I-Corps: Using Remote Sensing and Geospatial Data for Informed Climate Adaptation, Mitigation, Resiliency, and Environmentally Friendly Solutions

I-Corps项目的更广泛影响/商业潜力是，通过利用基于遥感和其他空间数据的模型，利用环境和地理空间解决方案，发展地球物理和工程方面的进步。该项目可能影响城市可持续性、水质和水量监测以及基于自然和气候变化的风险分析等领域。如今，随着大量卫星遥感观测的可用性以及机器学习和云计算的进步，新的分析可以为各利益攸关方和决策者提供信息。卫星数据的优势在于其空间（从当地到全球）和时间覆盖范围（有些是几十年前的），这可以大大降低替代性地面数据收集和处理的成本。该项目将探索的技术和服务包括水质监测（包括有害藻华（HAB）检测）和利用卫星数据确定热浪期间行人的弹性解决方案等特定主题。I-Corps项目基于使用数据处理、机器学习和验证工作开发高空间和时间分辨率卫星数据产品。该项目确定了可用遥感和数据处理技术填补的现有空白，例如：用于统计开发高时空分辨率缩小的卫星数据的算法；确定冷走廊和开放街道路径的模型，作为城市热岛的弹性解决方案和响应，将减轻城市热岛对健康的不利影响；以及小水体和湖泊水质监测的精细分辨率卫星图像算法。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of advancements in geophysics and engineering using environmental and geospatial solutions by utilizing models based on remote sensing and other spatial data. This project may impact areas such as urban sustainability, water quality and quantity monitoring, and risk analyses based on natural and climate change. Nowadays, with significant satellite remote sensing observations availability and advances in machine learning and cloud computing, new analyses could inform various stakeholders and policy makers. Satellite data are advantageous because of their spatial (from local up to global scale) and temporal coverage (some from decades ago) which could significantly lower the costs of alternative, ground-based, data collection and processing. Particular topics such as water quality monitoring (including Harmful Algal Bloom (HAB) detection) and identifying a resilient solution for pedestrians during heatwaves using satellite data are among the technology and services to be explored in this project.This I-Corps project is based on the development of high spatial and temporal resolution satellite data products using data processing, machine learning, and validation efforts. The project defines the existing gaps that could be filled with remote sensing and data processing technologies such as: algorithms to statistically develop a high spatio-temporal resolution downscaled satellite data; models to identify cool corridors and open street paths as a resilient solution and response to urban heat islands (UHIs) which will mitigate the adverse health impacts of UHIs; and algorithms for small water-bodies and lakes water quality monitoring using fine resolution satellite imageries.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.