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What can satellite imagery tell us about secondary cities? (Part 2/2)

Sarah Elizabeth Antos's picture
In the previous blog, we discussed how remote sensing techniques could be used to map and inform policymaking in secondary cities, with a practical application in 10 Central American cities. In this post, we dive deeper into the caveats and considerations when replicating these data and methods in their cities.

Can we rely only on satellite? How accurate are these results?

It is standard practice in classification studies (particularly academic ones) to assess accuracy from behind a computer. Analysts traditionally pick a random selection of points and visually inspect the classified output with the raw imagery. However, these maps are meant to be left in the hands of local governments, and not published in academic journals.

So, it’s important to learn how well the resulting maps reflect the reality on the ground.

Having used the algorithm to classify land cover in 10 secondary cities in Central America, we were determined to learn if the buildings identified by the algorithm were in fact ‘industrial’ or ‘residential’. So the team packed their bags for San Isidro, Costa Rica and Santa Ana, El Salvador.

Upon arrival, each city was divided up into 100x100 meter blocks. Focusing primarily on the built-up environment, roughly 50 of those blocks were picked for validation. The image below shows the city of San Isidro with a 2km buffer circling around its central business district. The black boxes represent the validation sites the team visited.
 
Land Cover validation: A sample of 100m blocks that were picked to visit in San Isidro, Costa Rica. At each site, the semi-automated land cover classification map was compared to what the team observed on the ground using laptops and the Waypoint mobile app (available for Android and iOS).

What can satellite imagery tell us about secondary cities? (Part 1/2)

Sarah Elizabeth Antos's picture

The buzz around satellite imagery over the past few years has grown increasingly loud. Google Earth, drones, and microsatellites have grabbed headlines and slashed price tags. Urban planners are increasingly turning to remotely sensed data to better understand their city.

But just because we now have access to a wealth of high resolution images of a city does not mean we suddenly have insight into how that city functions.

The question remains: How can we efficiently transform big data into valuable products that help urban planners?

In an effort a few years ago to map slums, the World Bank adopted an algorithm to create land cover classification layers in large African cities using very high resolution imagery (50cm). Building on the results and lessons learned, the team saw an opportunity in applying these methods to secondary cities in Latin America & the Caribbean (LAC), where data availability challenges were deep and urbanization pressures large. Several Latin American countries including Argentina, Bolivia, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, and Panama were faced with questions about the internal structure of secondary cities and had no data on hand to answer such questions.

A limited budget and a tight timeline pushed the team to assess the possibility of using lower resolution images compared to those that had been used for large African cities. Hence, the team embarked in the project to better understand the spatial layout of secondary cities by purchasing 1.5 meter SPOT6/7 imagery and using a semi-automated classification approach to determine what types of land cover could be successfully detected.

Originally developed by Graesser et al 2012 this approach trains (open source) algorithm to leverage both the spectral and texture elements of an image to identify such things as industrial parks, tightly packed small rooftops, vegetation, bare soil etc.

What do the maps look like? The figure below shows the results of a classification in Chinandega, Nicaragua. On the left hand side is the raw imagery and the resulting land cover map (i.e. classified layer) on the right. The land highlighted by purple shows the commercial and industrial buildings, while neighborhoods composed of smaller, possibly lower quality houses are shown in red, and neighborhoods with slightly larger more organized houses have been colored yellow. Lastly, vegetation is shown as green; bare soil, beige; and roads, gray.

Want to explore our maps? Download our data here. Click here for an interactive land cover map of La Ceiba.

Investing in wastewater in Latin America can pay off

Diego Juan Rodriguez's picture
We are all too familiar with these figures: on average, only 50% of the population in Latin America is connected to sewerage and 30% of those households receive any treatment. These figures are not new. The region has been lagging in the levels of wastewater treatment for decades, which is unacceptable considering its high levels of urbanization and income levels.

The region is also not homogenous. There is a large disparity in the levels of treatment per country: we see countries like Chile, which treats 90% of its wastewater, and countries like Costa Rica, which treats approximately 4% of its wastewater.
The Deodoro wastewater treatment plant in Rio the Janeiro, Brazil.
Credit: http://www.waterwastewaterasia.com/

Global Infrastructure Forum maps out route towards delivering sustainable infrastructure

Amal-Lee Amin's picture



Last Saturday, tens of thousands of people gathered on the Washington D.C. mall for the March for Science alongside hundreds of sister marches around the world to coincide with Earth Day. Climate change and environmental protection were high on the agenda as the planet continues to warm and countries confront an increasing number of extreme weather events.

Meanwhile, down the road at the Inter-American Development Bank (IDB), the 2017 Global Infrastructure Forum was in full swing, discussing how to deliver inclusive and sustainable infrastructure to ensure we achieve the objectives of the Paris Agreement and the Sustainable Development Goals (SDGs).

Can behavioral change support water conservation? Examples from the US, Colombia and Costa Rica

Juan Jose Miranda's picture


This blog is part of the series "Small changes, big impacts: applying #behavioralscience into development".

While Latin America is rich in water, people’s ability to access safe, reliable water supply remains elusive in most countries. Worse, most countries and major cities in the region will face economic water scarcity in less than a decade. Strategies to manage water scarcity vary, from investing in water recycling facilities to changing consumer behavior.

The most common ways to change consumer behavior are to increase the price or conduct communication campaigns to encourage conservation. Neither solution, however, is guaranteed to succeed. In some cases, they even backfire. Increasing price, for example, can upset citizens who currently pay little for poor quality water. Likewise, if done poorly, communication campaigns can cause panic and increase consumption and water stockpiling, something Bogota faced in 1997 when a tunnel providing water to the city collapsed and caused water shortages.

The Central Matter: An artistic analysis of Central America's Nini subculture

Rafael de Hoyos's picture


On her daily walk down the muddy road that connects her home with school, Beatriz would sing a cumbia and dream of becoming a professional dancer. However, she would soon find out that her aspirations were short lived. At the age of 14, Beatriz got pregnant and never went back to school. In the six years following her pregnancy, she struggled with an unstable and low-paid job, cleaning rich houses in Guatemala City. By the age of 20, without minimum skills and a secure job, Beatriz had little control over her life and a murky picture of her future loomed. 

A Lifetime Approach To Preventing Violence In Latin America

Jorge Familiar's picture
A prevention program against crime and violence in Zacatecoluca, El Salvador, supports sporting activities for the children from this municipality. Photo: Victoria Ojea/World Bank

2016: A unique opportunity to get it right on forests and climate change

Ellysar Baroudy's picture
Moniz Phu Khao Khouay, Vientiane Province
Forest monitoring efforts in Phu Khao Khouay, Vientiane Province, Laos PDR. Photo credit: Hannah McDonald

If ever there was a year to make significant progress on forest conservation and climate change, it was 2016. Coming on the heels of the historic COP21 Paris Agreement, 2016 was a year to demonstrate the commitment the World Bank Group has to support countries as they take forward their nationally determined contributions to address our global climate change challenge. It’s gratifying to look back on 2016 and feel that we contributed to harnessing this momentum and sense of urgency; especially in showing how sustainable land use, including sustainable forest management, is critical to achieving the ambitious targets set out in the Paris Agreement.

The next phase of forest action

Julia Bucknall's picture
© Andrea Borgarello/World Bank
© Andrea Borgarello/World Bank


Last year, over 100 countries included actions related to land-use change and forests in their nationally determined contributions to fight climate change.

At the World Bank, we’re excited to be part of this next phase of forest action. In April 2016, we launched both a Forest Action Plan and Climate Change Action Plan which take a more holistic and ambitious approach to forests. We proposed to focus on investments in sustainable forest management and forest restoration to enhance economic opportunities for people living in and near forests, but also to help countries plan their investments in sectors such as agriculture, energy and transport in a more thoughtful, ‘forest-smart’ manner – to maximize the benefits of their forest assets.

Using fieldwork to ask better questions

Maira Reimao's picture
Evaluate the following statements according to whether they are “not at all true”, “hardly true”, “moderately true” or “exactly true”:
  • I can always manage to solve difficult problems if I try hard enough.
  • I am confident that I can deal efficiently with unexpected events.
  • I can solve most problems if I invest the necessary effort.
  • I can usually handle whatever comes my way.

If, after reading the statements above, you were a little confused and found your eyes going back and forth between them, trying to figure out how they are different, you are not alone. When we tested these and similar survey questions on women in rural Guatemala, we found that they not only confused our respondents but also perhaps deflated them.


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