SBIR Phase I: Geographic Information Systems (GIS)-Based Decision Support Management Application to Optimize Site-Specific Environmental Stewardship

SBIR 第一阶段：基于地理信息系统 (GIS) 的决策支持管理应用程序，以优化特定地点的环境管理

• 批准号: 0060575
• 负责人: Donna Rizzo
• 金额: $ 9.95万
• 依托单位: SUBTERRANEAN RESEARCH, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-01-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0060575&HistoricalAwards=false
• 关键词: SBIR; Phase; Geographic; Information; Systems

This Small Business Innovation Research (SBIR) Phase I project leads to increased productivity at environmental restoration sites through an innovative integrated application of geographic information systems (GIS), databases, simulation modeling, optimization, and artificial neural networks. The project begins with the understanding that environmental decisions involve many stakeholders, each with different priorities among several objectives. The research goals for this environmental information technology project are to: (1) identify and develop a hierarchy of neural networks that efficiently estimate uncertainty in data and predict the uncertainty as a result of monitoring and remediation decisions; (2) integrate such estimates and data into methods to optimize monitoring and remediation operations, which are coupled with large-scale simulation models used for environmental fate, transport, and risk analysis; (3) store sets of optimized results, which can include different stakeholders' objectives and constraints, in databases; and (4) present results to decision making end-users through a GIS interface. The commercial application of this research, presenting results to decision making end-users through a GIS focuses on subsurface (groundwater and soil) remediation at thousands of sites nationwide, and will be realized by licensing to firms for sales to remediation contractors. The research has near-term applications in climate, weather, air pollution, water, forest, and mineral resources, and emergency planning.

这项小型企业创新研究（SBIR）I阶段项目通过地理信息系统（GIS），数据库，模拟建模，优化和人工神经网络的创新综合应用来提高环境恢复站点的生产率。 该项目始于理解，环境决策涉及许多利益相关者，每个利益相关者在几个目标之间具有不同的优先事项。 该环境信息技术项目的研究目标是：（1）识别和开发神经网络的层次结构，这些层次结构有效估计数据的不确定性，并通过监测和补救决策而预测不确定性； （2）将这些估计和数据集成到优化监视和补救操作的方法中，这些方法与用于环境命运，运输和风险分析的大规模仿真模型相结合； （3）存储一组优化结果，其中可以在数据库中包含不同的利益相关者的目标和约束； （4）通过GIS界面向决策最终用户提供结果。 这项研究的商业应用，通过GIS向决策最终用户呈现结果，重点是全国数千个站点的地下（地下水和土壤）修复，并将通过向公司许可获得销售销售来实现补救承包商。 该研究在气候，天气，空气污染，水，森林和矿产资源以及紧急计划中近期应用。