论文标题
案例研究：绘制Tegucigalpa潜在的非正式定居点领域，并通过机器学习来计划地面调查
Case study: Mapping potential informal settlements areas in Tegucigalpa with machine learning to plan ground survey
论文作者
论文摘要
在拉丁美洲平均每10年进行一次人口普查的数据收集，这使得难以监测这些定居点中生活的社区所需的增长和支持。进行现场调查需要后勤资源才能详尽地进行。开放数据，高分辨率卫星图像的可用性不断提高，并可以根据这些信息来源的分析以可扩展的方式来处理它们。该案例研究表明，Dymaxion Labs和非政府组织Techo使用机器学习技术来创建洪都拉斯Tegucigalpa的首次非正式定居点人口普查。
Data collection through censuses is conducted every 10 years on average in Latin America, making it difficult to monitor the growth and support needed by communities living in these settlements. Conducting a field survey requires logistical resources to be able to do it exhaustively. The increasing availability of open data, high-resolution satellite images, and free software to process them allow us to be able to do so in a scalable way based on the analysis of these sources of information. This case study shows the collaboration between Dymaxion Labs and the NGO Techo to employ machine learning techniques to create the first informal settlements census of Tegucigalpa, Honduras.
