Rob Marty

Data Scientist @ World Bank

[Arianna Legovini @alegovini]

Just released! A crowdsourced dataset that maps 30,000 road crashes in Nairobi. Download here https://t.co/P32e4yk3vy. This is work with @smilusheva3 @lupe_bedoya @robamarty to prioritize road safety investments and save people's lives on the roads https://t.co/FnMoiThQZ7

[Yohan @yohaniddawela]

Facebook's marketing API is primarily used by advertisers.

But did you know it can also be used to derive geospatial poverty estimates?

A new paper from @worldbankdata has developed the methodology.

Here's the breakdown:

[Rob Marty @robamarty]

@assad_shoaib @worldbankdata @assad_shoaib Ah yep getting those are a bit tricky! Do these instructions help? If unclear I can update. As of now the version needs to be specified - I think the latest is "v19.0" https://t.co/qSuav28RMx

[Estación R @estacion_erre]

[PAQUETE 📦] - ¿Trabajas con info de tráfico?

Con {googletraffic} vas poder armar data georreferenciada a partir de la información de tráfico de Google Maps en tiempo real.

🌐 https://t.co/acI7a5ZVnV
✍🏼 @robamarty @WorldBank

#RStats #RStatsES #Rtips #DataScience

[World Bank Data @worldbankdata]

Interested in tracking urbanization trends, conflict areas or economic activity?

Discover the potential of @NASA's #BlackMarble #data with our latest blog post, and explore how #R and #Python packages simplify data access and analysis.

🛰️ https://t.co/RO9rCGyYMy

[Arianna Legovini @alegovini]

Our spring recruitment drive just went online! Join the fantastic DIME team. We put research and creativity to the service of people, prosperity and the planet. https://t.co/1IOjLZcaTg

[World Bank Data @worldbankdata]

Interested in tracking urbanization trends, conflict areas or economic activity?

Discover the potential of @NASA's #BlackMarble #data with our latest blog post, and explore how #R and #Python packages simplify data access and analysis.

🛰️ https://t.co/xHfuhMi76l

[World Bank Data @worldbankdata]

Harness the power of @NASA's Black Marble data for groundbreaking analysis: From economic activity to disaster recovery, our research presents user-friendly #R & #Python packages to unlock nighttime lights data's potential.

Learn more in our blog post: https://t.co/1rKX6eAgxF

[Yohan @yohaniddawela]

NASA's Black Marble is the most accurate source of nightlights data.

However, it's difficult to use.

Here are the exact steps you need to take to work with Black Marble data:

[Rob Marty @robamarty]

@yohaniddawela @NASAEarth @DrMiguelRoman This is all extremely informative! Something potentially of interest are newly released Python/R packages for working with Black Marble (developed with @g4brielvs).

https://t.co/kj3O0FnSQK

https://t.co/WYqEEo0ZDz

[Yohan @yohaniddawela]

Economics is slow to adopt breakthroughs in earth observation.

There’s super high-res satellite data that sees through clouds, works at night, and in any weather conditions.

Here’s how SAR data will revolutionise spatial economics:

[Yohan @yohaniddawela]

Night time satellite data is one of the most promising proxies for economic growth.

• How does it work?
• How accurate is it?
• What are its issues?

Having worked on this extensively during my PhD and after, here’s everything you need to know:

[Yohan @yohaniddawela]

Soon we won't be able to use nightlights as a proxy for economic growth.

Why?

It's due to limitations of its spectral bands.

Here's the breakdown in simple terms:

[Rob Marty @robamarty]

If you prefer interactive figures to reading, see our dashboard!

https://t.co/oU3rnrgBhH 4/

[Rob Marty @robamarty]

After containment policies were implemented, mental health & unemployment searches rose while relationship/family planning searches fell. Higher-income countries saw a larger increase in unemployment related searches & a larger reduction relationship/family planning searches. 3/

[Rob Marty @robamarty]

Searches for #COVID19-specific symptoms (eg, “loss of smell”, “loss of taste”) initially correlated strongly with reported cases. As the virus evolved, this association diminished, with searches for general terms like "COVID symptoms" maintaining a strong correlation. 2/

[Rob Marty @robamarty]

Using data from 221 countries & territories, our @SciReports paper shows that @GoogleTrends can anticipate changes in reported #COVID19 cases and can be used to gauge socioeconomic impacts of #lockdowns.

https://t.co/U1RXc4uiEh

@ManuelRamosMaq @nausheen__khan @ArndtReichert 1/

[Rob Marty @robamarty]

@RitaFeinstein Of the 362 which was your favorite

[David Evans @DaveEvansPhD]

Curfews in Nairobi during COVID-19 led "to large reductions in crashes during the curfew hours when cars are off the road, but...reductions can be fully offset by an increase in crashes...when people rush to get home before the curfew starts." https://t.co/sUDZvwzjBc

[Arianna Legovini @alegovini]

Curfews restrict freedom of movement & are at best controversial. In Kenya, we looked at whether they helped road safety. They didn't. Curfews reduced crashes during restricted hours but equally increased accidents before the curfew as drivers rushed home. https://t.co/twuSz9Ha9F