North-Central Section - 50th Annual Meeting - 2016

Paper No. 24-7
Presentation Time: 10:15 AM

IDENTIFICATION OF DEFECTS IN EARTHEN-COVERED LANDFILLS BY REMOTE SENSING


STOHR, Christopher1, STUMPF, Andrew J.1, BARRETT, Melony1, FILIPPINI, Heather2 and LUMAN, Donald E.1, (1)Illinois State Geological Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, 615 East Peabody Drive, Champaign, IL 61820, (2)Applied Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL 61820, cstohr@illinois.edu

The integrity of a landfill cover degrades as buried wastes decompose and soils undergo weathering. Depressions, asperities, wet spots, barren areas, and gullies develop in the covers, allowing infiltration of meteoric waters that mix with wastes. This occurrence produces unwanted leachate, which could contaminate surface and ground waters with costly consequences. Illinois has 3,400+ unlined landfills capped with about two or more feet of earthen cover. Almost one-half of these landfills lie over shallow aquifers within 20 feet of the land surface. Only a small portion are actively monitored. Periodic “walkover” inspections of landfills provide limited information about cover conditions. Field surveys might not find all defects in the cover because of time constraints and limited visibility of features. Rather than relying solely upon traverses to identify every serious defect, onsite inspections can be improved by interpreting aerial imagery to identify features of interest prior to field reconnaissance. Two sources of publicly available, digital, georeferenced, high-resolution, remote sensing imagery useful for postclosure monitoring are, 1) airborne lidar enhanced elevation data; and 2) digital, orthorectified, color and near-infrared (VNIR) photography. Defects were manually identified on enhanced, multi-date imagery based upon photographic cues for several closed landfills to test the technique. Measurements and interpretations were incorporated into a GIS-based image service to make a defect tracking database. Initial results of field tests appear promising and additional refinements are being developed. Identification of defects could be automated using signal processing and computer vision techniques. Focused inspections could be improved and expedited by use of cellular-based tablet computers which provide a live link to GIS-based imagery and databases allowing landfill mangers to update pre-visit interpretations onsite. Consequently, the occurrence and characteristics of defects and vegetation anomalies can be measured and tracked through time to identify areas where features of concern are developing, recurring or worsening. The use of remote sensing, cellular and GIS technologies can improve postclosure management of landfills and prioritize maintenance for repairs.