Comparison of military and nonmilitary land condition using an image derived soil erosion cover factor

Abstract

Land condition of military installations varies spatially and temporally mainly due to variable intensity and frequency of military training induced disturbance. The existing ground-based methods to assess the land condition are costly and time consuming. There is thus a strong need to develop an efficient and low-cost methodology for modeling and monitoring of the land condition for military installations and compare it with nonmilitary land to assess the training induced impacts. For this purpose, in this study Fort Riley military installation (FR) and its neighboring Konza Prairie Biological Station (KPBS) were chosen. A remote sensing based linear spectral mixture (LSM) analysis method was proposed to model, monitor, and compare the land conditions of both sites by developing a soil erosion relevant and image derived cover factor (ICF) using both Landsat Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) images. The results showed that (1) the LSM based ICF was statistically significantly correlated with military training induced disturbance intensity and can be used to quantify the land conditions; (2) the ICF provided the potential to generate spatially and temporally explicit estimates of the land conditions; (3) the ICF time series revealed that the land condition of FR fluctuated with a slight decreasing trend of ICF values, but statistically the trend was not significant; and (4) small ICF values dominated both FR and KPBS, but compared to that in the nonmilitary land KPBS, military training led to significantly poorer land condition in the military land FR. Overall, the ICF method provides a potential tool to spatially and temporally assess land conditions of military installations. It is expected that this method can be applied to assess land conditions for other military and nonmilitary areas.