SBIR Phase I: High Resolution, Synthetic Satellite Imagery of the Earth

SBIR 第一阶段：地球的高分辨率合成卫星图像

• 批准号: 1519919
• 负责人: Stephanie Hulina
• 金额: $ 14.99万
• 依托单位: Geospatial Data Analysis Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1519919&HistoricalAwards=false
• 关键词: SBIR; Phase; Resolution; Synthetic; Satellite

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to address a strong commercial and scientific need for historical and most current satellite data for visualization and analytical purposes with regional-to-global coverage, frequent revisit, and high spatial detail at an affordable price. It will allow companies to improve their value proposition, competitive edge, and to differentiate their services. The technology will be valuable in operational settings at the large providers of commercial satellite imagery, to individual users, and in a host of commercial applications such as insurance, agriculture, and emergency. The development of the proposed technology will contribute to the advancement of scientific knowledge especially in the geospatial arena and to market spillovers. By dramatically simplifying access to accurate historical and most current imagery for any time and place, this project will provide companies, researchers, educators, students, and regular citizens with a valuable tool for visualizing and exploring our changing planet and will contribute to increasing public engagement with science and technology. Further, the analytical capabilities offered by the imagery have great potential in scientific applications thus contributing to partnerships between academia and industry and improving datasets for research and education. This Small Business Innovation Research (SBIR) Phase I project will demonstrate the technical feasibility of operationally synthesizing accurate global, high spatial / high temporal satellite imagery of the Earth. The complexity of accessing, processing, and analyzing various sources of satellite imagery creates a significant barrier to its use. Synthesis of regionally and globally continuous high spatial and high temporal resolution imagery is a challenge as in addition to inherent differences in spatial and temporal resolutions of the source data, the new models need to account for enormous data volumes and sparse coverage of high spatial resolution imagery. Existing techniques to handle these challenges have severe limitations which curtail their use outside of the research arena. The proposed technology will overcome these limitations by implementing advanced data fusion algorithms to combine various sources of satellite data to synthesize imagery for any given date and location while preserving the best spatial and temporal attributes of the data sources. The algorithms will be robust, easily automated, scalable, deliver accurate data, are usable in operational settings, and will provide spatially consistent and temporally relevant imagery which will empower businesses with regional and global outreach to make better decisions with better data.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力将是解决对历史和最新卫星数据的强烈商业和科学需求，用于可视化和分析目的，具有区域到全球的覆盖范围，频繁重访，以及以负担得起的价格提供高空间细节。它将使公司能够提高他们的价值主张，竞争优势，并使他们的服务与众不同。该技术将在商业卫星图像的大型提供商的操作环境中对个人用户以及保险，农业和紧急情况等许多商业应用具有价值。拟议技术的发展将有助于科学知识的进步，特别是在地理空间竞技场和市场溢出效应。通过极大地简化对任何时间和地点的准确历史和最新图像的访问，该项目将为公司，研究人员，教育工作者，学生和普通公民提供可视化和探索我们不断变化的地球的宝贵工具，并将有助于增加公众对科学和技术的参与。此外，图像提供的分析能力在科学应用方面具有巨大潜力，从而有助于学术界和工业界之间的伙伴关系，并改进用于研究和教育的数据集。该小企业创新研究（SBIR）第一阶段项目将证明在业务上合成准确的全球高空间/高时间地球卫星图像的技术可行性。访问、处理和分析各种来源的卫星图像的复杂性对其使用造成了重大障碍。综合区域和全球连续的高空间和高时间分辨率图像是一项挑战，因为除了源数据在空间和时间分辨率方面的固有差异外，新模型还需要考虑到巨大的数据量和高空间分辨率图像的稀疏覆盖。处理这些挑战的现有技术具有严重的局限性，这限制了它们在研究竞技场之外的使用。所提出的技术将克服这些限制，采用先进的数据融合算法，将各种来源的卫星数据联合收割机结合起来，合成任何给定日期和地点的图像，同时保留数据源的最佳空间和时间属性。这些算法将是强大的，易于自动化，可扩展的，提供准确的数据，可用于操作环境，并将提供空间一致和时间相关的图像，这将使企业能够与区域和全球联系，以更好的数据做出更好的决策。