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K. Thomas

Publications and source records attributed to K. Thomas.

2 recordsLinked to original sources

The Restoration Rapid Assessment Tool: An Access/Visual Basic application

Managers of parks and natural areas are increasingly faced with difficult decisions concerning restoration of disturbed lands. Financial and workforce resources often limit these restoration efforts, and rarely can a manager afford to address all concerns within the region of interest. With limited resources, managers and scientists have to decide which areas will be targeted for restoration and the restoration treatments to use in these areas. A broad range of approaches are used to make such decisions, from well-researched expert opinions (Cipollini et al. 2005) to gut feeling, with variable degrees of input from site visits, data collection, and data analysis used to support the decision. A standardized approach including an analytical assessment of site characteristics based on the best information available, with a written or electronic record of all the steps taken along the way, would make comparisons among a group of sites easier and lend credibility through use of common, documented criteria at all sites. In response to these concerns, we have developed the Restoration Rapid Assessment Tool (RRAT). RRAT is based on field observations of key indicators of site degradation, stressors influencing the site, value of the site with respect to larger management objectives, likelihood of achieving the management goals, and logistical constraints to restoration. The purpose of RRAT is not to make restoration decisions or prescribe methods, but rather to ensure that a basic set of pertinent issues are considered for each site and to facilitate comparisons among sites. Several concepts have been central to the development of RRAT. First, the management goal (also known as desired future condition) of any site under evaluation should be defined before the field evaluation begins. Second, the evaluation should be based upon readily observable indicators so as to avoid cumbersome field methods. Third, the ease with which site stressors can be ameliorated must be factored into the evaluation. Fourth, intrinsic site value must be assessed independently of current condition. Finally, logistical considerations must also be addressed. Our initial focus has been on riparian areas because they are among the most heavily impacted habitat types, and RRAT indicators reflect this focus.

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Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)

Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999-2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based "mapping zones". Over the course of 21/2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 land-cover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT = .60, n = 17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework. ?? 2006 Elsevier Inc. All rights reserved.

Remote Sensing of Environment↗