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Guatemala

What does it take to achieve universal and equitable access to water and sanitation in Guatemala?

Marco Antonio Aguero's picture
See the full infographic on key findings of the Guatemala Water Supply, Sanitation, and hygiene (WASH) Poverty Diagnostic.

Water and sanitation data figures in Guatemala show a challenging reality. Nationally, 91 percent of the population has access to improved drinking water, an increase of 14 percent points since the establishment of the MDGs.
 
Despite the improvement in coverage in relative terms, in absolute terms there are still a significant number of Guatemalan households using water from precarious or unimproved sources such as unprotected wells, rivers, or lakes. In addition, water quality is a concern -- from the monitoring of 20% of the water systems in the country, 54% reported to be at high and imminent risk for human health.

Why are energy subsidy reforms so unpopular?

Guillermo Beylis's picture

It is well established in the economic literature that it’s the rich who benefit from the lion’s share of energy subsidies. Yet, it is often the poor and vulnerable who protest loudly against these reforms. Why does this happen? What are we missing?

Customs Union between Guatemala and Honduras, from 10 hours to 15 minutes!

Mayra Alfaro de Morán's picture

Trading across borders in Central America has been a severe problem for many years. In 2017, cargo trucks used to spend 10 hours to travel less than one kilometer across the borders between Guatemala and Honduras. Such delays at border crossings made trade throughout the region slow and expensive.
 

How to guarantee water access to reduce inequality in Central America

Seynabou Sakho's picture

Four years ago, Juan Angel Sandoval, a resident of Barrio Buenos Aires in the Honduran municipality of Siguatepeque, received water at home only three times a week. His was not an isolated reality. Most of his neighbors, were in the same situation. "It was annoying because the water was not enough," says Juan Angel.

How can electricity subsidies help combat poverty in Central America?

Liliana Sousa's picture


By Liliana D. Sousa


It might be surprising, but the majority of Central American households receive electricity subsidies, benefiting up to 8 out of 10 households in some cases. Without a doubt, this provides many poor and low-income families with access to affordable electricity.

Central America, optimizing the cost of energy through renewables

Mariano González Serrano's picture


Some months ago, during a visit to one of the Central American countries, while we were on a call with the head of the electricity dispatch center, we noticed by the tone of his voice, that he was becoming nervous. Shortly after, background voices could be heard on the line. They were experiencing a crisis and he quickly asked to continue our conversation at another time.

The secret sauce for making the New Urban Agenda a success

Luis Triveno's picture

Also available in: Español | 中文

Credit: Lois Goh/ World Bank


Modernity’s most common story spanning national, cultural and religious borders is about people moving from rural areas to the cities. By 2030, 80% of the world’s population will be living in urban areas, following the dream of better jobs, education, and health care.

Too often, however, that dream risks remaining an urban daydream, due to natural disasters such as hurricanes, earthquakes, and floods, as well as climate change. Those of us working to help these families find a better future must focus more on ways to support efforts to protect their lives – and their livelihoods.
 
In the 40 years since the launch of Habitat I, governments and municipalities throughout emerging and developing countries have been proving that their cities can be not only inclusive and secure, but also resilient and sustainable. However, unless they increase their speed and scale, they are unlikely to achieve the goals of the “New Urban Agenda” and its Regional Plans, launched at Habitat III in 2016.
 
From our perspective helping governments in Latin America and the Caribbean, and ahead of the World Urban Forum taking place in Kuala Lumpur, Malaysia in February, let us share three key ingredients necessary to achieve that goal:

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.

Rethinking saving practices in the digital era

Margaret Miller's picture



3-1-0 Three minutes to complete the online loan application, one second for approval and with zero human touch for SME loans. This is the marketing slogan used by Ant Financial, one of China’s largest online lenders with more than 400 million active users.

Digital finance is a cost-effective route to financial inclusion for many unbanked and underserved consumers in emerging markets. But digital finance is also still developing and maturing, with many open questions on the impact it will have. One of the most important of these is whether digital finance will ultimately help consumers to make better financial decisions over time.

October 31 is World Savings Day, a day which emphasizes the importance of savings to economic development, and provides a good occasion to look at how fintech may help solve the challenge of savings.


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