## 1 Introduction
The performance of a valid measurement with infrared thermography requires the consideration of certain requirements, since the thermal infrared technique is based on the measurement of the incoming radiation to the camera, and its conversion to temperature values [20], which presents many parameters of influence, mainly: radiation from surrounding objects, the emissivity of the object under study, the distance from camera to object and ambient temperature and humidity [21]. In addition to the consideration of the parameters of interest, the conversion from incoming thermal infrared radiation to temperature values requires the thermal or radiometric calibration of the camera, that is, the equation that inputs radiation and outputs temperature values. Traditionally, thermal infrared cameras are calibrated using a temperature modulated black body target, under laboratory conditions [22]. This type of calibration reaches an accuracy of 0.06-0.2 K [22] for static measurements, going up to 0.32 K for measurements performed from Unmanned Aerial Vehicles, UAV [23]. It is a time-consuming and complicated process, with a high cost regarding the final price of the camera [24]. The radiometric calibration is usually based on Plank curves for the determination of the correlation between infrared radiation and temperature [25], although other mathematical relations, such as linear and polynomial models, have been tested [26]. Recent advances have focused on image processing techniques and neural networks for the radiometric calibration, in an image-by-image calibration [27] or with specifically trained artificial neural networks [26]. Provided the complexity of the radiometric calibration procedures, efforts are being made towards the simplification of the process, starting from the design of plate radiators in contrast to the more expensive cavity blackbodies [28]. The authors of Reference [29] prove the validity of a three-point calibration for measurements performed from UAV platforms, while the authors of Reference [30] perform a radiometric calibration using images acquired by the thermographic camera of an object at constant temperature. The radiometric calibration can be completed with a geometric calibration that allows knowing the interior geometry of the camera: dimensions of the pixels, focal length of the camera lens and principal or central point of the image. In the case of thermal infrared cameras, the geometric calibration requires calibration boards specifically designed, either based on a temperature difference [31] or on an emissivity difference [32] between the targets and the background. This paper presents a novel approach for the thermal characterization of geothermal environments. This approach consists of the monitoring of the soil surface with a thermographic camera, which has been radiometrically calibrated with a novel, low-cost approach. The thermal imbalances within the soil depth and in the soil surface allow for the determination of the thermal conductivity of the soil material, which is complemented with the thermographic monitoring for the computation of the convection effect. In addition, the comparison of thermal conductivity values computed in-depth and at the surface works as a validation of the radiometric calibration of the thermographic camera, together with its comparison with manufacturer values. Thus, the paper is structured as follows: Section 2 describes the devices used for the study, the methodology for the radiometric calibration of the camera and the modeling of the thermal behavior of the system (underground and at the surface). Section 3 shows the results obtained from the thermal imbalances in-depth (thermal conductivity) and at the surface (convection effect). Section 4 includes a discussion of the results, while Section 5 presents the conclusions reached.