Working Group: Resource Management
Led by Durwood Zaelke (ELIS project member and president of CIEL) and Steve Jamar (consultant to ELIS and Professor of Law at Howard University), the participants of this working group focused on the resource manager's ideal request to the producers of the data. The participants first identified many problems with the use of remote sensing technology in resource management. Participants were concerned that research conducted with satellite data is driven by research funding and not by the need for practical applications. This is problematic because research science was not developed to go backwards from the data, but to establish a hypothesis from an observed event and then proceed to deconstruct and reevaluate the hypothesis as the research proceeds resulting in a reasonable conclusion. Furthermore, the questions being presented by the resource managers are too general to be used as a point of scientific research. Another problematic issue is that of indicators. To efficiently use remote sensing in resource management, it is necessary to define an indicator of the problem to be researched. Identifying indicators that have an actual correlation to a specific event and that can be measured with remote sensing tools is a complex process. It is possible, however, as Dr. Ramsey demonstrated with the study of correlating leaf optical properties to marsh dieback, although with an automated system, the margin of error may be too great to use for applications. Connected to the problem of indicators is that if operable uses. Remote sensing efforts are directed at research, not at operational uses. The system needs to shift towards including research that can be directed at practical applications.
After voicing some of the obstacles to using remote sensing for natural resource management, needs were identified and answers proposed. According to Bill Campbell, NASA is beginning to focus its satellite programs on addressing user needs, rather than generalized data collection. Resource managers should take this opportunity to determine what data would be useful and discuss their data needs with the technology developers. Scientists must define indicators to help automate the system to reduce production costs. Relative standards of accuracy, contingent on the actual use of the data, should be designed.
Better education systems should be installed, and incentives should be implemented to motivate users to become familiar with the data. Considerable technical support is necessary to connect remote sensing technologies with users for data interpretation, as well as locating the best data sources. Guidance must be established to help users understand the limitations of the data. It is impossible for decision makers to use the current system without extensive training. Education is a twofold process: first, the data collectors should present the data in a way that laypeople understand it and second, laypeople should take the initiative to study remote sensing capabilities and data limitations, as well as to understand what are realistic expectations for the data.
The ideal answer: A consumer guide and catalog server should be set up to present information such as the data needed for specific applications, where to obtain the data, sufficient metadata to explain the data’s history, and an auction place for existing value-added data. A website that walks users through the steps from matching an application to data availability through the retrieval and processing of data requests should be established. Background work varying from cost-benefit analyses of the use of remote sensing data to determining the ultimate needs of the actual users must be completed.