Claycap anomaly detection using hyperspectral remote sensing and lidargrammetric techniques.

摘要

Clay capped waste sites are a common method to dispose of the more than 40 million tons of hazardous waste produced in the United States every year (EPA, 2003). Due to the potential threat that hazardous waste poses, it is essential to monitor closely the performance of these facilities. Development of a monitoring system that exploits spectral and topographic changes over hazardous waste sites is presented. Spectral anomaly detection is based upon the observed changes in absolute reflectance and spectral derivatives in centipede grass (Eremochloa ophiuroides) under different irrigation levels. The spectral features that provide the best separability among irrigation levels were identified using Stepwise Discriminant Analyses. The Red Edge Position was selected as a suitable discriminant variable to compare the performance of a global and a local anomaly detection algorithm using a DAIS 3715 hyperspectral image. Topographical anomaly detection is assessed by evaluating the vertical accuracy of two LIDAR datasets acquired from two different altitudes (700 m and 1,200 m AGL) over a clay-capped hazardous site at the Savannah River National Laboratory, SC using the same Optech ALTM 2050 and Cessna 337 platform. Additionally, a quantitative comparison is performed to determine the effect that decreasing platform altitude and increasing posting density have on the vertical accuracy of the LIDAR data collected.