From Canada to Kenya, nearly every country struggles to provide housing for all its residents. It’s a goal that has become a moving target: Migration – both rural-to-urban and cross-border – is placing mounting pressure on cities to house their newcomers.
Three million people move to urban areas every week, and
As markets change fast, governments must be ever vigilant that policies don’t become obsolescent or even harmful because their details have become out of date. Even well-designed housing programs require adjustments.
disaster risk management
Another year has passed, and we are only 11 years away from the goalpost of the 2030 Agenda for Sustainable Development (Agenda 2030).
In the past few years, knowledge sharing has moved to the center of global development as a third pillar complementing financial and technical assistance. Agenda 2030 calls for enhancing “knowledge sharing on mutually agreed terms,” while the Addis Ababa Action Agenda on Financing for Development encourages knowledge sharing in sectors contributing to the achievement of the SDGs.
For cities, this means that
This is a highly fertile, verdant place… You're at the foot of a volcano.
Across the globe, more than 20 million children from conflict-affected countries are out of school.
Take Syrian refugees in Turkey, the country that hosts more individuals fleeing from armed conflict than any other in the world.
Machine learning algorithms are excellent at answering “yes” or “no” questions. For example, they can scan huge datasets and correctly tell us: Does this credit card transaction look fraudulent? Is there a cat in this photo?
But it’s not only the simple questions – they can also tackle nuanced and complex questions.
Today, machine learning algorithms can detect over 100 types of cancerous tumors more reliably than a trained human eye. Given this impressive accuracy, we started to wonder: what could machine learning tell us about where people live? In cities that are expanding at breathtaking rates and are at risk from natural disasters, could it warn us that a family’s wall might collapse during an earthquake or rooftop blow away during a hurricane?
There is a unique space where you can encounter everyone from developers of self-driving cars in Silicon Valley to city planners in Niamey to humanitarian workers in Kathmandu Valley: the global OpenStreetMap (OSM) community. It comprises a geographically and experientially diverse network of people who contribute to OSM, a free and editable map of the world that is often called the “Wikipedia of maps.”
What is perhaps most special about this community is its level playing field. Anyone passionate about collaborative mapping can have a voice from anywhere in the world. In the past few years, there has been a meteoric rise of locally organized mapping communities in developing countries working to improve the map in service of sustainable development activities.
The next opportunity to see the OSM community in action will be the November 14th mapathon hosted by the Global Facility for Disaster Reduction and Recovery (GFDRR)’s Open Data for Resilience Initiative (OpenDRI). Mapathons bring together volunteers to improve the maps of some of the world’s most vulnerable areas, not only easing the way for emergency responders when disaster strikes, but also helping cities and communities plan and build more resiliently for the future.
They play such a pivotal role in addressing global challenges and improving citizen’s lives that
Post-disaster assessments changed my life by starting my career in disaster risk management. Three months after arriving in Indonesia as the World Bank’s environment coordinator, the Indian Ocean tsunami and related earthquakes struck Aceh and Nias at the end of 2004. I was asked to pull together the economic evaluation of the disaster’s environmental impact as part of what was then known as a damage-and-loss assessment. Subsequently, the World Bank, United Nations and European Union agreed on a joint approach to crisis response in 2008, including a common methodology for post-disaster needs assessment (PDNA).
Now that we have a decade of experience with this approach, what have we learned and how can we do a better job in the future?
Droughts, floods, hurricanes, and other disasters displaced over 24 million people in 2016. This is crucial, as land and homes are usually the main assets that people have.
Land and geospatial information tells the what, who, where, how much, and other key attributes of a property. Without this information, it is almost impossible for cities and communities to develop proper disaster response or preparedness plans.
– by providing accessible and instant data on disaster impact, the value of losses, the beneficiaries, as well as the levels of appropriate compensation and required investment to restore activities.
For a family, having a place to call home is everything. Housing tends to be a family’s most important asset – often, in fact, their only asset, especially for the poor. But more than a home, housing is also the workplace, collateral for loans and an important vehicle for job creation. In the U.S., housing contributes more than 15% of the GDP.
The dream of housing, however, can quickly turn into a nightmare – for both families and for governments. Disasters can erase decades of progress in reform and poverty reduction in a matter of seconds, hurting the poor and vulnerable the most. A review of the World Bank’s Post-Disaster Needs Assessments (PDNAs) since 2000 shows that housing comprises 40%-90% of damages to private property.