If you're using nightlights you need to know about two things: 1. What 𝙩𝙮𝙥𝙚 of economic activity it captures, and 2. 𝙎𝙥𝙖𝙩𝙞𝙖𝙡 𝙢𝙞𝙨𝙢𝙖𝙩𝙘𝙝𝙚𝙨 Here's the breakdown (in simple terms):

How far off are we from Autonomous GIS? A new paper provides the roadmap. Here's the key info you should know about:

By far, the data I'm asked most about is related to traffic and mobility. It's for good reason. This data is insanely hard to come by. So I've compiled a comprehensive list of datasets. These cover both paid and free options:

One of the best use cases for geospatial data is examining environmental factors. Here's a list of my favourite geospatial environmental datasets:

Climate datasets are the most commonly used geospatial data out there. But how accurate are they? A new study examines this (and the results are surprising):

You can get €50k (equity-free) to launch a geospatial business. I’ve done it twice. Here are the exact steps I took to obtain funding from @esa.int 's Business Incubation Centre:

Starter thread 🤖🧪 (AI for science) popularizing earth observation foundation models.

How to get a job as a data scientist at the World Bank? This is something I was asked about a lot. But my experience was (very) unorthodox. It involved burnout, CrossFit and Kyiv:

Geospatial Foundation Models are the geospatial space's answer to LLMs. But do they actually add value? Let's take a look:

To do good research, you need good tools. Here are the (free) tools I can't live without:

Granular and real-time estimates of carbon emissions are insanely tough to obtain. However, a new paper claims to have cracked it. Here's the breakdown:

Bill Gates loves estimating household wealth from satellites. So he'll love this new paper, which produces time-series wealth estimates at a granular level.

Official sub-national GDP is a nightmare to find. Most countries don't even publish it. However, some geospatial datasets provide these insights for every country in the world. Here's a list of geospatial GDP datasets, I wish I knew about 5 years ago:

Official estimates of methane emissions are inaccurate. How do we know? An analysis of satellite imagery conducted by NASA and Harvard. Here's the breakdown:

Some new surprising facts about nightlights have just been uncovered. These will impact how we use nightlights to measure economic growth. Here's the breakdown:

Much of the world runs on informal transport networks. However, it's difficult to assess how efficient these are. A new study examines 7,000 bus routes in 36 cities across 22 countries in order to find out. The results are pretty surprising:

If you're not using AI to help with research, you're missing out. An overview of the AI tools I use in my workflow:

Geospatial data science is all about having access to good data. Here are a list of my favourite free geospatial resources:

Meta is using Facebook and mobile phone data to produce super-granular household wealth estimates. Here’s what you need to know about the Relative Wealth Index:

In 1969 a husband and wife launched a geospatial company with $1,100. Today that bootstrapped company makes annual revenue over $1.5 billion. Here’s the story of ESRI:

Internet access unlocks economic and educational opportunities. Using (free) geospatial data, we can now identify which areas lack internet access at super granular levels. Here's the breakdown:

Inequality isn't just about income and wealth. It's also related to environmental factors. Here's how poorer people are more impacted by heat-related deaths:

There are many geospatial land-use maps available. However, they all tell us different things. So which one is the most accurate? Let's find out:

It's incredibly tough to come up with granular estimates of 𝙝𝙪𝙢𝙖𝙣-𝙢𝙖𝙙𝙚 CO2 emissions. However, a new approach attempts to do this in real-time using free data. Here's the breakdown:

Measuring agricultural GDP at a pixel level is notoriously challenging. It requires precise information on crop type and crop yield. @esa.int has launched a (free) dataset that provides this information. Here's what you need to know about it:

Most countries don't provide granular data on economic activity. Luckily, there are a range of geospatial datasets we can use as proxies. Here's a list of the best (free) resources for estimating sub-national economic activity:

You don't need to know programming or GIS to use geospatial data. Here are resources to get you started:

Geospatial foundation models are all the rage these days. But, are they all hype and no substance? Let's take a look:

Google is changing the weather forecasting game. Plus they've created a Python library to make their model available. Here's what you need to know about it:

Much of the world runs on informal transport networks. However, it's difficult to assess how efficient these are. To find out, a new study examines 7,000 bus routes in 36 cities across 22 countries. The results will surprise you:

The best way to accurately predict where deforestation will occur? By identifying 'Ghost Roads'. 200 people spent 7,000 hours identifying them. Here's what you need to know about it:

One of the biggest challenges in economic development? Assessing infrastructure quality. But did you know we can do this using satellite data? Here's how it works:

The way we use nightlights to measure economic activity is all wrong — according to a new study. This is due to a misunderstanding of 'elasticities'. Here's the breakdown (in simple terms):

The most important concept in the open-source geospatial world? Linus's Law. Here's what you need to know about it:

The most important geospatial concept? It's not vibe coding. It's Spatial Autocorrelation. It can make the difference between spurious and accurate results. Here’s what you need to know about it:

One of the most important models in geospatial data science? U-Nets. It's used for: • segmentation • super-resolution • diffusion models Here's the breakdown (in simple terms):

Identifying deposits of gold can be time-consuming and expensive. A new method demonstrates how we can use earth observation data to do this. Here's the breakdown:

Heatwaves disproportionately impact vulnerable communities. A new study demonstrates the extent of this. Here's the breakdown:

Meta is known for Facebook, WhatsApp and Instagram. But did you know they provide a range of free geospatial datasets for researchers? These include granular measures of household wealth, population, and network access. Here's what you need to know about it:

Internet access unlocks economic and educational opportunities. Using (free) geospatial data, we can now identify which areas lack internet access at super granular levels. Here's the breakdown:

We can now easily access over 18,000 geospatial datasets instantly, for free. Here's everything you need to know about the Geospatial Data Catalog:

It's possible to quantify damages in conflict zones using satellite images. How? It's to do with coherence. Here's the breakdown in simple terms:

Another good #climate and #geodata #mapping thread from Yohan

Inequality isn't just about income and wealth. It's also related to transport and accessibility. Here's how poorer people are more impacted by inaccessibility to public services:

Researchers have uncovered an unexpected driver of global warming in 2023. They found the answers in the clouds (pun intended). Here's the breakdown:

Did you know we can access 𝙙𝙖𝙞𝙡𝙮 geospatial climate projections up until 1 Jan 2100? It covers projections for: • temperatures • precipitation • wind Plus it's completely free. Here's what you need to know about it:

Much of the world runs on informal transport networks. However, it's difficult to assess how efficient these are. A new study examines 7,000 bus routes in 36 cities across 22 countries in order to find out. The results are pretty surprising:

Do give Yohan here a follow - he provides excellent #earrhobservation #EO #remotesensing and #geodata tips and insights. Has a rather large following in the birdsite and is finally joining us here in bluesky

Creating geospatial population estimates can be a nightmare. It's particularly tough when you don't have good-quality census data. A new method attempts to address this by estimating population from Sentinel images:

Some new surprising facts about nightlights have just been uncovered. These will impact how we use nightlights to measure economic growth. Here's the breakdown: