I-Corps: Geodetic Satellite-Based Observation System

I-Corps项目更广泛的影响/商业潜力是开发一个基于大地测量卫星的重力观测系统原型和相关的基于云的计算工具，用于快速远程监测全球流域范围内的洪水、干旱和淡水资源的供应情况。预计该项目将能够对淡水运输进行高效、动态、大数据量化，以实现广泛的潜在商业应用。这一工具的潜在商业化和相关数据产品的及时提供可能提供关键信息，并对商业应用产生影响，包括精准农业、灾害规划和管理以及一般水资源管理。i-Corps项目将探索基于云的卫星临时重力观测处理和可视化工具的商业化。这是为快速监测而设计的，最多每天对自然或人为特征进行时间采样。该项目建立在以前的发展基础上，提高了蓄水变化的时间分辨率，并有可能提高其空间分辨率。目前可用于农业和灾害/水资源管理服务的商业工具主要基于被动遥感成像，这种成像通常受到云层的限制，或者获取及时数据集的费用高得令人望而却步。随着地球卫星重力任务数据集持续到下一个十年，支持这项工作的数据可以免费获得，并可能近乎实时地更新。

The broader impact/commercial potential of the I-Corps project is the development of a prototype geodetic satellite-based gravity observational system and the associated cloud-based computing tools for the rapid remote monitoring of floods, droughts, and freshwater resources availability globally at basin scales. The project is expected to enable efficient, dynamic, big data quantifications of freshwater transport for a wide range of potential commercial applications. The potential commercialization of this tool and the timely availability of the associate data products could provide critical information and impact on commercial applications including precision agriculture, disaster planning and management, as well as general water resources management.This I-Corps project will explore the commercialization of a cloud-based satellite temporal gravity observation processing and visualization tool. This is designed for rapid monitoring with up to daily temporal sampling for natural or anthropogenic features. The project builds from prior developments improving the temporal resolution of water storage change and potentially improving its spatial resolution. Current commercially available tools for agricultural and disaster/water resources management services are primarily based on passive remote sensing imaging which are typically limited by cloud cover or are prohibitively expensive for acquiring timely data sets. As Earth satellite gravity mission data sets continue into the next decade, the data underpinning this work is freely available and potentially updated in near real time.