The purpose of this study is to analyze the surface temperature and the distribution of thermal signatures on Tuscany’s geothermal districts using data obtained through three separate surveys via satellite and an unmanned aerial vehicle (UAV). The analysis considers the highest available spatial resolution ranging from hundreds of meters per pixel of the satellite thermal images and the tenths/hundreds of centimeters per pixel of the thermal images acquired by the UAV. The surface temperature maps obtained by satellite data acquired at suitable spatial resolution and the thermal measurements obtained by the thermal camera installed on the UAV were orthorectified and geocoded. This allowed, for example, following the evolution of thermal anomalies, which may represent a modification of the current state of the geothermal field and a possible hazard for both the population and industrial assets. Here, we show the results obtained in three field campaigns during which the simultaneous acquisition of Landsat 8 satellite and UAV (FlyBit octocopter, IDS, Rome, Italy) thermal data were analyzed. By removing the atmosphere contribution from Landsat 8 data, we have produced three surface temperature maps that are compared with the ground field measurements and the surface temperature maps elaborated by FLIR VUE PRO-R on the UAV.

Quiescent volcanoes dissipate a large part of their thermal energy through hot soils and ground degassing mainly in restricted areas called Diffuse Degassing Structures. La Solfatara crater represents the main spot of thermal release for the Campi Flegrei volcano (Italy) despite its reduced dimensions with regards to the whole caldera. The purpose of this study was to develop a method to measure thermal energy release extrapolating it from the ground surface temperature. We used imaging from thermal cameras at short distances (1 m) to obtain a mapping of areas with thermal anomalies and a measure of their temperatures. We built a conceptual model of the energy release from the ground to atmosphere, which well fits the experimental data taken in the La Solfatara crater. Using our model and data, we could estimate the average heat flux in a portion of the crater as $q_{avg}=220\pm 40{\mathrm{W}/\mathrm{m}}^2$ , compatible with other measurements in literature.

Thermal camera use is becoming ever more widespread in volcanic and environmental research and monitoring activities. Depending on the scope of an investigation and on the type of thermal camera used, different software for thermal infrared (IR) images analysis is employed. The Osservatorio Vesuviano Sezione in Napoli of the Istituto Nazionale di Geofisica e Vulcanologia (INGV-OV) processes the images acquired during thermal monitoring activities acquired in the Neapolitan areas (Vesuvio, Ischia and Campi Flegrei) with different FLIR software that returns for each image, or for each selected area within the image, a series of parameters (maximum temperature, average temperature, standard deviation, etc.). An operator selects the area of interest and later “manually” inserts the relevant parameters in Excel sheets to generate graphs. Such a tedious, time- and resource-consuming procedure gave reason to implement a software able to automatically analyze sets of thermal images taken with a handheld thermal camera without any manual action. This paper describes the method and the software implemented to “automate” and refine the extrapolation process and the analysis of the relevant information. The employed method clusters thermal images by applying K-MEANS and DBSCAN techniques. After clustering a series of images, the software displays the necessary statistics to highlight possible fluctuations in temperature values. The software, “StaTistical Analysis clusteRed ThErmal Data” (STARTED), is already available. Although it has been developed mostly to support monitoring of the volcanoes in Campania, it is quite versatile and can be used for any activity that implies thermal data analysis. In this paper, we describe the workflow and the dataset used to develop the software, as well as the first result obtained from it.

The measurement of volcanic gases, such as CO₂ and SO₂, emitted from summit craters and fumaroles is crucial to monitor volcanic activity, providing estimations of gases fluxes, and geochemical information that helps to assess the status and the risk level of an active volcano. During high degassing events, the measurement of volcanic emissions is a dangerous task that cannot be performed using hand portable or backpack carried gas analysis systems. Measurements of gases plumes could be safety achieved by using instruments mounted on UAS (Unmanned Aerial System). In this work, we present the measurements of CO₂, SO₂, and H₂S gases collected with a miniaturized MultiGAS instrument during 2021 and 2022 field campaigns. They took place at several thermally active areas in Italy: Pisciarelli (Naples, Italy), Stromboli volcano (Messina, Italy), and Parco Naturalistico delle Biancane (Grosseto, Italy).

The aim of this study is to analyse problems related to thermal mapping obtained from thermal data acquired from Unmanned Aerial Systems (UAS) equipped with thermal cameras. We focused on an accurate analysis of uncertainties introduced by the PIX4D Mapper software used to obtain the surface temperature maps of thermal images acquired by the UAS. To achieve this aim, we used artificial thermal reference during the surveys, as well as natural hot targets, i.e. thermal anomalies in the Pisciarelli hydrothermal system in Campi Flegrei caldera (CFc). Artificial thermal targets, expressly created and designed for this goal, are a prototype here called “developed thermal target” (DTT) made by the drone Laboratory at Istituto Nazionale di Geofisica e Vulcanologia - Osservatorio Vesuviano (INGV-OV). We show the results obtained by three surveys during which thermal targets were positioned on land at different flight heights of the UAS. Different heights were also necessary to test spatial resolution of the DTT with the used thermal camera as well as possible temperature differences between the raw images acquired by UAS with the thermal mapping obtained from the PIX4D Mapper software. In this work we have estimated the uncertainty that may be introduced by the mosaic procedure and furthermore we find an attenuation of the measured temperatures introduced by the different distances between the thermal anomaly and sensor. These results appear to be of great importance for the subsequent calibration phase of the thermal maps especially in cases where these methodologies are applied for monitoring purposes of volcanic/geothermal areas.

The aim of this study is to analyse problems related to thermal mapping obtained from thermal data acquired from unmanned aerial systems (UAS) equipped with thermal cameras. We focused on an accurate analysis of uncertainties introduced by the PIX4D Mapper software version 4.4.12 used to obtain the surface temperature maps of thermal images acquired using the UAS. To achieve this aim, we used artificial thermal references during the surveys, as well as natural hot targets, i.e., thermal anomalies in the Pisciarelli hydrothermal system in Campi Flegrei caldera (CFc). Artificial thermal targets, expressly created and designed for this goal, are a prototype here called “developed thermal target” (DTT) created by the drone laboratory at Istituto Nazionale di Geofisica e Vulcanologia—Osservatorio Vesuviano (INGV-OV). We show the results obtained through three surveys, and during the last two, thermal targets were positioned on land at different flight heights of the UAS. Different heights were also necessary to test the spatial resolution of the DTT with the used thermal camera as well as possible temperature differences between the raw images acquired via UAS with the thermal mapping obtained from the PIX4D Mapper software. In this work, we estimate the uncertainty that may be introduced by the mosaic procedure, and furthermore we find an attenuation of the measured temperatures introduced by the different distances between the thermal anomaly and sensor. These results appear to be of great importance for the subsequent calibration phase of the thermal maps, especially in cases where these methodologies are applied for the purposes of monitoring volcanic/geothermal areas.