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One of the problems of the cities of Latin America and the Caribbean (LAC) is the expansion of informal settlements. At least 25% of its population lives in one of them. Why does this phenomenon happen? Can it be reversed? Can technology help us reduce urban informality ? In this blog we answer these questions and, in addition, we will show you how a project supported by the IDB has made it possible for artificial intelligence to help identify and prioritize interventions in informal settlements in Colombia . Your municipality could be next! Read on to find out how. What are informal settlements, and why are they created? Informal settlements exist in practically all countries. Those in our region are no exception. These settlements (known depending on the country as informal neighborhoods, villas, camps, favelas,) are created as a result of the unmet demand for housing in an uncontrolled manner, generally through self-construction.
Every year, thousands of households are created without access to formal housing, resulting in a continuous growth of the housing deficit. This gap between the demand and the formal supply of housing results in the informal market absorbing the demand of households that, due to their low purchasing WhatsApp Number List power, are excluded. This results in the formation of informal settlements: territories that develop in poor physical and social conditions, deepening the conditions of vulnerability of their residents, and increasing the inequality they suffer. Can satellite imagery identify informal settlements? The answer is yes. Images captured by satellites have been used for decades to collect information about the Earth's surface. Its analysis for urban planning allows producing very precise maps, with frequent updating of the growth of cities. This allows us not only to understand the speed at which a municipality grows, but also the characteristics of its construction.
For this reason, satellites can inform where and how informal settlements grow. However, this requires highly specialized work teams and a powerful processing infrastructure that often must be configured and tested from scratch for each project. These difficulties represent a barrier to the adoption of these techniques by local government teams. This is a paradox, since they are one of the institutions that could benefit the most from having highly detailed spatial information. How to analyze large amounts of satellite information?: artificial intelligence to the rescue The advance of artificial intelligence - specifically, so-called machine learning - represents a huge step forward, facilitating the processing of large amounts of information. It is possible to “train” digital systems to learn to identify objects of interest in satellite images, using as input the material previously produced by human experts. How can an algorithm recognize an informal settlement through satellite images? The first step is to take a satellite image of a neighborhood where a municipal team has demarcated informal areas.
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發表於 2024-3-12 12:55:33