Thursday, November 16, 2006 - 10:00 AM

Assessment and Implication for Improvement of RTLA/LCTA Plot Inventory Methods I: Optimal Spatial and Temporal Resolutions.

Guangxing Wang, Dept of Natural Resources and Environmental Science, Univ of Illinois, 1102 S Goodwin, Urbana, IL 61801, George Z. Gertner, Dept of Natural Resources and Environmental Sciences; Univ of Illinois, 1102 S Goodwin, Urbana, IL 61801, and Alan Anderson, US Army Corps of Engineers, CERL, 2902 Farber Dr, Champaign, IL 61822.

The Army Training and Testing Area Carrying Capacity (ATTACC) program is developed to estimate training land carrying capacity so as to meet the goal of the Integrated Training Area Management (ITAM) program. The Range and Training Land Assessment (RTLA, formerly called LCTA - Land Condition Trend Analysis) plot inventory methods were proposed as a critical data driver of the ATTACC program and have been used to collect field data that are needed for investigation and monitoring of land condition dynamics due to vehicle use in the U.S. Army Installations. However, the cost-efficiency of the sampling and inventory methods and their applications to different landscape types is unknown. Since 1998, the University of Illinois, Spatial Methods & Dynamics Modeling Laboratory (UI-SMDML) has been cooperating with Engineer Research and Development Center, Construction Engineering Research Laboratory (ERDC-CERL) for investigation, assessment and improvement of the RTLA/LCTA methods. This cooperation has led to six publications that deal with development of optimal sampling design methods and their comparison with RTLA/LCTA methods. The methods include determination of optimal spatial and temporal resolutions for data collection and mapping (that is, optimal plot size, optimal pixel size, and optimal time interval), selection of plot shape and its relationship with remote sensing mapping, determination of optimal sample size, the relationship of plot size with sample size and optimization in terms of cost-efficiency. This presentation will summarize and present the methods, results and implication for improving the RTLA/LCTA.