DETECTION AND ANALYSIS OF METHANE EMISSIONS FROM A LANDFILL USING UNMANNED AERIAL DRONE SYSTEMS AND SEMICONDUCTOR SENSORS

Abstract

Landfill operators must collect data on the topography of their landfills, their biological and hydrological characteristics, and local meteorological conditions. These data can be collected by satellite, using Unmanned Aerial Vehicles, or by traditional methods such as static flux chambers or modelling. They serve as the basis for landfill monitoring, including the identification and measurement of methane (CH4) gas emissions. Here, we present an approach for landfill mapping using sensor data from unmanned aerial drone systems (UADS) based on DJI Matrice 200 UAVs with Zenmuse X4S sensors and Trimble UX5 UAVs with Sony NEX-5R sensors. RGB (Red, Green, Blue) and near infrared (NIR) data from these sensors were processed using a Geographic Information System (GIS) to generate orthoimages, digital elevation models (DEMs), and normalized difference vegetation index (NDVI) maps. These were then used to evaluate changes in the surface structure and topography of the study area (Kariotiškės landfill, Lithuania). The NDVI maps were used to identify areas of sparse vegetation cover that may indicate localized CH4 emissions. Surface temperature maps based on thermal infrared (TIR) images were then prepared for analysis of these problematic areas. Finally, the presence of CH4 in these areas was investigated using a prototype lightweight gas sensor array. The structure of the Kariotiškės landfill site remained unchanged over three years, but there is evidence of possible CH4 gas influence at the landfill cover’s surface. The combination of UADS-mounted imaging systems and the prototype gas sensor array enabled rapid analysis of emission hotspots and of landfill topography.