Thermal Radiation Dynamics of Soil Surfaces with Unmanned Aerial Systems (original) (raw)
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ISPRS Journal of Photogrammetry and Remote Sensing
Airborne thermal cameras are a valuable source of information for energy analyses at city scale. The generation of accurate high-resolution thermal orthomosaics is a necessary but still challenging task, especially when a thermal camera is the only imaging sensor on-board, because of the peculiar characteristics of thermal imagery (i.e. low dynamic range and poor detail definition), large geometric distortions induced by the optical system and weak acquisition geometry. This paper discusses potentials and limitations of Structure from Motion approach for the automated generation of thermal orthomosaics, with the aim to define the best practices and assess the achievable accuracy. After processing with different strategies two thermal flights over a 10 km 2 area in Bologna city (Italy), it can be concluded that the absolute planimetric accuracy can be in the order of 3-4 pixels and the best results are obtained when computing camera calibration on a smaller subset of images, with a limited number of ground control points and an adaptive fitting algorithm. The analysis of generated point clouds (compared with reference LiDAR data) and calibration reports, in addition to check point residuals, proved to be crucial for a proper accuracy assessment.
Calibrating thermal imagery from an unmanned aerial system - AggieAir
2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013
Small unmanned aerial systems (UAS) can be very useful for acquiring high resolution thermal imagery for many ecological applications. With these systems, routine ground sampling is important in order to calibrate the imagery and to understand unique environmental disturbances. Simple, accurate methods to sample surface temperature is needed. This paper introduces two methods for sampling ground surface temperatures. One method uses a ground-based thermal camera to capture a high-resolution sample of a small area. The other method uses temperature controlled pools, which can be seen from the aerial thermal image. These samples are used to calibrate a thermal mosaic captured by the UAS AggieAir. Accuracy and simplicity are evaluated for each method.
A Cost-Effective System for Aerial 3D Thermography of Buildings
Journal of Imaging
Three-dimensional (3D) imaging and infrared (IR) thermography are powerful tools in many areas in engineering and sciences. Their joint use is of great interest in the buildings sector, allowing inspection and non-destructive testing of elements as well as an evaluation of the energy efficiency. When dealing with large and complex structures, as buildings (particularly historical) generally are, 3D thermography inspection is enhanced by Unmanned Aerial Vehicles (UAV—also known as drones). The aim of this paper is to propose a simple and cost-effective system for aerial 3D thermography of buildings. Special attention is thus payed to instrument and reconstruction software choice. After a very brief introduction to IR thermography for buildings and 3D thermography, the system is described. Some experimental results are given to validate the proposal.
Remote Sensing, 2020
Land surface temperature (LST) is a fundamental parameter within the system of the Earth’s surface and atmosphere, which can be used to describe the inherent physical processes of energy and water exchange. The need for LST has been increasingly recognised in agriculture, as it affects the growth phases of crops and crop yields. However, challenges in overcoming the large discrepancies between the retrieved LST and ground truth data still exist. Precise LST measurement depends mainly on accurately deriving the surface emissivity, which is very dynamic due to changing states of land cover and plant development. In this study, we present an LST retrieval algorithm for the combined use of multispectral optical and thermal UAV images, which has been optimised for operational applications in agriculture to map the heterogeneous and diverse agricultural crop systems of a research campus in Germany (April 2018). We constrain the emissivity using certain NDVI thresholds to distinguish diffe...
Integration of Thermal and RGB Data Obtained by Means of a Drone for Interdisciplinary Inventory
Energies
Thermal infrared imagery is very much gaining in importance in the diagnosis of energy losses in cultural heritage through non-destructive measurement methods. Hence, owing to the fact that it is a very innovative and, above all, safe solution, it is possible to determine the condition of the building, locate places exposed to thermal escape, and plan actions to improve the condition of the facility. The presented work is devoted to the technology of creating a dense point cloud and a 3D model, based on data obtained from UAV. It has been shown that it is possible to build a 3D point model based on thermograms with the specified accuracy by using thermal measurement marks and the dense matching method. The results achieved in this way were compared and, as the result of this work, the model obtained from color photos was integrated with the point cloud created on the basis of the thermal images. The discussed approach exploits measurement data obtained with three independent devices...
Capturing the Diurnal Cycle of Land Surface Temperature Using an Unmanned Aerial Vehicle
Remote Sensing
Characterizing the land surface temperature (LST) and its diurnal cycle is important in understanding a range of surface properties, including soil moisture status, evaporative response, vegetation stress and ground heat flux. While remote-sensing platforms present a number of options to retrieve this variable, there are inevitable compromises between the resolvable spatial and temporal resolution. For instance, the spatial resolution of geostationary satellites, which can provide sub-hourly LST, is often too coarse (3 km) for many applications. On the other hand, higher-resolution polar orbiting satellites are generally infrequent in time, with return intervals on the order of weeks, limiting their capacity to capture surface dynamics. With recent developments in the application of unmanned aerial vehicles (UAVs), there is now the opportunity to collect LST measurements on demand and at ultra-high spatial resolution. Here, we detail the collection and analysis of a UAV-based LST da...
Combined Geometric and Thermal Analysis from Uav Platforms for Archaeological Heritage Documentation
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013
The aim of this work is to study the value and potential of UAV technology as an instrument for documenting and analyzing a heritage site on both the detailed scale and the wider territorial scale. In particular, this paper will focus on the application of an UAV platform on the archeological site of Isola Comacina (Comacina Island), in the Lago di Como (Lake Como, Lombardy, Northern Italy). The work considers the advantages of different metric scales and the use of both RGB and thermal imagery, along with other terrestrial data (total station measurements and laser scans), in order to arrive at a working heritage information model. In particular, the archaeological remains on Isola Comacina have been intensively studied before by standard techniques but unfortunately no wider context is provided. A part of the research is the investigation of new methodologies offered by accurate geometric reconstructions combined with thermal imagery acquired by means of UAV platforms, e.g. the support of this type of imagery to discover rock formations partially buried. Figure 1. UAV system (Asctec Falcon 8), DEM extracted from digital images, RGB and thermal orthophotos.
Remote Sensing, 2018
The high demand for unmanned aerial systems (UASs) reflects the notable impact that these systems have had on the remote sensing field in recent years. Such systems can be used to discover new findings and develop strategic plans in related scientific fields. In this work, a case study is performed to describe a novel approach that uses a UAS with two different sensors and assesses the possibility of monitoring peatland in a small area of a plantation forest in West Kalimantan, Indonesia. First, a multicopter drone with an onboard camera was used to collect aerial images of the study area. The structure from motion (SfM) method was implemented to generate a mosaic image. A digital surface model (DSM) and digital terrain model (DTM) were used to compute a canopy height model (CHM) and explore the vegetation height. Second, a multicopter drone combined with a thermal infrared camera (Zenmuse-XT) was utilized to collect both spatial and temporal thermal data from the study area. The te...
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Thermography is a robust method for detecting thermal irregularities on the roof of the buildings as one of the main energy dissipation parts. Recently, UAVs are presented to be useful in gathering 3D thermal data of the building roofs. In this topic, the low spatial resolution of thermal imagery is a challenge which leads to a sparse resolution in point clouds. This paper suggests the fusion of visible and thermal point clouds to generate a high-resolution thermal point cloud of the building roofs. For the purpose, camera calibration is performed to obtain internal orientation parameters, and then thermal point clouds and visible point clouds are generated. In the next step, both two point clouds are geo-referenced by control points. To extract building roofs from the visible point cloud, CSF ground filtering is applied, and the vegetation layer is removed by RGBVI index. Afterward, a predefined threshold is applied to the normal vectors in the z-direction in order to separate facets of roofs from the walls. Finally, the visible point cloud of the building roofs and registered thermal point cloud are combined and generate a fused dense point cloud. Results show mean re-projection error of 0.31 pixels for thermal camera calibration and mean absolute distance of 0.2 m for point clouds registration. The final product is a fused point cloud, which its density improves up to twice of the initial thermal point cloud density and it has the spatial accuracy of visible point cloud along with thermal information of the building roofs.
Remote estimation of thermal inertia and soil heat flux for bare soil
Agricultural and forest meteorology, 2004
A method is presented which allows thermal inertia (the soil heat capacity times the square root of the soil thermal diffusivity, C h √ D h ), to be estimated remotely from micrometeorological observations. The method uses the drop in surface temperature, T s , between sunset and sunrise, and the average night-time net radiation during that period, for clear, still nights. A Fourier series analysis was applied to analyse the time series of T s . The Fourier series constants, together with the remote estimate of thermal inertia, were used in an analytical expression to calculate diurnal estimates of the soil heat flux, G. These remote estimates of C h √ D h and G compared well with values derived from in situ sensors. The remote and in situ estimates of C h √ D h both correlated well with topsoil moisture content. This method potentially allows area-average estimates of thermal inertia and soil heat flux to be derived from remote sensing, e.g. METEOSAT Second Generation, where the area is determined by the sensor's height and viewing angle.