## 2 Study Goal and Site Description
### Satellite Data Acquisition and Processing  
The U.S. Geological Survey (USGS) Earth Explorer tool provides the ability to query, search, and order satellite images, aerial photographs, and cartographic products from several sources. However, none of these representations contain information related to temperature. To determine land surface temperature (LST) distributions, Level 1 satellite images of the exact location of the Bridgeton Sanitary Landfill (GeoTIFF format) were downloaded from the USGS online archive ([[https://earthexplorer.usgs.gov](https://earthexplorer.usgs.gov)]([https://earthexplorer.usgs.gov](https://earthexplorer.usgs.gov))) and were then processed as described below. Observations from Landsat satellites were used to detect the thermal state of the Bridgeton landfill area and to identify  
Figure 1: Outlines of Bridgeton landfill areas [20]. thermal anomalies at its surface. All relevant Landsat data generated between 2000 and 2016 were downloaded and images with only slight (less than 10%) overall cloud contamination were retained. All retained images were then subjected to an image acceptance test, i.e., an algorithm designed to use the Quality Assessment band (now available with downloaded data for Landsat 5, 7 and 8) to accept only images (in this study, the landfill scene) that have no clouds, snow, water, or other land cover that may lead to misleading results. In addition, the images were visually checked to ensure that the landfill area was not obscured by clouds. Due to cloud contamination of the imagery and because of the long, 16-day revisit time of Landsat satellites, the average annual number of clear-sky images collected was seven, for a total of 115 images over the 16-year time period. No reliable data were available between December 2011 and March 2013 as the Landsat 5 archive ended in November 2011, Landsat 8 was launched in April 2013, and the Landsat 7 data for 2012 were found to be unusable for this analysis because of sensor problems. The missing 2012 data is unfortunate, but only affect 15 months out of 204. Hotspots can still be tracked for over 93% of the period of interest. Images from 2000-2011 were obtained using the Landsat 5 TM. Starting from 2013, we acquired data from the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments. The number and positions of the spectral bands in the Landsat sensors differed, but we used all sensors that provided observations in the visible, near-infrared (near-IR), and thermal infrared (TIR) bands. The spatial resolution of all the sensors in the visible and near-IR bands was 30 m, and that of the TIR band was 120 m on the TM sensor and 100 m on the TIRS sensor. However, the USGS provides observations in these bands resampled to 30-m resolution, which is the same as that of the visible and near-IR bands. All scenes were acquired at Level 1B with observations in all bands provided as 8 bits for the TM and 16 bits for the OLI and TIRS. Preprocessing of the satellite imagery was performed according to the procedure described in the Landsat handbook [24]. Digital numbers (DNs) in the optical bands were converted first to radiance and then to reflectance. The reflectance values were corrected for variable Sun-Earth distances and normalized to the overhead Sun by dividing the reflectance by the cosine of the solar zenith angle. Observations in the TIR band were converted first to radiance and then to brightness temperature Tb values. The calibration coefficients used to convert DN counts into physical values (reflectance and brightness temperature) were obtained from metafiles supplied by the USGS with the Landsat imagery (Table 1).