I-Corps: Automated water quality monitoring system using satellite data for measurements of water resource characteristics

I-Corps：利用卫星数据测量水资源特征的自动化水质监测系统

• 批准号: 2205585
• 负责人: Leif Olmanson
• 金额: $ 5万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2205585&HistoricalAwards=false
• 关键词: Corps; Automated; water; quality; monitoring

The broader impact/commercial potential of this I-Corps project is the development of an online service to measure and report on lake water quality for government and business. Leveraging the ongoing investments for earth observation using satellites that provide free data, technology advancements like cloud computing and development of sophisticated algorithms, it is possible to automate the determination of water quality for every body of water in the world. Today, the methods and technology for monitoring lakes and field measurements are sparse with only on a small subset of lakes being monitored on a regular basis. Regulatory and policy entities could monitor water quality for every lake and reservoir on a regular basis with the capability of near real-time measurements to set policy and to better direct limited resources where they are needed most. The outcomes will be better management of a critical environmental resource for their constituents. Commercial entities such as vacation property businesses and real-estate brokerages will be able to better deliver value by reporting to consumers about the quality of lakes when renting, buying or selling properties. Lake water management companies would be able to continuously monitor the water quality to target treatment if needed. This I-Corps project is based on a software technology that processes remotely sensed satellite data into water quality products from all available Landsat 8 and Sentinel 2 imagery. Recent advances in satellite technology (improved spectral, spatial, radiometric and temporal resolution) and atmospheric correction, along with cloud and supercomputing capabilities have enabled the use of satellite data for automated regional scale measurements of water resource characteristics. Field-validated methods were developed and implemented in an automated water quality monitoring system on supercomputers. The system acquires satellite imagery, removes clouds, cloud shadows, haze, smoke, and land, and applies water quality models to deliver satellite-derived water quality products. Using these methods, a prototype database was created with monthly open water pixel level mosaics and lake level data for each clear image occurrence. The lake level (2017-2020) data includes 603,678 daily lake measurements of chlorophyll, clarity, and color (1,811,034 total) that were compiled into a database that was used to calculate water quality variables for different timeframes (e.g., monthly, summer (June-Sept)) and linked to a lake polygon layer that was used for geospatial analysis and included in a web map interface.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.

这个I-Corps项目的更广泛的影响/商业潜力是开发一种在线服务，为政府和企业测量和报告湖泊水质。利用对地球观测的持续投资，使用提供免费数据的卫星，云计算等技术进步和复杂算法的开发，可以自动确定世界上每一个水体的水质。今天，用于监测湖泊和实地测量的方法和技术很少，只有一小部分湖泊定期监测。监管和政策实体可以定期监测每个湖泊和水库的水质，并有能力进行近实时测量，以制定政策，并更好地将有限的资源用于最需要的地方。其结果将是更好地管理其成员的关键环境资源。 度假房地产企业和房地产经纪公司等商业实体将能够在租赁、购买或出售房产时向消费者报告湖泊的质量，从而更好地提供价值。湖水管理公司将能够持续监测水质，以便在需要时进行目标处理。这一I-Corps项目以一种软件技术为基础，该技术将遥感卫星数据处理成来自所有现有Landsat 8和Sentinel 2图像的水质产品。卫星技术（提高光谱、空间、辐射和时间分辨率）和大气校正方面的最新进展，加上云和超级计算能力，沿着使得能够利用卫星数据对水资源特性进行区域规模的自动测量。在超级计算机上的自动水质监测系统中开发并实施了经过现场验证的方法。该系统获取卫星图像，去除云、云阴影、雾霾、烟雾和土地，并应用水质模型提供卫星衍生的水质产品。使用这些方法，创建了一个原型数据库，每月公开水域像素级马赛克和湖泊水位数据，为每个清晰的图像发生。 湖泊水位（2017-2020年）数据包括603，678个叶绿素，透明度和颜色的每日湖泊测量值（总计1，811，034），这些测量值被编译成一个数据库，用于计算不同时间段的水质变量（例如，每月，夏季（6月至9月）），并链接到用于地理空间分析的湖泊多边形图层，并包含在Web地图界面中。该奖项反映了NSF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。