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.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是，它将导致更多和更健康的城市树木在整个美国。它将影响气候，能源，空气和水的质量和宜居性。这将通过市政当局对城市森林进行更有效和高效的管理以及通过更多和更好地组织公民参与来实现。树木是一个社区的宝贵资产。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;改善个人和社区福祉。为了确保最大的效益和最低的成本，需要有效地管理行道树。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）第一阶段项目旨在使用尖端的计算机视觉和机器学习技术，从空中和街景图像中自动生成行道树库存。该清单包含每棵树的GPS位置，它的物种，树干直径和它的健康估计。每当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，它们基于深度卷积网络、3D几何和由专家和众包组合收集的大型注释数据集的学习能力。这一创新使得它能够保持一个始终最新的，准确的，完整的，美国范围内的行道树库存在当前成本的一小部分。