This is a highly fertile, verdant place… You're at the foot of a volcano.
This is a highly fertile, verdant place… You're at the foot of a volcano.
The future is uncertain. It’s hard to know exactly how our climate will change. That means there is also deep uncertainty around its impacts on flooding, the most prevalent disaster worldwide. How much will sea level rise? How extreme will rainfall be?
What we do know is that the best way to cope with uncertainty is flexibility.
While it may be difficult to predict impacts, we can – and must – take action. Growing uncertainty means preparation is even more urgent.
By 2050, two-thirds of all people will live in cities. Each year, 72.8 million more people live in urban areas. That’s the equivalent of a new San Diego appearing every week.
But By 2030, climate change alone could force up to 77 million urban residents into poverty.
Achieving resilience is the goal – and the good news is that cities aren’t alone on the team.
Much of this has to do with the lack of adequate infrastructure that can defend against the impacts of floods, sea level rise, landslides or earthquakes. . But even when cities know what it takes to become more resilient, most often they do not have access to the necessary funding to realize this vision.
It is estimated that worldwide, investments of more than $4 trillion per year in urban infrastructure will be needed merely to keep pace with expected economic growth, and an additional $1 trillion will be needed to make this urban infrastructure climate resilient. It is clear that the public sector alone, including development finance institutions like the World Bank, will not be able to generate these amounts—not by a long stretch.
The recent series of devastating hurricanes in the Caribbean has reminded the world, once again, that natural disasters are not equal-opportunity destroyers. The economically marginalized and those lacking secure land and property rights are often disproportionately affected for at least three reasons:
- First, without secure property rights, they typically lack the long-term incentive and access to credit to build safe, resilient houses.
- Second, they can be reluctant to flee their homes to safe areas, fearing they won’t be allowed to return.
- Finally, they are less likely to be the recipients of government risk mitigation or recovery efforts. Government recovery efforts – no matter how well intentioned – rarely reach those most in need. After the floods and landslides in Nepal in 2011, for example, only 6% of the poorest received government support – compared to almost 90% of the well off.
The increasing frequency of natural disasters with tragic human consequences should also serve as reminders that resources spent on disaster risk reduction (DRR) are much more effective at saving lives and property loss. Yes, despite substantial evidence that reducing disaster risk is more cost-effective than responding to disasters, expenditures for disaster response and reconstruction exceed spending on disaster risk reduction and preparedness at a rate of about 20 to 1.
To overcome that spending gap will require innovative thinking on a time-tested idea. Governments, the World Bank, and other donors are doing the right thing when trying to devote more resources to disaster risk reduction – and to make land and property rights reforms part of a multi-faceted DRR strategy. In doing so, they would do even better by recognizing that those rights exist in three dimensions, encompassing not just the ground beneath our feet but to the space above (and below) it.
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).|
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:
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.
From East Asia, South Asia, and Africa to Latin America, disaster events such as hurricanes, floods, and earthquakes are on the rise, destroying homes and claiming lives.
Climate change is making it worse. , causing greater losses.
We may not know exactly what the world will look like in two decades, but we know this: it is going to be a world of cities.
Each year, urban areas are growing by an average of more than 75 million people – more than the population of the world’s 85 smallest countries combined.
For the world’s economy, this is great news, since cities produce 80 percent of global GDP, despite currently being home to only 55 percent of the population. But it is a problem for urban infrastructure, which can’t keep up with such fast-paced growth. As a result, – from flooding and landslides that can decimate informal housing settlements, to earthquakes that can devastate power grids and water systems.
These risks could be disastrous for the urban poor, 881 million of whom currently live in slums (up 28 percent since 2000). And climate change – which is increasing the intensity and frequency of natural disasters – will only exacerbate the problem. For this reason, multilateral and government institutions now see resilience and climate adaptation as integral pillars of development.
The Swiss State Secretariat for Economic Affairs (SECO), for example, considers low-emission and climate-resilient economies to be key to global competitiveness. A recent report by the World Bank and the Global Facility for Disaster Reduction and Recovery (GFDRR) found that climate change may force up to 77 million urban residents into poverty by 2030 – unless we take action to improve the resilience of cities around the world.
The good news is that the world has a brief window of opportunity to make cities more resilient to climate change, natural disasters, and other stresses, as almost 60% of the urban area that will be built by 2030 is yet to be developed.