #GoogleEarthEngine & newest Kontur team member, combines Hansen Global Tree Cover/Loss dataset & 80+ workshop locations (from memory) that helped Earth Engine "map" its impact 🌲🌍.
#30DayMapChallenge2024

DATA
> Relative Wealth Index (https://data.humdata.org/dataset/relative-wealth-index)

PROCESS
1. Load the RWI point layer for the Philippines.
2. Style the layer as square markers—size: 2400 meters at scale; color: ramp of your choice.

#30DayMapChallenge #30DayMapChallenge2024 #Day8 #HDX #MadeWithQGIS #QGIS #FOSS4G #GISChat #Wealth #Poverty #RelativeWealthIndex #Meta

30 DAY MAP CHALLENGE 2024 | DAY 8 - DATA:HDX

Relative Wealth Index

The Relative Wealth Index (RWI) from Meta are microestimates showing the relative wealth and poverty of different areas in a country.

IMPORTANT: As with any global-scale, machine-learning product, you should first validate the usefulness and applicability to your local context.

#30DayMapChallenge #30DayMapChallenge2024 #Day8 #HDX #MadeWithQGIS #QGIS #FOSS4G #GISChat #Wealth #Poverty #RelativeWealthIndex #Meta

30 DAY MAP CHALLENGE 2024 | DAY 6 - RASTER
Albay at different resolutions (100m, 500m, 1000m, 5000m)

DATA
> Any Digital Elevation Model (DEM)

PROCESS
1. Resample the DEM into 100, 500, 1000, 5000m meter pixel sizes (e.g. using Warp (Reproject) algorithm)
2. Create polygon boundaries for each resampled DEM using Polygonize (raster to vector) and Dissolve.
3. Style #2 accordingly

...

#30DayMapChallenge #30DayMapChallenge2024 #Day6 #Raster #MadeWithQGIS #QGIS #FOSS4G #Albay

#30DayMapChallenge Day 6: Raster

Into aerial photography but don’t know where to host your imagery? 📸✈️ Check out openaerialmap.org!

Our colleague created this map to showcase this perfect solution for sharing high-quality aerial images with the world. This particular photo of their hometown was uploaded by an OpenAerialMap contributor under an open license. It can be used for mapping in OpenStreetMap, any GIS project, and shared on social media. 😊

#OpenAerialMap #GIS #30DayMapChallenge2024

NOTE
1. The flood hazard data has invalid geometries/features. You can resolve this by fixing the geometries (takes a long time) or simply disabling the Invalid features filtering in QGIS processing settings.
2. Some areas have no flood hazard features. These are marked as NO DATA in the maps.

#30DayMapChallenge #30DayMapChallenge2024 #Day4 #Hexagons #MadeWithQGIS #QGIS #FOSS4G #Kontur #UPRI #Flood #NCR #Albay #Cebu #Pangasinan

...
3. Generate centroids from the output of #2 (either using the Centroids algorithm or Geometry generators).
4. To speed up and automate the process, I created a model that runs steps 1-3 above.
5. Style the output of 3 using: marker = hexagon, size = depends on population, color = depends on hazard level (Var). Utilize data-defined overrides/Assistant.

#30DayMapChallenge #30DayMapChallenge2024 #Day4 #Hexagons #MadeWithQGIS #QGIS #FOSS4G #Kontur #UPRI #Flood #NCR #Albay #Cebu #Pangasinan

PROCESS
1. Use the "Sort" algorithm to create an ordered version of the flood hazard layer such that the features with high hazard level (3) will always be the first feature that will be matched in #2 below.
2. Run a "Join attributes by Location" between the population hex grid layer and the sorted/ordered flood hazard layer (output of #1).
...

#30DayMapChallenge #30DayMapChallenge2024 #Day4 #Hexagons #MadeWithQGIS #QGIS #FOSS4G #Kontur #UPRI #Flood #NCR #Albay #Cebu #Pangasinan

30 DAY MAP CHALLENGE 2024 | DAY 4 - HEXAGONS

Population ⬡ Flood Hazard
- larger hexagon = more people in the area
- redder color = higher hazard level

DATA
> Population density for 400m H3 Hexagons [Kontur] - https://data.humdata.org/dataset/kontur-population-philippines
> Flood hazard (100-year rain return) [UPRI/Project NOAH] - https://drive.google.com/drive/folders/10pCWTfU-gVuAbdx4gdUGaDcNrSzMz0Mm

#30DayMapChallenge #30DayMapChallenge2024 #Day4 #Hexagons #MadeWithQGIS #QGIS #FOSS4G #Kontur #UPRI #Flood #NCR #Albay #Cebu #Pangasinan

30 DAY MAP CHALLENGE 2024 | DAY 3 - POLYGONS

Shapes of (K)yøu(si)
of triangles, circles, and ovals

DATA
> Digitized from OpenStreetMap (copyright OSM contributors)

PROCESS
> Duplicate the digitized layer.
> Apply a hand-drawn smudgy-pen outline style and a pencil fill with categorized symbology.
> Styles are from the hand-drawn styles by Andy Woodruff (https://www.facebook.com/bnhr.xyz/posts/pfbid02BKbYMnv5quZcDjNoYiGnZPzc2MqWwU8YbuypFJMdYA242WibaNnsZLsYErvWQEfdl)

#30DayMapChallenge #30DayMapChallenge2024 #Day3 #Polygons #MadeWithQGIS #QGIS #QC #Kyusi #QuezonCity #Philippines