Environmental Condition Assessment of US Military Installations Using GIS Based Spatial Multi-Criteria Decision Analysis

Abstract

Environment functions in various aspects including soil and water conservation, biodiversity and habitats, and landscape aesthetics. Comprehensive assessment of environmental condition is thus a great challenge. The issues include how to assess individual environmental components such as landscape aesthetics and integrate them into an indicator that can comprehensively quantify environmental condition. In this study, a geographic information systems based spatial multi-criteria decision analysis was used to integrate environmental variables and create the indicator. This approach was applied to Fort Riley Military installation in which land condition and its dynamics due to military training activities were assessed. The indicator was derived by integrating soil erosion, water quality, landscape fragmentation, landscape aesthetics, and noise based on the weights from the experts by assessing and ranking the environmental variables in terms of their importance. The results showed that landscape level indicator well quantified the overall environmental condition and its dynamics, while the indicator at level of patch that is defined as a homogeneous area that is different from its surroundings detailed the spatiotemporal variability of environmental condition. The environmental condition was mostly determined by soil erosion, then landscape fragmentation, water quality, landscape aesthetics, and noise. Overall, environmental condition at both landscape and patch levels greatly varied depending on the degree of ground and canopy disturbance and their spatial patterns due to military training activities and being related to slope. It was also determined the environment itself could be recovered quickly once military training was halt or reduced. Thus, this study provided an effective tool for the army land managers to monitor environmental dynamics and plan military training activities. Its limitation lies at that the obtained values of the indicator vary and are subjective to the experts' knowledge and experience. Thus, further advancing this approach is needed by developing a scientific method to derive the weights of environmental variables.

A dynamic simulation/optimization model for scheduling restoration of degraded military training lands

“…4 considering different types of vehicles at a certain site (e.g., Jones et al 2005). Several studies focused on natural characteristics, such as soil erosion properties (Althoff et al, 2007;Singer et al, 2012), soil wetness (Althoff and Thien, 2005), and vegetation cover (Greene and Nichols, 1996). Besides natural factors, some studies found that land conditions also depend on spatial intensity and temporal frequency of training activities (Howard et al, 2013) and continuous intensive training exercises on disturbed lands (Wang et al, 2014).…”

The Analytic Hierarchy Process in GIS-Driven Military Operation Base Selection: A Case Study in Sri Lanka

“…The use of GIS provides far-superior accuracy in analyzing locationbased information than previously used techniques, and supports easy information sharing, thus building a common picture of a geographic environment in a very short time period. This capacity supports MDMP by reducing uncertainty in decision making, and as such, GIS technologies have become widely used tools in a modern military organization [11][12][13]. Sri Lanka is a developing country, one which uses far fewer advanced technologies compared to other countries, especially within the military establishment.…”

Research Articles: Scenario Analysis for Urban Sustainability Assessment: A Spatial Multicriteria Decision-Analysis Approach

“…Multicriteria decision making is a mechanism to assist the decision maker in selecting the best alternative from a number of feasible alternatives under the presence of multiple choices, criteria, and priorities~Jankowski, 1995; Linkov and Moberg, 2012;Malczewski, 1999;Singer et al, 2012!. Typically, this technique begins with the generation of discrete set of alternatives, the formulation of the set of criteria, and an evaluation of the impact of each alternative on every criterion~Graymore, Wallis, and Richards, 2009!. The input criteria are organized in a decision matrix in which the rows of the matrix represent the alternatives; each attribute and the cells of the matrix contain the measured or assessed values of attributes with respect to the alternatives.…”