Welcome to our eleventh edition on everything related to society and impact. We explore a massive dataset mapping the world’s agricultural fields, how climate journalists use satellite imagery to report the news, an interactive tool revealing the depopulation of European villages, and a novel index quantifying urban car dependency.
In this newsletter, we cover:
Interesting Dataset: Fields of The World
Interesting Read: Webinar: Satellite Imagery for Climate News
Interesting Tool: European Village Population Map
Interesting Variable: Car Dependency Index
Interesting Dataset: Fields of The World
Fields of The World (FTW) is an open ecosystem designed to detect and map agricultural field boundaries on a global scale. Because most countries lack complete maps of their agricultural lands, FTW uses open Sentinel-2 satellite imagery combined with machine learning to identify these boundaries, which is crucial for monitoring land use, assessing food security, and analyzing crops worldwide. The initiative’s recent global release covers the years 2024 and 2025 at a 10-meter resolution. The results are surprisingly good.
Scope: 3.17 billion field polygons across 241 countries and territories.
Benchmark data: over 1.6 million labeled parcels used to train and evaluate models.
Access: a browser-based Explorer App lets users pan the world map, download polygons for specific regions, or run inference directly in the browser, with no coding required.
Beyond the raw data, the FTW ecosystem provides pre-trained baseline machine learning models and inference tools, making it a comprehensive resource for researchers monitoring global agriculture.
The screenshot above shows the Explorer App’s Global Predictions mode over Carinthia, Austria. Users can zoom to any region, adjust the prediction confidence threshold, and toggle between growing seasons to inspect the model’s output field by field.
Interesting Read: Webinar: Satellite Imagery for Climate News
In a recent Copernicus Data Space Ecosystem webinar, Washington Post graphics columnist Daniel Wolfe discussed the role of satellite imagery in climate journalism. He explained that satellite data typically serves two functions in newsrooms: supporting existing reporting by providing contextual maps or recent imagery of events like earthquakes, and acting as the news itself by revealing or confirming on-the-ground situations, such as conflicts or natural disasters.
Wolfe highlighted the utility of the Sentinel satellite fleets and the Copernicus Browser, the same false-color tool we explored in Newsletter #10, in his reporting process:
Sentinel-2: frequently used for timely true-color imagery and time-lapse visuals to track environmental change.
Sentinel-1: its synthetic aperture radar (SAR) penetrates cloud cover, making it invaluable for assessing flooding and infrastructure damage during hurricanes.
By translating complex scientific information into compelling visual narratives, including false-color manipulation that makes invisible data like wildfire burn scars visible to readers, journalists can make the impacts of climate change accessible to a wider audience without needing advanced third-party software. Check out this interesting webinar to get more details.
Interesting Tool: European Village Population Map
An interactive mapping tool developed by CORRECTIV.Europe visualizes a stark demographic reality: while Europe’s overall population has grown over the past decades, half of all its cities and municipalities have fewer inhabitants today than they did 60 years ago. The tool displays population growth in green and shrinkage in red for approximately 100,000 municipalities across the EU and neighboring countries between 1961 and 2024.
Scope: around 100,000 municipalities across the EU, the UK, and neighboring countries.
Timeline: population trends recalculated for every decade from 1961 to 2024.
Trends revealed: severe rural exodus in “empty Spain,” and 88 percent of municipalities shrinking in eastern Germany since 1991.
On the map above, green marks municipalities that have grown since 1961, while pink marks those that have shrunk. Note the deep pink blanketing much of Spain, Italy, and eastern Germany, against the green pockets around booming capitals like Dublin and Warsaw.
To build the tool, researchers at the EU’s Joint Research Centre used a novel dasymetric mapping methodology to recalculate 63 years of historical population data according to current 2021 municipal boundaries, preventing distortions from past border changes. The data reveals a growing divide between booming urban centers, like Madrid’s suburbs or the Lithuanian capital of Vilnius, and declining rural areas. Demography experts warn that this localized shrinking severely threatens quality of life in rural regions, making it increasingly difficult and expensive to maintain essential infrastructure like schools, transport, and local businesses.
Interesting Variable: Car Dependency Index
A new paper introduces the Car Dependency Index (CDI), a novel territorial metric designed to quantify the accessibility gap between private vehicles and public transport across 18 cities in Europe and North America. The CDI measures the difference in the number of essential services and opportunities a resident can reach via car versus public transit within a reasonable time. A positive CDI score indicates that a car provides greater access to opportunities, whereas a negative score highlights areas where public transport is more efficient.
Pattern: central urban cores often show negative CDI values, while car dependency typically dominates in peripheral city districts.
Predictive power: the CDI strongly predicts actual commuting behavior and car ownership, even when controlling for residents’ income.
Rome case study: a simulated metro expansion significantly reduces car dependency for residents living nearby, but the city-wide reduction is relatively modest.
This finding underscores that tackling urban car dependency and fostering sustainable mobility requires systemic, network-level public transit expansions rather than isolated, localized interventions.
Source: https://arxiv.org/pdf/2604.01019
The maps above compare CDI across 11 of the study’s cities: blue areas indicate public transport is more efficient than a car, red areas the opposite. Paris and Zurich stand out as the only cities with net-negative CDI, while car dependency blankets nearly all of Rome, New York, and Vienna outside their historic cores.