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#30DayMapChallenge Day 4 — Hexagons Today’s highlight is “Crystal Cities” by Mapbox map designer Stephen Kennedy. This map uses the Kontur Population hex grid dataset to visualize population density stylized as glowing crystal forms. Explore how data brings cities to life: #BuiltWithMapbox #Data

Mapbox

76,576 subscribers

15,895 views • 1 year ago •via X (Twitter)

Education Arts Science & Technology #30DayMapChallenge

Anya Rossi• Live Now

Private livecam show

4 Comments

Kontur1 year ago

Great to see Kontur population dataset featured in such beautiful maps for #30DayMapChallenge! 💯 Next time, give #KonturAtlas a try — we’ve added even more hexagonal data for you to explore at 🗺️

Emmanuel Okeke1 year ago

@Mapbox why is mapbox declining my credit card on sign-up?

AI Pill - e/acc⏫️1 year ago

Looks beautiful.

Geo Political Guy1 year ago

Love it!

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Mapbox has a brand new 3D map style, still in beta! But it didn’t have a hackable live demo, so at Skydio we created one 😎 , try it out here: The updates include: - Hundreds of new 3D models for famous landmarks - New symbolic design that works hand in hand with the style - Day/night light shift built in! How does this help? Through more accurate 3D maps: - Data displayed on the map is more useful as it’s easier to understand where you are (our brains think in 3D) - More immersive 3D experiences are unlocked, not just navigation Looking forward to seeing where Mapbox takes this next

Alberto

43,945 views • 3 years ago

BREAKING: Stephen Miller just said that the DOJ is working on exposing how Democrat controlled cities have been MANIPULATING crime data! "When we ultimately share the results, it will STUN you!" "There are even accusations that m*rders and homIcides were reported as accidents instead of m*rders." "This is how severe the manipulation of the crime data has been in the city. It will all be uncovered and brought to light."

BREAKING: Stephen Miller just said that the DOJ is working on exposing how Democrat controlled cities have been MANIPULATING crime data! "When we ultimately share the results, it will STUN you!" "There are even accusations that mrders and homIcides were reported as accidents instead of mrders." "This is how severe the manipulation of the crime data has been in the city. It will all be uncovered and brought to light."

Gunther Eagleman™

135,603 views • 1 year ago

📊 “Jews in Ukraine, 1897–2025?” A set of maps circulating online presents population figures under the title “Number of Jews in Ukraine (1897–2025).” The figures are real. The label is imprecise. Before 1991, there was no Ukrainian state. Therefore, population data from 1897, 1918, 1926 or 1939 cannot describe a country that did not exist. What these maps actually do is take historical census data and reassign it to the territory of today’s Ukraine, using modern borders as a frame for earlier periods. In 1897, western cities shown on the map were located in lands historically tied to Poland and later administered under Austro-Hungarian rule. Eastern and southern cities — including Kyiv, Odesa and Kharkiv — belonged to the Russian Empire. The Jewish population counted in that census were subjects of imperial states, not citizens of a Ukrainian nation-state. The same applies to later decades. From the 1920s until 1991, the territory was governed within the Soviet Union. Population changes during that period reflect war, genocide, Soviet policies, assimilation and emigration, not decisions of an independent Ukraine. Only after 1991 does it become accurate to speak of “Ukraine” as a state in demographic terms. From that point onward, the continued decline shown in the maps corresponds to post-Soviet migration patterns and, more recently, large-scale displacement caused by war. The maps therefore do not describe a continuous national history. They describe population changes across the same geographic space under different states: •Polish and Austro-Hungarian administration in the west •Russian imperial rule in the east •Soviet governance across most of the territory •Ukrainian statehood only after 1991 Without that clarification, the headline suggests historical continuity that did not exist. The data itself is not fabricated. The issue is how it is labeled. A technically accurate title would be: “Jewish population in the territory of today’s Ukraine, based on imperial, Soviet, and post-1991 data.” That framing reflects historical reality. Anything else simplifies borders that were never static. ⸻ If you like what we are doing — like, share, subscribe, and invite your friends for more. Follow us also on Facebook: Slavic Networks Nirali VVeles SlavicFreeSpirit

📊 “Jews in Ukraine, 1897–2025?” A set of maps circulating online presents population figures under the title “Number of Jews in Ukraine (1897–2025).” The figures are real. The label is imprecise. Before 1991, there was no Ukrainian state. Therefore, population data from 1897, 1918, 1926 or 1939 cannot describe a country that did not exist. What these maps actually do is take historical census data and reassign it to the territory of today’s Ukraine, using modern borders as a frame for earlier periods. In 1897, western cities shown on the map were located in lands historically tied to Poland and later administered under Austro-Hungarian rule. Eastern and southern cities — including Kyiv, Odesa and Kharkiv — belonged to the Russian Empire. The Jewish population counted in that census were subjects of imperial states, not citizens of a Ukrainian nation-state. The same applies to later decades. From the 1920s until 1991, the territory was governed within the Soviet Union. Population changes during that period reflect war, genocide, Soviet policies, assimilation and emigration, not decisions of an independent Ukraine. Only after 1991 does it become accurate to speak of “Ukraine” as a state in demographic terms. From that point onward, the continued decline shown in the maps corresponds to post-Soviet migration patterns and, more recently, large-scale displacement caused by war. The maps therefore do not describe a continuous national history. They describe population changes across the same geographic space under different states: •Polish and Austro-Hungarian administration in the west •Russian imperial rule in the east •Soviet governance across most of the territory •Ukrainian statehood only after 1991 Without that clarification, the headline suggests historical continuity that did not exist. The data itself is not fabricated. The issue is how it is labeled. A technically accurate title would be: “Jewish population in the territory of today’s Ukraine, based on imperial, Soviet, and post-1991 data.” That framing reflects historical reality. Anything else simplifies borders that were never static. ⸻ If you like what we are doing — like, share, subscribe, and invite your friends for more. Follow us also on Facebook: Slavic Networks Nirali VVeles SlavicFreeSpirit

Slavic Networks

58,121 views • 8 months ago

MUST-WATCH/SHARE INFO: The Truth About MASSIVE AI Data Centers Coming To A City Near YOU! "It Needs All The Power, But YOU Can't Have Any!" Power Grid Overloaded, Cities' Reservoirs Drained, & Forever Chemical Toxic Sludge Dumped Into The Water Table! This Is Absolutely HELLISH What's Being Done— A Giant Screw Job To Power AI As It Takes Control Of Your Life! 🔴ALEX JONES BREAKS THE LATEST LIVE:

MUST-WATCH/SHARE INFO: The Truth About MASSIVE AI Data Centers Coming To A City Near YOU! "It Needs All The Power, But YOU Can't Have Any!" Power Grid Overloaded, Cities' Reservoirs Drained, & Forever Chemical Toxic Sludge Dumped Into The Water Table! This Is Absolutely HELLISH What's Being Done— A Giant Screw Job To Power AI As It Takes Control Of Your Life! 🔴ALEX JONES BREAKS THE LATEST LIVE:

Alex Jones

58,296 views • 4 months ago

🚨 WATCH THIS MAP — JAPAN IS BEING REPLACED IN REAL TIME. 👀 This official animation shows the ratio of foreigners in their 20s by municipality from 2013 to 2024. Red = areas where it EXCEEDS 10%. Look how the red EXPLODES across the country — especially after KISHIDA took power. The so-called “WORST PRIME MINISTER IN JAPANESE HISTORY” opened the floodgates, and the surge has been relentless. Even now, under TAKAICHI and the LDP, the legal imm*gration faucet stays WIDE OPEN. The numbers are still climbing fast. This is not “temporary workers.” This is demographic transformation happening in front of our eyes — documented by government data. Japan’s young population is being swapped out municipality by municipality while politicians smile and talk about “orderly coexistence.” ENOUGH. JAPANESE PEOPLE: THROW THE LDP OUT OF POWER before there is nothing left to save. 🔥 The data doesn’t lie. The map doesn’t lie. Time to act like you still own your country. 🇯🇵 (Video Source: ニホンモニター)

🚨 WATCH THIS MAP — JAPAN IS BEING REPLACED IN REAL TIME. 👀 This official animation shows the ratio of foreigners in their 20s by municipality from 2013 to 2024. Red = areas where it EXCEEDS 10%. Look how the red EXPLODES across the country — especially after KISHIDA took power. The so-called “WORST PRIME MINISTER IN JAPANESE HISTORY” opened the floodgates, and the surge has been relentless. Even now, under TAKAICHI and the LDP, the legal imm*gration faucet stays WIDE OPEN. The numbers are still climbing fast. This is not “temporary workers.” This is demographic transformation happening in front of our eyes — documented by government data. Japan’s young population is being swapped out municipality by municipality while politicians smile and talk about “orderly coexistence.” ENOUGH. JAPANESE PEOPLE: THROW THE LDP OUT OF POWER before there is nothing left to save. 🔥 The data doesn’t lie. The map doesn’t lie. Time to act like you still own your country. 🇯🇵 (Video Source: ニホンモニター)

SAMURAI VOICE

12,010 views • 2 months ago

🗺️ Developed a real-time astrocartography console: planetary lines move across a live world map as earthquakes and live magnetometer data stream in, updating throughout the day. Originally coded the astro map in Pine Script on TradingView. Love Pine, but live earthquake feeds were kind of where it drew the 😅 On the right, a live density profile of the parans where the planetary lines cross, plotted by latitude. It updates in real time as the sky changes, so you can watch the entire distribution breathe throughout the day. An instrument designed to explore the question, not to answer it. Inspired by Jim Lewis's astrocartography and Richard Cordaro's geomagnetic-anomaly work. Here's the console in action from the beginning of today (UTC).

Blueprint Research 🫆

11,677 views • 1 month ago

2/2) Here is the paper: Video Abstract: 🧠 Unique Population, Unique Data The LMHR group is distinct population with exceptionally high LDL-C, high HDL-C and low triglycerides that emerges as a metabolic response to carbohydrate restriction vis-a-vis the Lipid Energy Model ⚠️ Caveats These are preliminary data, so let’s not overstate the findings. However, dismissing them outright would ignore the unique metabolic response of this population, which differs significantly from other causes of high LDL-C. 📢 Your Role Now it’s time to put YOU to work! Share this paper, tweet, and video abstract widely. These data need to be discussed, even if (especially if) it makes some people uncomfortable. 🤓Further Learning I encourage you to explore more on ApoB, ACM, and different causes of high LDL. You can start on this 30+ video playlist on the topic. 🌍 Stay Open-Minded Avoid becoming a hyper-extremist—whether an “LDL denier” or “LMHR denier.” This research is still evolving, and we’ll make the most progress by staying open to new data and discussing it thoughtfully #LMHR #KetoDiet #LDL

2/2) Here is the paper: Video Abstract: 🧠 Unique Population, Unique Data The LMHR group is distinct population with exceptionally high LDL-C, high HDL-C and low triglycerides that emerges as a metabolic response to carbohydrate restriction vis-a-vis the Lipid Energy Model ⚠️ Caveats These are preliminary data, so let’s not overstate the findings. However, dismissing them outright would ignore the unique metabolic response of this population, which differs significantly from other causes of high LDL-C. 📢 Your Role Now it’s time to put YOU to work! Share this paper, tweet, and video abstract widely. These data need to be discussed, even if (especially if) it makes some people uncomfortable. 🤓Further Learning I encourage you to explore more on ApoB, ACM, and different causes of high LDL. You can start on this 30+ video playlist on the topic. 🌍 Stay Open-Minded Avoid becoming a hyper-extremist—whether an “LDL denier” or “LMHR denier.” This research is still evolving, and we’ll make the most progress by staying open to new data and discussing it thoughtfully #LMHR #KetoDiet #LDL

Nick Norwitz MD PhD

13,178 views • 2 years ago

GeoLibre v1.6.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings multi-map layouts, advanced cartographic symbology and labeling, and a one-click way to install external plugins from a zip. What's new in v1.6.0 - Multi-map grid: Split the workspace into a grid of synchronized map views to compare basemaps, layers, or time steps side by side. - Advanced symbology: Style features with a rule-based renderer, proportional symbols, fill patterns, and a built-in marker library. - Label engine: Label vector features by any attribute, with full placement and styling control. - Install plugins from a zip: Add external plugins from an uploaded zip on both desktop and web. - New vector analysis: Movement, space-time, and cell-coverage tools under Processing. - Faster sample data: Ready-to-load example datasets from a dropdown in every Add Data panel. - Place search in the layer panel: Geocode and fly to a location without leaving the Layers panel. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python #Cartography

GeoLibre v1.6.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings multi-map layouts, advanced cartographic symbology and labeling, and a one-click way to install external plugins from a zip. What's new in v1.6.0 - Multi-map grid: Split the workspace into a grid of synchronized map views to compare basemaps, layers, or time steps side by side. - Advanced symbology: Style features with a rule-based renderer, proportional symbols, fill patterns, and a built-in marker library. - Label engine: Label vector features by any attribute, with full placement and styling control. - Install plugins from a zip: Add external plugins from an uploaded zip on both desktop and web. - New vector analysis: Movement, space-time, and cell-coverage tools under Processing. - Faster sample data: Ready-to-load example datasets from a dropdown in every Add Data panel. - Place search in the layer panel: Geocode and fly to a location without leaving the Layers panel. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python #Cartography

Qiusheng Wu

15,473 views • 2 months ago

From 1900 to 1970, land and sea temperatures rose almost identically. But after 1970, land readings shot up while the oceans warmed only slightly. The reason isn't a sudden "climatic change," but a measurement one. As the global population doubled, cities sprawled and weather stations once surrounded by open fields were swallowed by concrete, asphalt and traffic. This creates what's known as the 'urban heat island effect.' Cities trap heat during the day and release it slowly at night, keeping local temperatures artificially higher than the surrounding countryside. That extra warmth shows up in the records, pushing land data upward. The oceans, of course, have remained unaffected by city sprawl, and they show a more gentle, gradual rise. It isn't CO2, it's concrete.

From 1900 to 1970, land and sea temperatures rose almost identically. But after 1970, land readings shot up while the oceans warmed only slightly. The reason isn't a sudden "climatic change," but a measurement one. As the global population doubled, cities sprawled and weather stations once surrounded by open fields were swallowed by concrete, asphalt and traffic. This creates what's known as the 'urban heat island effect.' Cities trap heat during the day and release it slowly at night, keeping local temperatures artificially higher than the surrounding countryside. That extra warmth shows up in the records, pushing land data upward. The oceans, of course, have remained unaffected by city sprawl, and they show a more gentle, gradual rise. It isn't CO2, it's concrete.

Electroverse

16,032 views • 1 month ago

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

Mathelirium

139,757 views • 9 months ago

✊ Data belongs to the people. Democracy runs on transperancy West Bengal's Special Intensive Revision (SIR) 2026 data ie. the data that determines whether your name stays on the voter list, is technically "public." But try accessing it. You'll hit CAPTCHAs. Download limits. Scanned PDFs that no machine can read. Data buried so deep it may as well not exist. So we did something about it. Sabar Institute, with the help of our researcher Souptik Halder and support from our team of SABIR AHAMED, Ashin Chakraborty and Sohail Mallick has built free, open, interactive maps of SIR 2026 data across all 294 West Bengal Assembly constituencies and we're making them available to every journalist, researcher, activist, and citizen who needs them. 🪦 ASDD Deletion Map — See exactly where voters are being deleted as Absent, Shifted, Dead, or Duplicate. Track overall deletion %, gender ratio, death counts, untraceable voters — assembly by assembly, on a live map. ⚖️ Supplementary Adjudication Map — Follow the adjudication trail: who's under review, how many were added or deleted, what percentage are still pending — across every single constituency. Why does this matter? Because mass deletions from voter rolls don't affect everyone uniformly. They happen in specific places, to specific communities, in patterns that deserve scrutiny. You cannot scrutinize what you cannot see. 🔗 Link to explore the map is in the next tweet If this work matters to you, support us using the link below👇 #DataForBetterLives

✊ Data belongs to the people. Democracy runs on transperancy West Bengal's Special Intensive Revision (SIR) 2026 data ie. the data that determines whether your name stays on the voter list, is technically "public." But try accessing it. You'll hit CAPTCHAs. Download limits. Scanned PDFs that no machine can read. Data buried so deep it may as well not exist. So we did something about it. Sabar Institute, with the help of our researcher Souptik Halder and support from our team of SABIR AHAMED, Ashin Chakraborty and Sohail Mallick has built free, open, interactive maps of SIR 2026 data across all 294 West Bengal Assembly constituencies and we're making them available to every journalist, researcher, activist, and citizen who needs them. 🪦 ASDD Deletion Map — See exactly where voters are being deleted as Absent, Shifted, Dead, or Duplicate. Track overall deletion %, gender ratio, death counts, untraceable voters — assembly by assembly, on a live map. ⚖️ Supplementary Adjudication Map — Follow the adjudication trail: who's under review, how many were added or deleted, what percentage are still pending — across every single constituency. Why does this matter? Because mass deletions from voter rolls don't affect everyone uniformly. They happen in specific places, to specific communities, in patterns that deserve scrutiny. You cannot scrutinize what you cannot see. 🔗 Link to explore the map is in the next tweet If this work matters to you, support us using the link below👇 #DataForBetterLives

SABAR Institute

31,593 views • 5 months ago

You've been watching football wrong your entire life. This 40-minute Databricks talk on how LaLiga uses data is the proof. The goals and assists you obsess over are the least interesting numbers on the pitch. By fusing tracking data (every player's position, many times a second) with eventing data (every action on the ball), LaLiga measures the invisible game space created, defensive lines pulled apart, the value of a run nobody passed to. The best player in a match is often the one who never touched the scoresheet. Pair it with article by Roan and you are good. Once you see the game as data, you can't unsee it.

You've been watching football wrong your entire life. This 40-minute Databricks talk on how LaLiga uses data is the proof. The goals and assists you obsess over are the least interesting numbers on the pitch. By fusing tracking data (every player's position, many times a second) with eventing data (every action on the ball), LaLiga measures the invisible game space created, defensive lines pulled apart, the value of a run nobody passed to. The best player in a match is often the one who never touched the scoresheet. Pair it with article by Roan and you are good. Once you see the game as data, you can't unsee it.

gemchanger

79,892 views • 3 months ago

GeoLibre v1.10.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings photorealistic city-scale 3D to the map, adds OGC API vector tiles, and makes vector tiles and live editing easier to work with. What's new in v1.10.0 - Google Photorealistic 3D Tiles: drape entire cities in photorealistic 3D right in the map, streamed and rendered through - ArcGIS I3S scene layers: stream Integrated Mesh and 3D Object scene layers and render them in 3D on the shared instance. - OGC API vector tiles: add standards-based OGC API - Tiles vector tile services as a remote source, right alongside XYZ and ArcGIS vector tiles. - Local HDF5 and NetCDF-4 loading: open scientific HDF5 and NetCDF-4 files straight from disk, no cloud references required. - GeoEditor from the current view: pull the vector features currently visible in the map into the GeoEditor and start editing what you are looking at, without re-importing the source data. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre

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Qiusheng Wu

24,578 views • 2 months ago

🚀 Quality-of-Life Boost: Enhanced Utilities Today’s update adds a set of practical tools designed to make WeatherWise more powerful and easier to use: • Map Action Menu - Right click on desktop or long press on mobile to: - Turn on the nearest radar tower - See and copy the GPS location - Inspect data on the map - Plus more • Measuring Tool - drop a single range ring or draw multiple rings to quickly judge how far away a storm is from you or your saved locations - On Desktop: a new "m" keyboard shortcut will activate this • Enhanced Search - search for METAR stations or even precise GPS coordinates • Map Scale Legend - always know your distances at a glance with a clear, built-in scale on the map Available now for free on: iOS: Android: Browser: And to Plus/Pro subscribers using our Windows/Mac/Linux App

🚀 Quality-of-Life Boost: Enhanced Utilities Today’s update adds a set of practical tools designed to make WeatherWise more powerful and easier to use: • Map Action Menu - Right click on desktop or long press on mobile to: - Turn on the nearest radar tower - See and copy the GPS location - Inspect data on the map - Plus more • Measuring Tool - drop a single range ring or draw multiple rings to quickly judge how far away a storm is from you or your saved locations - On Desktop: a new "m" keyboard shortcut will activate this • Enhanced Search - search for METAR stations or even precise GPS coordinates • Map Scale Legend - always know your distances at a glance with a clear, built-in scale on the map Available now for free on: iOS: Android: Browser: And to Plus/Pro subscribers using our Windows/Mac/Linux App

WeatherWise.app

23,265 views • 1 year ago

GeoLibre v2.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release is about reaching more data and moving through it: new browsers for STAC, NASA Earthdata, and Hugging Face, a flight simulator, a Time Slider that animates tiled data and data cubes, and a live API for pages that embed the map. What's new in v2.4.0 - STAC catalogs browser: discover public catalogs from STAC Index, connect to static catalogs and STAC APIs, search a collection's items, and add any visualizable asset to the map. No more copying COG URLs by hand. - Earthdata GIS browser: search NASA's Earthdata GIS portal and add its imagery, map, and feature services, and its published web maps, as first-class layers. - Hugging Face on the map: search the Hub, walk a dataset repo's folders, and add its vector and raster files. You can create a dataset repo and upload layers to it too. - Flight Simulator: steer a continuous free-flight camera over terrain and 3D layers from the keyboard, instead of declaring a destination and watching a scripted flight. - Time Slider for tiled data and data cubes: bind vector tiles, PMTiles, and MBTiles to the timeline and animate them over their full extent, and let a Zarr store's own time dimension join the shared timeline. - Zarr gets a real Add Data path: open a remote store or a folder on disk, and pick variables and dimensions by their actual coordinate values rather than raw indices. - Live embed API: a versioned postMessage protocol so a host page can load a project, move the camera, highlight features, and open a tool at runtime, with events coming back out. - OGC API - Features: add collections as vector layers from whatever URL you have in hand, whether that is a landing page, /collections, or a full items URL. - H3 everywhere: a new hexagonal grid plugin that renders and inspects H3 cells and exports them as GeoJSON or CSV, plus typing an H3 index into the search box to fly straight to that cell. - Jupyter from outside the app: attach VS Code's Jupyter extension or jupyter console to the desktop app's server and your notebook cells drive the map. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #GeoLibre

GeoLibre v2.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release is about reaching more data and moving through it: new browsers for STAC, NASA Earthdata, and Hugging Face, a flight simulator, a Time Slider that animates tiled data and data cubes, and a live API for pages that embed the map. What's new in v2.4.0 - STAC catalogs browser: discover public catalogs from STAC Index, connect to static catalogs and STAC APIs, search a collection's items, and add any visualizable asset to the map. No more copying COG URLs by hand. - Earthdata GIS browser: search NASA's Earthdata GIS portal and add its imagery, map, and feature services, and its published web maps, as first-class layers. - Hugging Face on the map: search the Hub, walk a dataset repo's folders, and add its vector and raster files. You can create a dataset repo and upload layers to it too. - Flight Simulator: steer a continuous free-flight camera over terrain and 3D layers from the keyboard, instead of declaring a destination and watching a scripted flight. - Time Slider for tiled data and data cubes: bind vector tiles, PMTiles, and MBTiles to the timeline and animate them over their full extent, and let a Zarr store's own time dimension join the shared timeline. - Zarr gets a real Add Data path: open a remote store or a folder on disk, and pick variables and dimensions by their actual coordinate values rather than raw indices. - Live embed API: a versioned postMessage protocol so a host page can load a project, move the camera, highlight features, and open a tool at runtime, with events coming back out. - OGC API - Features: add collections as vector layers from whatever URL you have in hand, whether that is a landing page, /collections, or a full items URL. - H3 everywhere: a new hexagonal grid plugin that renders and inspects H3 cells and exports them as GeoJSON or CSV, plus typing an H3 index into the search box to fly straight to that cell. - Jupyter from outside the app: attach VS Code's Jupyter extension or jupyter console to the desktop app's server and your notebook cells drive the map. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #GeoLibre

Qiusheng Wu

14,268 views • 1 month ago

China Has 50 Million Homeless. Yes, FIFTY MILLION. China claims it eliminated poverty. But the reality on the ground is far darker. While Western media obsess over homelessness in LA or San Francisco, no one’s talking about China’s own homeless population, which is as high as 50 MILLION. In this video, I break down the ugly truth about mass homelessness in China with hard data, real examples, and firsthand experience from my time living there. From ghost cities full of empty apartments to migrant workers crammed into unsafe slums, this is the story of human wreckage in the shadow of skyscrapers.

China Has 50 Million Homeless. Yes, FIFTY MILLION. China claims it eliminated poverty. But the reality on the ground is far darker. While Western media obsess over homelessness in LA or San Francisco, no one’s talking about China’s own homeless population, which is as high as 50 MILLION. In this video, I break down the ugly truth about mass homelessness in China with hard data, real examples, and firsthand experience from my time living there. From ghost cities full of empty apartments to migrant workers crammed into unsafe slums, this is the story of human wreckage in the shadow of skyscrapers.

Ken Cao-The China Crash Chronicle

23,716 views • 6 months ago

Introducing the new UNESCO Sites Navigator—a powerful new digital platform designed for the exploration, analysis, and monitoring of UNESCO-designated sites worldwide. This interactive tool provides verified, geospatial data on #WorldHeritage properties, #BiosphereReserves, and #GlobalGeoparks. With advanced cartographic features, users can explore site boundaries and information, measure and annotate directly on the map, import/export shapefiles, and access reliable data to support research and conservation. Funded by the Flanders, the platform is strengthening capacities for effective and sustainable heritage management globally. Discover how geospatial technology is transforming heritage conservation. Start exploring today: Flanders DFA #47WHC

Introducing the new UNESCO Sites Navigator—a powerful new digital platform designed for the exploration, analysis, and monitoring of UNESCO-designated sites worldwide. This interactive tool provides verified, geospatial data on #WorldHeritage properties, #BiosphereReserves, and #GlobalGeoparks. With advanced cartographic features, users can explore site boundaries and information, measure and annotate directly on the map, import/export shapefiles, and access reliable data to support research and conservation. Funded by the Flanders, the platform is strengthening capacities for effective and sustainable heritage management globally. Discover how geospatial technology is transforming heritage conservation. Start exploring today: Flanders DFA #47WHC

UNESCO

11,626 views • 1 year ago

Here's a copy/paste prompt recipe and vid showing exactly how to ask an LLM for an interactive map with satellite/map layers + a georeferencer that lets you see how old maps correspond with modern geography. Today the computer can’t make good print maps (that's your hill to climb ) but it can, with five bucks and twenty minutes, make good interactive maps. No software/GIS knowledge necessary, you just need a few nouns and an LLM. Scroll to the bottom for the repo/live map if you want those. I'm using Claude Code as an extension in VS Code but you can use the Claude CLI, Cursor, whatever. 1) Let's grab an old cadastral map and see who owned big tracts of a city; I found this an 1854 map of Niagara Falls, NY I found in the Library of Congress: , grabbed the .jp2, saved as a jpg from photoshop. 2) Let's ask Claude Code for a map. You can see exactly what I did in the video but my prompt, sans simple "hey it's busted" debugging, is written out in the following paragraphs. I explain the map-specific nouns in brackets. You can likely dump this whole thing in your LLM window and it'll work; I'd try plan mode + skip permissions. THE PROMPT Make an interactive map with MapLibre GL JS [maplibre is a javascript mapping library, a FOSS version of Mapbox GL JS. This lets us display tiled map data and arbitrary images on the map] Add basemap toggles with Esri satellite, Carto Positron, and OSM [these map layers require no API keys for light usage; Carto Positron is a nice road map layer and OSM is ugly but comprehensive] Add a globe/mercator projection toggle [I think the globe looks better at low zooms] Add a layer panel on the left with visibility checkboxes and delete buttons. Add a search box on the map that flies to results, with deletable pin markers [Makes this easy to get to your area of interest] Include an interactive local georeferencer: drop a JPG, pick ground control points on a zoomable/pannable image viewer, place them on the map, watch it warp with a progress bar centered on the map. [The georeferencer uses math ("affine transform"??) to match points on the old map to points on the new map; generally you click road intersections on the old map, match them on the new map, repeat a dozen times and everything aligns] The georeferenced map overlay defaults to 25% opacity with a slider above the control point list. [I want it easy to see the underlying modern geography] Add Export/import control point buttons [this saves the control points as a JSON so you can save and reimport your work] Add a button to export the warped image as a GeoTIFF with a .prj [In case you want to add the georeferenced image to a real GIS program like QGIS] Look up all relevant docs before starting [Claude sometimes uses outdated stuff] Split everything into separate HTML/CSS/JS files [Claude tends to pile everything in index.html, which is hard to read] Use Optima font, base color #FEFAF6 [I just like this style] Let me test with a local server [it serves it on a simple server so you can nav your host to localhost:8000 and try it out] Log all errors [so you don't have to play telephone with the LLM describing what's busted] 3) Once your LLM finishes, test it out in your browser; if it doesn't work, ask the LLM to check logs. Repeat 'til functional. 4) After this works on your computer, you can show it to everyone by hosting it on GitHub: prompt with "write a README explaining what everything does, add it to a new GitHub repo, deploy using GitHub pages, gimme the live URL" Here's what Claude made for me, try it yourself: • Upload the JPG in the repo, which is linked below • "Add GCP" • Click somewhere recognizable on the old map, like the tip of an island or a road intersection • Click the matching point on the new map • Repeat til you have least 3x points • Hit "georeference" • You'll see the old map atop the new map; if you want a better fit, delete bad points or add a dozen new ones, hit georeference again, repeat Repo: Is this map robust? Human-maintainable? Elegant? Performant? Secure? No, but *your* personal web map need not be. It just needs to work for *your* narrow use case, because it’s *your* map.

Here's a copy/paste prompt recipe and vid showing exactly how to ask an LLM for an interactive map with satellite/map layers + a georeferencer that lets you see how old maps correspond with modern geography. Today the computer can’t make good print maps (that's your hill to climb ) but it can, with five bucks and twenty minutes, make good interactive maps. No software/GIS knowledge necessary, you just need a few nouns and an LLM. Scroll to the bottom for the repo/live map if you want those. I'm using Claude Code as an extension in VS Code but you can use the Claude CLI, Cursor, whatever. 1) Let's grab an old cadastral map and see who owned big tracts of a city; I found this an 1854 map of Niagara Falls, NY I found in the Library of Congress: , grabbed the .jp2, saved as a jpg from photoshop. 2) Let's ask Claude Code for a map. You can see exactly what I did in the video but my prompt, sans simple "hey it's busted" debugging, is written out in the following paragraphs. I explain the map-specific nouns in brackets. You can likely dump this whole thing in your LLM window and it'll work; I'd try plan mode + skip permissions. THE PROMPT Make an interactive map with MapLibre GL JS [maplibre is a javascript mapping library, a FOSS version of Mapbox GL JS. This lets us display tiled map data and arbitrary images on the map] Add basemap toggles with Esri satellite, Carto Positron, and OSM [these map layers require no API keys for light usage; Carto Positron is a nice road map layer and OSM is ugly but comprehensive] Add a globe/mercator projection toggle [I think the globe looks better at low zooms] Add a layer panel on the left with visibility checkboxes and delete buttons. Add a search box on the map that flies to results, with deletable pin markers [Makes this easy to get to your area of interest] Include an interactive local georeferencer: drop a JPG, pick ground control points on a zoomable/pannable image viewer, place them on the map, watch it warp with a progress bar centered on the map. [The georeferencer uses math ("affine transform"??) to match points on the old map to points on the new map; generally you click road intersections on the old map, match them on the new map, repeat a dozen times and everything aligns] The georeferenced map overlay defaults to 25% opacity with a slider above the control point list. [I want it easy to see the underlying modern geography] Add Export/import control point buttons [this saves the control points as a JSON so you can save and reimport your work] Add a button to export the warped image as a GeoTIFF with a .prj [In case you want to add the georeferenced image to a real GIS program like QGIS] Look up all relevant docs before starting [Claude sometimes uses outdated stuff] Split everything into separate HTML/CSS/JS files [Claude tends to pile everything in index.html, which is hard to read] Use Optima font, base color #FEFAF6 [I just like this style] Let me test with a local server [it serves it on a simple server so you can nav your host to localhost:8000 and try it out] Log all errors [so you don't have to play telephone with the LLM describing what's busted] 3) Once your LLM finishes, test it out in your browser; if it doesn't work, ask the LLM to check logs. Repeat 'til functional. 4) After this works on your computer, you can show it to everyone by hosting it on GitHub: prompt with "write a README explaining what everything does, add it to a new GitHub repo, deploy using GitHub pages, gimme the live URL" Here's what Claude made for me, try it yourself: • Upload the JPG in the repo, which is linked below • "Add GCP" • Click somewhere recognizable on the old map, like the tip of an island or a road intersection • Click the matching point on the new map • Repeat til you have least 3x points • Hit "georeference" • You'll see the old map atop the new map; if you want a better fit, delete bad points or add a dozen new ones, hit georeference again, repeat Repo: Is this map robust? Human-maintainable? Elegant? Performant? Secure? No, but your personal web map need not be. It just needs to work for your narrow use case, because it’s your map.

Evan Applegate

15,772 views • 5 months ago

'Climate Change' Will Be Used As A Reason To Take Away Your Home & Confine You To A Smart City. Del Bigtree "There will be cameras on every lamppost, watching you from every nook & cranny, turning your heat up & down for you, telling you whether you can drive 2 blocks from home" Insurance companies are citing "climate change" as a pretext to raise natural disaster insurance premiums by 3 to 10 times, even though insured losses have remained nearly flat over the past decade. This practice threatens homeowners with unaffordable policies, forcing some to sell their homes or risk foreclosure as banks demand coverage. Del Bigtree warns that this trend will lead to widespread home losses across America, turning cities like Los Angeles into heavily surveilled 'smart cities' under authoritarian control. Smart Cities Will Be The End Of Democracy & Autonomy: --Privacy Concerns-- Data Collection: Smart cities rely on vast amounts of data from various sources, including surveillance cameras, sensors & personal devices. This data is used to optimize city functions, but it also raises serious privacy issues. Residents find their every move tracked, leading to a loss of personal privacy. Data Security: The more data is collected, the greater the risk of being hacked or misused. Cybersecurity threats are a significant concern & a breach leads to sensitive personal information being exposed or exploited. --Environmental Impact-- E-Waste: Smart cities involves the rapid turnover of electronic devices, leading to an increase in electronic waste. Resource Consumption: Production & maintenance of these technologies require significant amounts of energy & raw materials, offsetting any benefits. --Social Implications-- Surveillance State: The extensive use of surveillance technologies to constantly monitor citizens, stifles freedom of expression & creates a culture of fear. Loss of Community: The focus on technology & efficiency leads to a loss of community spirit & human interaction. Residents are isolated as they rely more on digital interfaces than on personal relationships. --Health Risks-- Radiation Exposure: The widespread deployment of wireless technologies in smart cities, including 5G networks, raises health risks with prolonged exposure to electromagnetic radiation. Mental Health: The constant connectivity & surveillance in smart cities contributes to stress & anxiety among residents, negatively impacting their mental well being. --Infrastructure Vulnerability-- Cyber Attacks: Smart city infrastructure, heavily reliant on interconnected digital systems, is vulnerable to cyber-attacks. A successful attack disrupts critical services such as power, water & transportation, causing widespread chaos. System Failures: Overreliance on technology leads to significant problems when systems fail or malfunction. Resulting in disruptions to essential services & risks to public safety. --Ethical Concerns-- Bias in Algorithms: The algorithms used in smart city technologies perpetuate existing biases, leading to unequal treatment of different demographic groups. Resulting in discriminatory practices & reinforcing social inequalities. Lack of Transparency: Smart city systems make opaque decisions, lacking transparency in how they use data & make decisions. This erodes trust in public institutions & undermines democratic processes. 👇Smart Cities & Ethical Implications👇 👇Smart Cities Are Dangerous👇 👇Smart Cities & Citizens Discontent👇 Speakers: Del Bigtree & Sean Kelly | Digital Social Hour Podcast Video: @fitconqueror1

'Climate Change' Will Be Used As A Reason To Take Away Your Home & Confine You To A Smart City. Del Bigtree "There will be cameras on every lamppost, watching you from every nook & cranny, turning your heat up & down for you, telling you whether you can drive 2 blocks from home" Insurance companies are citing "climate change" as a pretext to raise natural disaster insurance premiums by 3 to 10 times, even though insured losses have remained nearly flat over the past decade. This practice threatens homeowners with unaffordable policies, forcing some to sell their homes or risk foreclosure as banks demand coverage. Del Bigtree warns that this trend will lead to widespread home losses across America, turning cities like Los Angeles into heavily surveilled 'smart cities' under authoritarian control. Smart Cities Will Be The End Of Democracy & Autonomy: --Privacy Concerns-- Data Collection: Smart cities rely on vast amounts of data from various sources, including surveillance cameras, sensors & personal devices. This data is used to optimize city functions, but it also raises serious privacy issues. Residents find their every move tracked, leading to a loss of personal privacy. Data Security: The more data is collected, the greater the risk of being hacked or misused. Cybersecurity threats are a significant concern & a breach leads to sensitive personal information being exposed or exploited. --Environmental Impact-- E-Waste: Smart cities involves the rapid turnover of electronic devices, leading to an increase in electronic waste. Resource Consumption: Production & maintenance of these technologies require significant amounts of energy & raw materials, offsetting any benefits. --Social Implications-- Surveillance State: The extensive use of surveillance technologies to constantly monitor citizens, stifles freedom of expression & creates a culture of fear. Loss of Community: The focus on technology & efficiency leads to a loss of community spirit & human interaction. Residents are isolated as they rely more on digital interfaces than on personal relationships. --Health Risks-- Radiation Exposure: The widespread deployment of wireless technologies in smart cities, including 5G networks, raises health risks with prolonged exposure to electromagnetic radiation. Mental Health: The constant connectivity & surveillance in smart cities contributes to stress & anxiety among residents, negatively impacting their mental well being. --Infrastructure Vulnerability-- Cyber Attacks: Smart city infrastructure, heavily reliant on interconnected digital systems, is vulnerable to cyber-attacks. A successful attack disrupts critical services such as power, water & transportation, causing widespread chaos. System Failures: Overreliance on technology leads to significant problems when systems fail or malfunction. Resulting in disruptions to essential services & risks to public safety. --Ethical Concerns-- Bias in Algorithms: The algorithms used in smart city technologies perpetuate existing biases, leading to unequal treatment of different demographic groups. Resulting in discriminatory practices & reinforcing social inequalities. Lack of Transparency: Smart city systems make opaque decisions, lacking transparency in how they use data & make decisions. This erodes trust in public institutions & undermines democratic processes. 👇Smart Cities & Ethical Implications👇 👇Smart Cities Are Dangerous👇 👇Smart Cities & Citizens Discontent👇 Speakers: Del Bigtree & Sean Kelly | Digital Social Hour Podcast Video: @fitconqueror1

Valerie Anne Smith

21,620 views • 1 year ago