## 4 Results
### GIS Analysis for Hot Spot Identification  
The orthoimages obtained from the 3D models are analyzed with GIS in order to identify possible thermal anomalies and their causes. Through a first photointerpretation, different hot spots to be evaluated were identified, as shown in Figure 8. The identified points were chosen because these hot spots were considered the most relevant and there was no known prior justification. For example, it is possible to find hot spots in the lower left corner due to ash deposition from the incineration plant during image capture; these were not analyzed.  
Figure 5: RGB orthoimage of the MSW landfill.  
Figure 6: 3D thermal model (X,Y,Z-temperature) of the MSW landfill. The 4D point cloud provides the position in space and the temperature for each point.  
Analysis using GIS functions such as reclassifications, segmentations, or the application of enhancement filters for digital identification of thermal anomalies is possible. The application of enhancing or softening filters allows certain conclusions to be reached. Since the temperature values of the data of interest may be modified, the application of this type of analysis may screen out or eliminate useful information.  
Figure 8: Hot spots identified through photointerpretation of the surface temperature distribution in the thermal orthoimage of the Meruelo MSW landfill.  
Figure 7: Thermal orthoimage of the Meruelo MSW landfill.  
Photointerpretation of the analog RGB orthoimage provides the most extensive thermal anomalies identified, such as zones A and D, with temperatures of 41.6 \({}^{\circ}\)C and 31.2 \({}^{\circ}\)C, respectively. Most of the hot spots identified correspond to areas of the landfill where plastic liners and geotextiles are exposed, awaiting the deposition of new MSW to cover them, as can be seen in Figure 9.  
In the lower right corner of Figure 8 is the hot spot G, an area of high temperatures (33.8 \({}^{\circ}\)C) that is shown in detail in Figure 10. The anomaly in this case may be due to two causes. First of all, the interpretation of the RGB orthoimage enables the deduction that the lack of vegetation is the main cause. Secondly, by analyzing the leachate collection system, it is possible to note that there is a set of subway pipes located in this specific area. The fluids from the decomposition of organic matter in the landfill may have high temperatures, and the buried collection pipe may heat up the soil as a result, or there may be leaks in the piping.  
The other hot spots that were identified lack an a priori justified cause derived from the photointerpretation or analysis of the installations. In this case (Figure 11), zones B (33.3 \({}^{\circ}\)C) and C (27.3 \({}^{\circ}\)C) show homogeneous parts of the surface terrain where there are temperature differences that may indicate a heat source underneath. These anomalies may be due to possible LFG emission zones, decomposition of buried organic matter, or underground fires.  
In the oldest zone of the landfill (right side of Figure 8), two other areas of thermal anomalies in need of justification can be identified. Figure 12 shows a stockpile of material that is at a higher temperature (26.4 \({}^{\circ}\)C) than the surrounding area, and it is even higher  
Figure 9: Detail of the thermal and RGB photointerpretation for the hot spots A and D. These thermal anomalies are due to the exposure of geotextiles in the Meruelo MSW landfill.