SBIR Phase I: Automated Census of Street Trees from Public Imagery

SBIR 第一阶段：根据公共图像对街道树木进行自动普查

• 批准号: 1648144
• 负责人: David Hall
• 金额: $ 22.5万
• 依托单位: AEye Labs, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1648144&HistoricalAwards=false
• 关键词: SBIR; Phase; Automated; Census; Street

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is that it will lead to more numerous and healthier city trees throughout the US. It will impact climate, energy, air and water quality and livability. This will be achieved through more effective and efficient management of the urban forest by municipalities, and through more and better organized citizen participation. Trees are a valuable asset for a community. Their benefits include: a reduction in energy use; improvement in air and water quality; increased carbon capture and storage; increased property values; and an improvement in individual and community well-being. To ensure maximum benefit and minimum cost, street trees need to be managed efficiently. In order to do this, municipalities need up-to-date inventories of trees. This Small Business Innovation Research (SBIR) Phase I project intends to automatically generate inventories of street trees from aerial and street-view imagery using cutting-edge computer vision and machine learning techniques. The inventory contains each tree's GPS location, its species, trunk diameter and an estimate of its health. The inventory is updated every time a new aerial or street-view image becomes available. Both tree detection and tree species classification are unprecedented applications based on combining the learning capabilities of deep convolutional networks, 3D geometry, and large annotated datasets that are collected by a combination of experts and crowdsourcing. This innovation makes it possible to maintain an always up-to-date, accurate, complete, US-wide street tree inventory at a fraction of the current cost.

该小企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业潜力在于，它将在美国各地种植更多、更健康的城市树木。它将影响气候、能源、空气和水质以及宜居性。这将通过各市政府对城市森林进行更有效和高效的管理以及通过更多更好的有组织的公民参与来实现。树木是社区的宝贵资产。它们的好处包括： 减少能源使用；改善空气和水质；增加碳捕获和储存；增加财产价值；以及个人和社区福祉的改善。为了确保最大效益和最小成本，需要有效管理行道树。为了做到这一点，市政当局需要最新的树木库存。这个小型企业创新研究 (SBIR) 第一阶段项目旨在利用尖端的计算机视觉和机器学习技术，从航空和街景图像中自动生成街道树木清单。该清单包含每棵树的 GPS 位置、树种、树干直径以及对其健康状况的估计。每次有新的航拍或街景图像可用时，库存都会更新。树木检测和树种分类都是前所未有的应用，它们结合了深度卷积网络、3D 几何的学习能力以及专家和众包收集的大型注释数据集。这项创新使我们能够以当前成本的一小部分来维护美国范围内始终最新、准确、完整的行道树库存。