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BNHR.XYZ :tux: :qgis:

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  1. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    DATA
    > Relative Wealth Index (data.humdata.org/dataset/relat)

    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
  2. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    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
  3. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    30 DAY MAP CHALLENGE 2024 | DAY 7 - VINTAGE

    A (very maximalist) map of the University of the Philippines Diliman in vintage 16th/17th century European cartographic style (complete with some out-of-place sea monsters haha).

    DATA
    > UPD data

    PROCESS
    1. There are several ways to do this using QGIS, GIMP, or a combination of both.
    2. Fantasy map brushes/pngs from @kmalexander (kmalexander.com/free-stuff/fan)

    #30daymapchallenge #30daymapchallenge2024 #day7 #vintage #qgis #foss4g
  4. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    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
  5. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    ...

    DATA
    > TomTom 2023 Traffic Index (tomtom.com/traffic-index/ranki)
    > DPWH RBI (for the roads) | You can also use OpenStreetMap

    PROCESS
    1. Style the main EDSA road differently from the other roads.
    2. Add information in the Print Layout.
    3. Utilize the Print Layout's ability to render text as HTML to style the texts.

    ...


    #30daymapchallenge #30daymapchallenge2024 #day5 #journey #madewithqgis #qgis
  6. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    ...

    But maybe we can start by shifting away from car-centric designs, investing in safe and efficient public transport, creating spaces for walking and cycling, and putting people at the heart of urban planning.

    ...


    #30daymapchallenge #30daymapchallenge2024 #day5 #journey #madewithqgis #qgis
  7. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    ...

    Every person on the road lost an average of 117 hours (~5 days) waiting in traffic [2] during rush hour over the course of the year [3].

    Traffic is a wicked problem—so complex and intertwined that finding a single, definitive solution is virtually impossible.

    ...


    #30daymapchallenge #30daymapchallenge2024 #day5 #journey #madewithqgis #qgis
  8. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    30 DAY MAP CHALLENGE 2024 | DAY 5 - JOURNEY

    BYAHENG MAYNILA (loosely translated: Manila Trip/Journey)

    In TomTom's 2023 Traffic Index, the Manila metro area [1] ranked the worst among 387 cities with an average travel time of 25 mins 30 secs per 10 kilometers.

    ...


    #30daymapchallenge #30daymapchallenge2024 #day5 #journey #madewithqgis #qgis
  9. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    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
  10. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    ...
    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
  11. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    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
  12. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    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] - data.humdata.org/dataset/kontu
    > Flood hazard (100-year rain return) [UPRI/Project NOAH] - drive.google.com/drive/folders

    #30daymapchallenge #30daymapchallenge2024 #day4 #hexagons #madewithqgis #qgis
  13. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    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 (facebook.com/bnhr.xyz/posts/pf)

    #30daymapchallenge #30daymapchallenge2024 #day3 #polygons #madewithqgis #qgis
  14. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    30 DAY MAP CHALLENGE 2024 | DAY 2 - LINES

    a thousand cuts.
    Typhoon tracks from 1884-2024

    DATA
    > GADM country-level data (adm0)
    > International Best Track Archive for Climate Stewardship (IBTrACS)

    PROCESS
    > Add spatial index to the 2 layers.
    > Clip the IBTrACS layer with the GADM layer for the PHL.
    > Style the two layers accordingly with
    the PHL tracks slightly thicker.

    #30daymapchallenge #30daymapchallenge2024 #day2 #lines #madewithqgis #qgis
  15. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    30 DAY MAP CHALLENGE 2024 | DAY 1 - POINTS

    The Philippine archipelago mapped using 10^n points with each point being 1000 x 2^(6-n) meters in diameter.

    DATA
    > GADM country-level data (adm0)

    PROCESS
    > Use the "Random points inside polygons" algorithm in QGIS to generate layers with 10^n points
    > Style accordingly
    > Add the 6 layers into a single Print Layout

    #30daymapchallenge #30daymapchallenge2024 #day1 #points #madewithqgis #qgis
  16. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    First 2024 meetup in the books! Maraming salamat sa mga dumalo at nakibahagi!

    We will (hopefully) be doing this every 3rd/4th Thursday of the month for the rest of the year so we hope to meet more FOSS4G enthusiasts at future events!

    #foss4gph #foss4g #foss #opensource #qgis #philippines
  17. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    According to the authors of the paper published in iScience [4]: "With further improvements in stability of local clocks used for timing, it is anticipated that MuWNS can be adapted to improve autonomous mobile robot navigation and positioning as well as other underground and underwater practical applications."

    In what other ways do you think this technology can be used? Deep-sea mission navigation perhaps?

    #gps #gischat #navigation #positioning #muons #cosmic
  18. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    Muons have been used previously to image archeological structures, search for hidden Mayan ruins, and detect hidden corridors and chambers of the Great Pyramid of Giza [3].

    Recently, the first navigation with wireless muometric navigation system (MuWNS) in indoor and underground environments was successfully tested [4] showing accuracy exceeding the GPS single-point positioning.

    #gps #gischat #navigation #positioning #muons #cosmic
  19. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    You know GPS but have you heard of muPS (Muometric Positioning System)?

    The muometric positioning or navigation system (muPS/μPS/muNS) is a novel positioning/navigation system that utilizes the ubiquitous and highly-penetratve cosmic-ray muons [1][2].

    This technique does not require active signal generation [1][2] and is usable in environments where GPS/GNSS signals cannot reach such as underwater and underground.

    #gps #gischat #navigation #positioning #muons #cosmic
  20. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    Regardless of whether the threat of .zip (or .mov) domains are overblown, it doesn't hurt to be careful and remain vigilant when opening links (whether they have .zip or not at the end).

    #zip #mov #tld #domains #phishing #cybersecurity
  21. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    There have been some examples online of people registering .zip domains—some as a joke—to show how these can be used by malicious actors. While there are those who argue that these concerns are unwarranted and overblown, others believe that the general availability of .zip (and .mov) TLDs introduce additional risks our already precarious online environment—especially considering that not everyone might be aware of these risks.

    #zip #mov #tld #domains #phishing #cybersecurity
  22. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    3a. For the first visualization:
    - Apply a graduated symbology or "data-defined" symbology using the pop_sum field.

    3b. For the second visualization:
    - Use geometry generators and the "scale" expression with pop_sum and max(pop_sum) to create the bar/column graph.

    🧵 4/4

    #gis #qgis #geospatial #philippines #maps #cartography
  23. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    1. Used QGIS' "Create grid" algorithm to generate a grid of 30 second (or longitudes) covering the extent of the Philippines.

    2. Used the "Zonal Statistics" algorithm to compute for the sum of population (pop_sum) for each latitude (or longitude) using the WorldPop population data.

    🧵 3/4

    #gis #qgis #geospatial #philippines #maps #cartography
  24. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    The data used are a population raster (30 second/1km grid) from WorldPop and Philippine admin boundary map from GADM.

    The first map visualizes the population per 30 second of latitude (or longitude) using color while the second visualizes the population as a bar/column chart.

    The process was once again fairly straightforward.

    🧵 2/4

    #gis #qgis #geospatial #philippines #maps #cartography
  25. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    Friday is map day! Were you waiting for new maps/visualizations of Philippine population? Well, you're in luck because here's (or four really).

    This time they are maps of population per latitude (and longitude) in the Philippines. As usual, all the processing and map-making was done in QGIS.

    🧵 1/4

    #anotherone #gis #qgis #geospatial #philippines #maps
  26. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    - Ran the process dividing the country in 2 to 8 groups.

    What do you think?

    Note: I included the population of Highly Urbanized Cities and Component Cities in the population of the province/area that they are geographically located in (e.g. Basilan's population includes that of the city of Isabela).

    Data from PSA 2020 Census and GADM. Processed in QGIS.

    🧵 3/3

    #qgis #gis #philippines #population #maps #cartography
  27. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    - Made a population layer (based on 2020 Census) composed of provinces and NCR cities/municipality.

    - Used QGIS' "Order by expression" algorithm to sort the layer features based on their centroid latitude (x(centroid($geometry)).

    - Made a script that would divide the sorted features into groups whose population sum was approximately the same (or close to it).

    🧵 2/3

    #qgis #gis #philippines #population #maps #cartography
  28. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    Have you ever wondered what the Philippines would look like if we divided it into areas of equal population? Nope? Only me? Oh well here it is. 😅

    The process was fairly straightforward.

    🧵 1/3

    #qgis #gis #philippines #population #maps #cartography
  29. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    Can you pronounce QGIS 3.30's version name?

    QGIS 3.30 's-Hertogenbosch is currently in packaging. It's already available for Linux users from the QGIS repositories while Windows and Mac installers should be available soon.

    You can read the changelog at: changelog.qgis.org/en/qgis/ver or watch at youtube.com/watch?v=q7O819lFKc4

    What are you most excited about in QGIS 3.30?

    #qgis #gis #rat #rasters #vectors #geospatial
  30. BNHR.XYZ :tux: :qgis: @bnhrdotxyz ·

    Sharing the highlights of Pista ng Mapa and State of the Map Asia Conference 2022.

    A big thank you to everyone who helped and participated to make this the biggest celebration of open mapping and open geospatial in the the Philippines and in the Asian region!

    youtu.be/9WTnx_RQrBU

    #foss4g #osgeo #openstreetmap #gis #geospatial #opengeospatial