Journal articles: 'Thermal imagery'

1

Ulhaq, Anwaar, Peter Adams, Tarnya E. Cox, Asim Khan, Tom Low, and Manoranjan Paul. "Automated Detection of Animals in Low-Resolution Airborne Thermal Imagery." Remote Sensing 13, no. 16 (August 19, 2021): 3276. http://dx.doi.org/10.3390/rs13163276.

Full text

Abstract:

Detecting animals to estimate abundance can be difficult, particularly when the habitat is dense or the target animals are fossorial. The recent surge in the use of thermal imagers in ecology and their use in animal detections can increase the accuracy of population estimates and improve the subsequent implementation of management programs. However, the use of thermal imagers results in many hours of captured flight videos which require manual review for confirmation of species detection and identification. Therefore, the perceived cost and efficiency trade-off often restricts the use of these systems. Additionally, for many off-the-shelf systems, the exported imagery can be quite low resolution (<9 Hz), increasing the difficulty of using automated detections algorithms to streamline the review process. This paper presents an animal species detection system that utilises the cost-effectiveness of these lower resolution thermal imagers while harnessing the power of transfer learning and an enhanced small object detection algorithm. We have proposed a distant object detection algorithm named Distant-YOLO (D-YOLO) that utilises YOLO (You Only Look Once) and improves its training and structure for the automated detection of target objects in thermal imagery. We trained our system on thermal imaging data of rabbits, their active warrens, feral pigs, and kangaroos collected by thermal imaging researchers in New South Wales and Western Australia. This work will enhance the visual analysis of animal species while performing well on low, medium and high-resolution thermal imagery.

APA, Harvard, Vancouver, ISO, and other styles

2

Gao, Lyuzhou, Liqin Cao, Yanfei Zhong, and Zhaoyang Jia. "Field-Based High-Quality Emissivity Spectra Measurement Using a Fourier Transform Thermal Infrared Hyperspectral Imager." Remote Sensing 13, no. 21 (November 5, 2021): 4453. http://dx.doi.org/10.3390/rs13214453.

Full text

Abstract:

Emissivity information derived from thermal infrared (TIR) hyperspectral imagery has the advantages of both high spatial and spectral resolutions, which facilitate the detection and identification of the subtle spectral features of ground targets. Despite the emergence of several different TIR hyperspectral imagers, there are still no universal spectral emissivity measurement standards for TIR hyperspectral imagers in the field. In this paper, we address the problems encountered when measuring emissivity spectra in the field and propose a practical data acquisition and processing framework for a Fourier transform (FT) TIR hyperspectral imager—the Hyper-Cam LW—to obtain high-quality emissivity spectra in the field. This framework consists of three main parts. (1) The performance of the Hyper-Cam LW sensor was evaluated in terms of the radiometric calibration and measurement noise, and a data acquisition procedure was carried out to obtain the useful TIR hyperspectral imagery in the field. (2) The data quality of the original TIR hyperspectral imagery was improved through preprocessing operations, including band selection, denoising, and background radiance correction. A spatial denoising method was also introduced to preserve the atmospheric radiance features in the spectra. (3) Three representative temperature-emissivity separation (TES) algorithms were evaluated and compared based on the Hyper-Cam LW TIR hyperspectral imagery, and the optimal TES algorithm was adopted to determine the final spectral emissivity. These algorithms are the iterative spectrally smooth temperature and emissivity separation (ISSTES) algorithm, the improved Advanced Spaceborne Thermal Emission and Reflection Radiometer temperature and emissivity separation (ASTER-TES) algorithm, and the Fast Line-of-sight Atmospheric Analysis of Hypercubes-IR (FLAASH-IR) algorithm. The emissivity results from these different methods were compared to the reference spectra measured by a Model 102F spectrometer. The experimental results indicated that the retrieved emissivity spectra from the ISSTES algorithm were more accurate than the spectra retrieved by the other methods on the same Hyper-Cam LW field data and had close consistency with the reference spectra obtained from the Model 102F spectrometer. The root-mean-square error (RMSE) between the retrieved emissivity and the standard spectra was 0.0086, and the spectral angle error was 0.0093.

APA, Harvard, Vancouver, ISO, and other styles

3

Galbraith, A. E., J. Theiler, K. J. Thome, and R. W. Ziolkowski. "Resolution enhancement of multilook imagery for the multispectral thermal imager." IEEE Transactions on Geoscience and Remote Sensing 43, no. 9 (September 2005): 1964–77. http://dx.doi.org/10.1109/tgrs.2005.853569.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Singh Rawat, Kishan, V. K. Sehgal, and S. S. Ray. "Downscaling of MODIS thermal imagery." Egyptian Journal of Remote Sensing and Space Science 22, no. 1 (April 2019): 49–58. http://dx.doi.org/10.1016/j.ejrs.2018.01.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Wynne, J. Judson, Jeff Jenness, Derek L. Sonderegger, Timothy N. Titus, Murzy D. Jhabvala, and Nathalie A. Cabrol. "Advancing Cave Detection Using Terrain Analysis and Thermal Imagery." Remote Sensing 13, no. 18 (September 8, 2021): 3578. http://dx.doi.org/10.3390/rs13183578.

Full text

Abstract:

Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) Determine the efficacy of methods designed for terrain analysis and applied to thermal imagery; (2) evaluate the usefulness of predawn and midday imagery for detecting caves; and (3) ascertain which imagery type (predawn, midday, or the difference between those two times) was most informative. Using forward stepwise logistic (FSL) and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses for model selection, and a thermal imagery dataset acquired from the Mojave Desert, California, we examined the efficacy of three well-known terrain descriptors (i.e., slope, topographic position index (TPI), and curvature) on thermal imagery for cave detection. We also included the actual, untransformed thermal DN values (hereafter “unenhanced thermal”) as a fourth dataset. Thereafter, we compared the thermal signatures of known cave entrances to all non-cave surface locations. We determined these terrain-based analytical methods, which described the “shape” of the thermal landscape, hold significant promise for cave detection. All imagery types produced similar results. Down-selected covariates per imagery type, based upon the FSL models, were: Predawn— slope, TPI, curvature at 0 m from cave entrance, as well as slope at 1 m from cave entrance; midday— slope, TPI, and unenhanced thermal at 0 m from cave entrance; and difference— TPI and slope at 0 m from cave entrance, as well as unenhanced thermal and TPI at 3.5 m from cave entrance. We provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery.

APA, Harvard, Vancouver, ISO, and other styles

6

Maguire, Mitchell S., Christopher M. U. Neale, and Wayne E. Woldt. "Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications." Remote Sensing 13, no. 9 (April 22, 2021): 1635. http://dx.doi.org/10.3390/rs13091635.

Full text

Abstract:

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by leveraging the increased thermal signatures of water stressed plants. Thermal infrared cameras suitable for UAS remote sensing are often uncooled microbolometers. This type of thermal camera is subject to inaccuracies not typically present in cooled thermal cameras. In addition, atmospheric interference also may present inaccuracies in measuring surface temperature. In this study, a UAS with integrated FLIR Duo Pro R (FDPR) thermal camera was used to collect thermal imagery over a maize and soybean field that contained twelve infrared thermometers (IRT) that measured surface temperature. Surface temperature measurements from the UAS FDPR thermal imagery and field IRTs corrected for emissivity and atmospheric interference were compared to determine accuracy of the FDPR thermal imagery. The comparison of the atmospheric interference corrected UAS FDPR and IRT surface temperature measurements yielded a RMSE of 2.24 degree Celsius and a R2 of 0.85. Additional approaches for correcting UAS FDPR thermal imagery explored linear, second order polynomial and artificial neural network models. These models simplified the process of correcting UAS FDPR thermal imagery. All three models performed well, with the linear model yielding a RMSE of 1.27 degree Celsius and a R2 of 0.93. Laboratory experiments also were completed to test the measurement stability of the FDPR thermal camera over time. These experiments found that the thermal camera required a warm-up period to achieve stability in thermal measurements, with increased warm-up duration likely improving accuracy of thermal measurements.

APA, Harvard, Vancouver, ISO, and other styles

7

LEINONEN, I., O. M. GRANT, C. P. P. TAGLIAVIA, M. M. CHAVES, and H. G. JONES. "Estimating stomatal conductance with thermal imagery." Plant, Cell and Environment 29, no. 8 (August 2006): 1508–18. http://dx.doi.org/10.1111/j.1365-3040.2006.01528.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Ding, De Hong, Kui Fang, He Xiang Yu, Ke Jun Qian, and Dai Jun Cui. "Research of Infrared Thermal Imagery Segmentation Technology Based on Visible Light Image." Applied Mechanics and Materials 401-403 (September 2013): 1534–38. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.1534.

Full text

Abstract:

To solve the problem of infrared target recognition, byusing the complementarity of visible-light image and infrared-thermal imagery, thisarticle presents a kind of infrared thermal imagery segmentation technology. Segmentingthe target edges of visible-light images, and superimposing the edge on thecorresponding infrared thermal imagery, then segmenting the infrared thermalimagery by the improved weighted regions growing algorithm. After the testabout relevant parameters of the infraredthermal imagery, found that contrast enhancement and entropy increase, witchmaking it easy to split and recognize, and human eye subjective judgment isalso much easier. It put forward a new research method about infrared targetrecognition

APA, Harvard, Vancouver, ISO, and other styles

9

Hasani, H., and F. Samadzadegan. "3D OBJECT CLASSIFICATION BASED ON THERMAL AND VISIBLE IMAGERY IN URBAN AREA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 11, 2015): 287–91. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-287-2015.

Full text

Abstract:

The spatial distribution of land cover in the urban area especially 3D objects (buildings and trees) is a fundamental dataset for urban planning, ecological research, disaster management, <i>etc</i>. According to recent advances in sensor technologies, several types of remotely sensed data are available from the same area. Data fusion has been widely investigated for integrating different source of data in classification of urban area. Thermal infrared imagery (TIR) contains information on emitted radiation and has unique radiometric properties. However, due to coarse spatial resolution of thermal data, its application has been restricted in urban areas. On the other hand, visible image (VIS) has high spatial resolution and information in visible spectrum. Consequently, there is a complementary relation between thermal and visible imagery in classification of urban area. This paper evaluates the potential of aerial thermal hyperspectral and visible imagery fusion in classification of urban area. In the pre-processing step, thermal imagery is resampled to the spatial resolution of visible image. Then feature level fusion is applied to construct hybrid feature space include visible bands, thermal hyperspectral bands, spatial and texture features and moreover Principle Component Analysis (PCA) transformation is applied to extract PCs. Due to high dimensionality of feature space, dimension reduction method is performed. Finally, Support Vector Machines (SVMs) classify the reduced hybrid feature space. The obtained results show using thermal imagery along with visible imagery, improved the classification accuracy up to 8% respect to visible image classification.

APA, Harvard, Vancouver, ISO, and other styles

10

Khodaei, B., F. Samadzadegan, F. Dadras Javan, and H. Hasani. "3D SURFACE GENERATION FROM AERIAL THERMAL IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 11, 2015): 401–5. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-401-2015.

Full text

Abstract:

Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.

APA, Harvard, Vancouver, ISO, and other styles

11

Fernandez-Gallego, Jose, Ma Buchaillot, Nieves Aparicio Gutiérrez, María Nieto-Taladriz, José Araus, and Shawn Kefauver. "Automatic Wheat Ear Counting Using Thermal Imagery." Remote Sensing 11, no. 7 (March 28, 2019): 751. http://dx.doi.org/10.3390/rs11070751.

Full text

Abstract:

Ear density is one of the most important agronomical yield components in wheat. Ear counting is time-consuming and tedious as it is most often conducted manually in field conditions. Moreover, different sampling techniques are often used resulting in a lack of standard protocol, which may eventually affect inter-comparability of results. Thermal sensors capture crop canopy features with more contrast than RGB sensors for image segmentation and classification tasks. An automatic thermal ear counting system is proposed to count the number of ears using zenithal/nadir thermal images acquired from a moderately high resolution handheld thermal camera. Three experimental sites under different growing conditions in Spain were used on a set of 24 varieties of durum wheat for this study. The automatic pipeline system developed uses contrast enhancement and filter techniques to segment image regions detected as ears. The approach is based on the temperature differential between the ears and the rest of the canopy, given that ears usually have higher temperatures due to their lower transpiration rates. Thermal images were acquired, together with RGB images and in situ (i.e., directly in the plot) visual ear counting from the same plot segment for validation purposes. The relationship between the thermal counting values and the in situ visual counting was fairly weak (R2 = 0.40), which highlights the difficulties in estimating ear density from one single image-perspective. However, the results show that the automatic thermal ear counting system performed quite well in counting the ears that do appear in the thermal images, exhibiting high correlations with the manual image-based counts from both thermal and RGB images in the sub-plot validation ring (R2 = 0.75–0.84). Automatic ear counting also exhibited high correlation with the manual counting from thermal images when considering the complete image (R2 = 0.80). The results also show a high correlation between the thermal and the RGB manual counting using the validation ring (R2 = 0.83). Methodological requirements and potential limitations of the technique are discussed.

APA, Harvard, Vancouver, ISO, and other styles

12

Abdullah, Woolpert's Qassim, and Nadja Turek. "Thermal Imagery for Building and Utilities Owners." Photogrammetric Engineering & Remote Sensing 87, no. 10 (October 1, 2021): 689–96. http://dx.doi.org/10.14358/pers.87.10.689.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Baker, Emily A. "Measuring stream temperature using thermal infrared imagery." Nature Reviews Earth & Environment 1, no. 5 (April 15, 2020): 236. http://dx.doi.org/10.1038/s43017-020-0050-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Radosavljevic, Zvonko, and Mirko Jezdimirovic. "AU example of TV and thermal imagery." Vojnotehnicki glasnik 49, no. 3 (2001): 315–23. http://dx.doi.org/10.5937/vojtehg0103315r.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Yu, Y., and D. A. Rothrock. "Thin ice thickness from satellite thermal imagery." Journal of Geophysical Research: Oceans 101, no. C11 (November 15, 1996): 25753–66. http://dx.doi.org/10.1029/96jc02242.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Chandel, Narendra S., Yogesh A. Rajwade, Kumkum Dubey, Abhilash K. Chandel, A. Subeesh, and Mukesh K. Tiwari. "Water Stress Identification of Winter Wheat Crop with State-of-the-Art AI Techniques and High-Resolution Thermal-RGB Imagery." Plants 11, no. 23 (December 2, 2022): 3344. http://dx.doi.org/10.3390/plants11233344.

Full text

Abstract:

Timely crop water stress detection can help precision irrigation management and minimize yield loss. A two-year study was conducted on non-invasive winter wheat water stress monitoring using state-of-the-art computer vision and thermal-RGB imagery inputs. Field treatment plots were irrigated using two irrigation systems (flood and sprinkler) at four rates (100, 75, 50, and 25% of crop evapotranspiration [ETc]). A total of 3200 images under different treatments were captured at critical growth stages, that is, 20, 35, 70, 95, and 108 days after sowing using a custom-developed thermal-RGB imaging system. Crop and soil response measurements of canopy temperature (Tc), relative water content (RWC), soil moisture content (SMC), and relative humidity (RH) were significantly affected by the irrigation treatments showing the lowest Tc (22.5 ± 2 °C), and highest RWC (90%) and SMC (25.7 ± 2.2%) for 100% ETc, and highest Tc (28 ± 3 °C), and lowest RWC (74%) and SMC (20.5 ± 3.1%) for 25% ETc. The RGB and thermal imagery were then used as inputs to feature-extraction-based deep learning models (AlexNet, GoogLeNet, Inception V3, MobileNet V2, ResNet50) while, RWC, SMC, Tc, and RH were the inputs to function-approximation models (Artificial Neural Network (ANN), Kernel Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machine (SVM) and Long Short-Term Memory (DL-LSTM)) to classify stressed/non-stressed crops. Among the feature extraction-based models, ResNet50 outperformed other models showing a discriminant accuracy of 96.9% with RGB and 98.4% with thermal imagery inputs. Overall, classification accuracy was higher for thermal imagery compared to RGB imagery inputs. The DL-LSTM had the highest discriminant accuracy of 96.7% and less error among the function approximation-based models for classifying stress/non-stress. The study suggests that computer vision coupled with thermal-RGB imagery can be instrumental in high-throughput mitigation and management of crop water stress.

APA, Harvard, Vancouver, ISO, and other styles

17

Lin, Dong, Lutz Bannehr, Christoph Ulrich, and Hans-Gerd Maas. "Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8." Remote Sensing 12, no. 1 (December 30, 2019): 112. http://dx.doi.org/10.3390/rs12010112.

Full text

Abstract:

Thermal imagery is widely used in various fields of remote sensing. In this study, a novel processing scheme is developed to process the data acquired by the oblique airborne photogrammetric system AOS-Tx8 consisting of four thermal cameras and four RGB cameras with the goal of large-scale area thermal attribute mapping. In order to merge 3D RGB data and 3D thermal data, registration is conducted in four steps: First, thermal and RGB point clouds are generated independently by applying structure from motion (SfM) photogrammetry to both the thermal and RGB imagery. Next, a coarse point cloud registration is performed by the support of georeferencing data (global positioning system, GPS). Subsequently, a fine point cloud registration is conducted by octree-based iterative closest point (ICP). Finally, three different texture mapping strategies are compared. Experimental results showed that the global image pose refinement outperforms the other two strategies at registration accuracy between thermal imagery and RGB point cloud. Potential building thermal leakages in large areas can be fast detected in the generated texture mapping results. Furthermore, a combination of the proposed workflow and the oblique airborne system allows for a detailed thermal analysis of building roofs and facades.

APA, Harvard, Vancouver, ISO, and other styles

18

Tikunov, V. S., I. A. Rylskiy, and S. B. Lukatzkiy. "Evaluation of the expediency of using thermal i magery data for decryption exogenous processes and vegetation." Geodesy and Cartography 933, no. 3 (April 20, 2018): 52–62. http://dx.doi.org/10.22389/0016-7126-2018-933-3-52-62.

Full text

Abstract:

Innovative methods of aerial surveys changed approaches to information provision of projecting dramatically in last years. Nowadays there are several methods pretending to be the most efficient for collecting geospatial data intended for projecting – airborne laser scanning (LIDAR) data, RGB aerial imagery (forming 3D pointclouds) and orthoimages. Thermal imagery is one of the additional methods that can be used for projecting. LIDAR data is precise, it allows us to measure relief even under the vegetation, or to collect laser re-flections from wires, metal constructions and poles. Precision and completeness of the DEM, produced from LIDAR data, allows to define relief microforms. Airborne imagery (visual spectrum) is very widespread and can be easily depicted. Thermal images are more strange and less widespread, they use different way of image forming, and spectral features of ob-jects can vary in specific ways. Either way, the additional spectral band can be useful for achieving additional spatial data and different object features, it can minimize field works. Here different aspects of thermal imagery are described in comparison with RGB (visual) images, LIDAR data and GIS layers. The attempt to estimate the feasibility of thermal imag-es for new data extraction is made.

APA, Harvard, Vancouver, ISO, and other styles

19

Nugent, Paul W., Joseph A. Shaw, Nathan J. Pust, and Sabino Piazzolla. "Correcting Calibrated Infrared Sky Imagery for the Effect of an Infrared Window." Journal of Atmospheric and Oceanic Technology 26, no. 11 (November 1, 2009): 2403–12. http://dx.doi.org/10.1175/2009jtecha1288.1.

Full text

Abstract:

Abstract A method is demonstrated for deriving a correction for the effects of an infrared window when used to weatherproof a radiometrically calibrated thermal infrared imager. The technique relies on initial calibration of two identical imagers without windows and subsequently operating the imagers side by side: one with a window and one without. An equation is presented that expresses the scene radiance in terms of through-window radiance and the transmittance, reflectance, and emissivity of the window. The window’s optical properties are determined as a function of angle over the imager’s field of view through a matrix inversion using images observed simultaneously with and without a window. The technique is applied to calibrated sky images from infrared cloud imager systems. Application of this window correction algorithm to data obtained months before or after the algorithm was derived leads to an improvement from 0.46 to 0.91 for the correlation coefficient between data obtained simultaneously from imagers with and without a window. Once the window correction has been determined, the windowed imager can operate independently and provide accurate measurements of sky radiance.

APA, Harvard, Vancouver, ISO, and other styles

20

Soszynska, Agnieszka, Harald van der Werff, Jan Hieronymus, and Christoph Hecker. "A New and Automated Method for Improving Georeferencing in Nighttime Thermal ECOSTRESS Imagery." Sensors 23, no. 11 (May 25, 2023): 5079. http://dx.doi.org/10.3390/s23115079.

Full text

Abstract:

Georeferencing accuracy plays a crucial role in providing high-quality ready-to-use remote sensing data. The georeferencing of nighttime thermal satellite imagery conducted by matching to a basemap is challenging due to the complexity of thermal radiation patterns in the diurnal cycle and the coarse resolution of thermal sensors in comparison to sensors used for imaging in the visual spectral range (which is typically used for creating basemaps). The presented paper introduces a novel approach for the improvement of the georeferencing of nighttime thermal ECOSTRESS imagery: an up-to-date reference is created for each to-be-georeferenced image, derived from land cover classification products. In the proposed method, edges of water bodies are used as matching objects, since water bodies exhibit a relatively high contrast with adjacent areas in nighttime thermal infrared imagery. The method was tested on imagery of the East African Rift and validated using manually set ground control check points. The results show that the proposed method improves the existing georeferencing of the tested ECOSTRESS images by 12.0 pixels on average. The strongest source of uncertainty for the proposed method is the accuracy of cloud masks because cloud edges can be mistaken for water body edges and included in fitting transformation parameters. The georeferencing improvement method is based on the physical properties of radiation for land masses and water bodies, which makes it potentially globally applicable, and is feasible to use with nighttime thermal infrared data from different sensors.

APA, Harvard, Vancouver, ISO, and other styles

21

Dadras Javan, F., and M. Savadkouhi. "THERMAL 3D MODELS ENHANCEMENT BASED ON INTEGRATION WITH VISIBLE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 263–69. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-263-2019.

Full text

Abstract:

Abstract. In the last few years, Unmanned Aerial Vehicles (UAVs) are being frequently used to acquire high resolution photogrammetric images and consequently producing Digital Surface Models (DSMs) and orthophotos in a photogrammetric procedure for topography and surface processing applications. Thermal imaging sensors are mostly used for interpretation and monitoring purposes because of lower geometric resolution. But yet, thermal mapping is getting more important in civil applications, as thermal sensors can be used in condition that visible sensors cannot, such as foggy weather and night times which is not possible for visible cameras. But, low geometric quality and resolution of thermal images is a main drawback that 3D thermal modelling are encountered with. This study aims to offer a solution for to fixing mentioned problem and generating a thermal 3D model with higher spatial resolution based on thermal and visible point clouds integration. This integration leads to generate a more accurate thermal point cloud and DEM with more density and resolution which is appropriate for 3D thermal modelling. The main steps of this study are: generating thermal and RGB point clouds separately, registration of them in two course and fine level and finally adding thermal information to RGB high resolution point cloud by interpolation concept. Experimental results are presented in a mesh that has more faces (With a factor of 23) which leads to a higher resolution textured mesh with thermal information.

APA, Harvard, Vancouver, ISO, and other styles

22

Darettamarlan, R. R., H. Hidayat, and M. R. Darminto. "Correlation analysis of Land Surface Temperature (LST) measurement using DJI Mavic Enterprise Dual Thermal and Landsat 8 Satellite Imagery (case study: Surabaya City)." IOP Conference Series: Earth and Environmental Science 936, no. 1 (December 1, 2021): 012037. http://dx.doi.org/10.1088/1755-1315/936/1/012037.

Full text

Abstract:

Abstract Landsat 8 Satellite Imagery (Landsat Data Continuity Mission, LDCM) is a satellite product made by Orbital Science Corporation, which launched with The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments as the latest features. One of the Thermal Infrared Sensor (TIRS) instruments is called Band 10, that provide temperature information on the earth’s surface. As many research conduct the temperature comparison between satellite imagery analysis and land cover temperature has been come with positive correlation for both of the variable. As to prove the temperature relationship, it is necessary to validate the actual temperature values on the earth’s surface by conduct the temperature survey in the area using the temperature measurement tools. One of the tools is DJI Mavic Enterprise Dual Thermal camera as the camera that capable to take samples data of particular objects categories that included urban areas, waters, vegetation, open land, settlements, and industrial factories. Using the satellite imagery’s temperature data and the land cover temperature data survey, comparing and accuration assessment are needed to see how close the value of both variable. The data processing carried out that both of the data have a positive correlation as the relationship, which have a Pearson correlation value of 0.892 and sig. (2-tailed) at the number 0.000000068. This correlation value showed that the relationship between both data is acceptable as the both data can represent each other to conduct any research. However, as the satellite imagery contains 29,85% of cloud cover, the temperature obtained lower in the Landsat 8 satellite image rather than the actual temperature on the earth’s surface.

APA, Harvard, Vancouver, ISO, and other styles

23

Shcherbenko, Ye V., and S. G. Doroshenko. "Monitoring High-Water Conditions Using Nighttime Thermal Imagery." Mapping Sciences and Remote Sensing 39, no. 3 (September 2002): 170–80. http://dx.doi.org/10.2747/0749-3878.39.3.170.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Gupta, Umesh, Maitreyee Dutta, and Mahesh Vadhavaniya. "Analysis of Target Tracking Algorithm in Thermal Imagery." International Journal of Computer Applications 71, no. 16 (June 26, 2013): 34–41. http://dx.doi.org/10.5120/12443-9140.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Bedoya-Echeverry, Sebastián, Hernán Belalcázar-Ramírez, Humberto Loaiza-Correa, Sandra Esperanza Nope-Rodríguez, Carlos Rafael Pinedo-Jaramillo, and Andrés David Restrepo-Girón. "Detection of lies by facial thermal imagery analysis." Revista Facultad de Ingeniería 26, no. 44 (January 25, 2017): 45. http://dx.doi.org/10.19053/01211129.v26.n44.2017.5771.

Full text

Abstract:

An artificial vision system is presented for lie detection by analyzing face thermal image sequences. This system represents an alternative technique to the polygraph. Some of its features are: 1) it has no physical contact with the examinee, 2) it is non-intrusive, 3) it has a potential for private use, and 4) it can simultaneously analyze several persons. The proposed system is based on the detection of physiological changes in temperature in the lacrimal puncta area caused by the subtle increase in blood flow through the nearby vascular network. These changes take place when anxiety appears as a consequence of deception. Thus, the system segments the periorbital area, and tracks consecutive frames using the Kanade-Lucas-Tomasi algorithm. The results show a success rate of 79.2 % in detecting lies using a simple classification based on the comparison between the estimated temperatures in control questions, and the rest of the interrogation procedure. The performance of this system is comparable with previous works, where cameras with better specifications were used.

APA, Harvard, Vancouver, ISO, and other styles

26

Maes, Wouter, Alfredo Huete, and Kathy Steppe. "Optimizing the Processing of UAV-Based Thermal Imagery." Remote Sensing 9, no. 5 (May 12, 2017): 476. http://dx.doi.org/10.3390/rs9050476.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Anderson, P. S. "Ice-shelf microtopography observed using satellite thermal imagery." Journal of Glaciology 51, no. 175 (2005): 528–38. http://dx.doi.org/10.3189/172756505781829025.

Full text

Abstract:

AbstractSmall anomalies in ice-shelf surface temperature correlate with measured microtopography. Clear-sky thermal infrared (TIR) images of the Brunt Ice Shelf, Antarctica, frequently show persistent patterns of anomalous snow surface temperatures. The anomalous signatures appear as stripes orientated along the ice flowline and are of the order of 5 K in magnitude. The positional persistence of the stripes suggests a topographic mechanism for their formation. In order to test this hypothesis, the TIR stripes are compared to a digital terrain model (DTM) derived from a kinematic global positioning system survey of the ice shelf. Ridges and valleys are seen in the DTM; the ridges correspond to the warmer TIR stripes, the valleys to the colder areas. In order to investigate the mechanism that couples elevation with thermal signature, two comparable but contrasting sets of clear-sky infrared images are presented, along with surface meteorological data. The first shows strong TIR stripes, whilst the second, despite similar snow- and air-temperature profiles, shows a weaker signature and smaller sensible-heat flux, H. Two possible mechanisms are presented which explain the TIR signature: surface elevation mapping onto the vertical air-temperature profile or, alternatively, enhanced surface sensible-heat flux on elevated areas. At present, there is insufficient information to resolve this uncertainty.

APA, Harvard, Vancouver, ISO, and other styles

28

Mundy, Erin, Tom Gleeson, Mark Roberts, Michel Baraer, and Jeffrey M. McKenzie. "Thermal Imagery of Groundwater Seeps: Possibilities and Limitations." Groundwater 55, no. 2 (August 30, 2016): 160–70. http://dx.doi.org/10.1111/gwat.12451.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Chun, Myung Geun, and Seong G. Kong. "Focusing in thermal imagery using morphological gradient operator." Pattern Recognition Letters 38 (March 2014): 20–25. http://dx.doi.org/10.1016/j.patrec.2013.10.023.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Socolinsky, Diego A., Andrea Selinger, and Joshua D. Neuheisel. "Face recognition with visible and thermal infrared imagery." Computer Vision and Image Understanding 91, no. 1-2 (July 2003): 72–114. http://dx.doi.org/10.1016/s1077-3142(03)00075-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Willardson, Anthony G. "Landsat Thermal Infrared Imagery and Western Water Management." Journal of Contemporary Water Research & Education 153, no. 1 (April 2014): 42–48. http://dx.doi.org/10.1111/j.1936-704x.2014.03178.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Davis, James W., and Vinay Sharma. "Background-Subtraction in Thermal Imagery Using Contour Saliency." International Journal of Computer Vision 71, no. 2 (June 1, 2006): 161–81. http://dx.doi.org/10.1007/s11263-006-4121-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Kulsum, Umi. "STYLISTIC ANALYSIS ON WALTER SAVAGE LANDOR’S ‘ACON AND RHODOPE; OR, INCONSTANTLY’." Journal of English Education Program (JEEP) 8, no. 1 (April 28, 2021): 61. http://dx.doi.org/10.25157/(jeep).v8i1.5233.

Full text

Abstract:

This descriptive study is aimed to find out the types and the functions of imagery and to figure out the examples and the functions of archaic words which are found in poem. The documentary data was used in form of poem script “Acon and Rhodope; or, Inconstantly” written by Walter Savage Landor. Content analysis was used by the writer to analyze the content of poem which was adapted from Cohen, et al. (2007, p. 475). The findings showed that there were 174 words or expressions found in poem which were divided into seven types of imagery such as: visual, auditory, gustatory, olfactory, tactile, thermal, and kinesthesia. There were also seven functions of imagery in the poem: 1) visual imagery representing the sense of sight; 2) auditory imagery representing the sense of sound; 3) gustatory imagery or representing the sense of taste; 4) olfactory imagery representing the sense of smell; 5) tactile imagery representing the sense of touch; 6) thermal imagery representing the sense of heat and cold; and 7) kinesthesia imagery appealing to physical sensations of movement, balance, and muscular tension. Also, there were 95 archaic words found in poem to enhance the aesthetical or musical value of the poem, to find out the social life, customs, belief systems and generally cultural richness of the time he emerged, and to make his language old and solemn. It is suggested for the teacher to understand stylistic analysis used by the poets in their poems; and introduce stylistic analysis to the students so that they can improve knowledge of stylistic analysis and understand its meanings. Keywords: archaic words, imagery, stylistic analysis, Walter Savage Landor

APA, Harvard, Vancouver, ISO, and other styles

34

Gautam, Asheesh Kumar, Lokesh K. Sinha, and Mahendra R. Bhutiyani. "An Innovative Approach for Detection of Armoured Vehicle in Airborne Thermal Imagery Using Morphological Processing and Texture Feature Extraction." Journal of Intelligent Systems 26, no. 2 (April 1, 2017): 359–70. http://dx.doi.org/10.1515/jisys-2015-0132.

Full text

Abstract:

AbstractAutomatic detection of a vehicle in an airborne thermal imagery is a challenging research topic in computer vision, especially the detection of military tanks in the field. Various methodologies for detection in forward-looking infrared imagery, which has higher spatial resolution, has been discussed by a number of researchers in literature. The algorithm we developed in the present study detects tanks not only in higher resolution but in lower resolution imagery as well. Detection algorithm is initiated by the segmentation of thermal image using mean shift, which provides possible targets present in the field other than the background. To reduce clutter and uneven illumination in a thermal image, a pre-processing morphological algorithm based on top-hat filtering has been implemented. After convolution of image window with Gabor filter banks, we extracted the energy feature of each image generated after convolution. The energy vector of such a target and the neighbouring background window has been calculated, and the similarity between the target and background using distance-measuring method has been measured. The minimum distance is used as the threshold to decide the target. A comparative study has been carried out between tanks and various targets/objects that appear similar to tanks in a thermal image. This validates our target detection algorithm. The false-positive rate and true-positive rate have been calculated for performance evaluation. Overall, this algorithm shows promising results for tank detection using single-band thermal imagery.

APA, Harvard, Vancouver, ISO, and other styles

35

Cusson, Daniel, and Helen Stewart. "Satellite Synthetic Aperture Radar, Multispectral, and Infrared Imagery for Assessing Bridge Deformation and Structural Health—A Case Study at the Samuel de Champlain Bridge." Remote Sensing 16, no. 4 (February 7, 2024): 614. http://dx.doi.org/10.3390/rs16040614.

Full text

Abstract:

A space-borne remote sensing method was applied, validated, and demonstrated in a case study on the Samuel de Champlain Bridge in Montreal, Canada. High-resolution C-band radar satellite imagery was analyzed using the Persistent Scatterer Interferometric Synthetic Aperture Radar technique to derive bridge displacements and compare them against theoretical estimates. Multispectral and long-wave thermal infrared satellite imagery acquired during the InSAR observation period and historical environmental data were analyzed to provide context for the interpretation and understanding of InSAR results. Thermal deformation measurements compared well with their theoretical estimates based on known bridge geometry and ambient temperature data. Non-thermal deformation measurements gave no evidence of settlement during the 2-year monitoring period, as would normally be expected for a newly constructed bridge with its foundation on bedrock. The availability of environmental data obtained from multispectral and thermal infrared satellite imagery was found to be useful in providing context for the bridge stability assessment. Ambient temperature measurements from thermal infrared satellite imagery were found to be a suitable alternative in cases where data from in situ temperature sensors or nearby weather stations are not available or not fit for purpose. No strong correlation was found between the river conditions and bridge deformation results from the InSAR analysis; this is partly due to the fact that most of these effects act along the river flow in the north–south direction, to which the satellite sensor is not sensitive.

APA, Harvard, Vancouver, ISO, and other styles

36

Wei, Hong, Fang Jiang, Fang Shao, Denghui Zhang, Fang Gu, Ying Yang, Qiuxia Chen, and Zheng Ai. "Temperature Measurement and Control Application in a Laser Plastic Surgery Real Temperature Detection System." Scientific Programming 2021 (September 28, 2021): 1–5. http://dx.doi.org/10.1155/2021/8382482.

Full text

Abstract:

The purpose of this study was to grasp the development process of thermal image temperature measurement technology. It provides directional support for the optimization development of the thermal imagery and laser plastic surgery and laser treatment. This paper uses the infrared thermal image temperature measurement principle and performs infrared thermal image precise temperature measurement technology and its application research. The results showed that there was a correlation between 595 nm pulse dye laser, age, laser energy density, and skin temperature ( P < 0.05 ). There is a significant difference in the average ( P < 0.05 ). The infrared thermal imagery temperature monitoring system is a simple and relatively accurate temperature detection system that can be widely used in temperature measurement and control of laser plastic surgery.

APA, Harvard, Vancouver, ISO, and other styles

37

Glaser, Barbara, Marta Antonelli, Marco Chini, Laurent Pfister, and Julian Klaus. "Technical note: Mapping surface-saturation dynamics with thermal infrared imagery." Hydrology and Earth System Sciences 22, no. 11 (November 22, 2018): 5987–6003. http://dx.doi.org/10.5194/hess-22-5987-2018.

Full text

Abstract:

Abstract. Surface saturation can have a critical impact on runoff generation and water quality. Saturation patterns are dynamic, thus their potential control on discharge and water quality is also variable in time. In this study, we assess the practicability of applying thermal infrared (TIR) imagery for mapping surface-saturation dynamics. The advantages of TIR imagery compared to other surface-saturation mapping methods are its large spatial and temporal flexibility, its non-invasive character, and the fact that it allows for a rapid and intuitive visualization of surface-saturated areas. Based on an 18-month field campaign, we review and discuss the methodological principles, the conditions in which the method works best, and the problems that may occur. These considerations enable potential users to plan efficient TIR imagery-mapping campaigns and benefit from the full potential offered by TIR imagery, which we demonstrate with several application examples. In addition, we elaborate on image post-processing and test different methods for the generation of binary saturation maps from the TIR images. We test the methods on various images with different image characteristics. Results show that the best method, in addition to a manual image classification, is a statistical approach that combines the fitting of two pixel class distributions, adaptive thresholding, and region growing.

APA, Harvard, Vancouver, ISO, and other styles

38

Hill, Austin Chad, Elise Jakoby Laugier, and Jesse Casana. "Archaeological Remote Sensing Using Multi-Temporal, Drone-Acquired Thermal and Near Infrared (NIR) Imagery: A Case Study at the Enfield Shaker Village, New Hampshire." Remote Sensing 12, no. 4 (February 20, 2020): 690. http://dx.doi.org/10.3390/rs12040690.

Full text

Abstract:

While archaeologists have long understood that thermal and multi-spectral imagery can potentially reveal a wide range of ancient cultural landscape features, only recently have advances in drone and sensor technology enabled us to collect these data at sufficiently high spatial and temporal resolution for archaeological field settings. This paper presents results of a study at the Enfield Shaker Village, New Hampshire (USA), in which we collect a time-series of multi-spectral visible light, near-infrared (NIR), and thermal imagery in order to better understand the optimal contexts and environmental conditions for various sensors. We present new methods to remove noise from imagery and to combine multiple raster datasets in order to improve archaeological feature visibility. Analysis compares results of aerial imaging with ground-penetrating radar and magnetic gradiometry surveys, illustrating the complementary nature of these distinct remote sensing methods. Results demonstrate the value of high-resolution thermal and NIR imagery, as well as of multi-temporal image analysis, for the detection of archaeological features on and below the ground surface, offering an improved set of methods for the integration of these emerging technologies into archaeological field investigations.

APA, Harvard, Vancouver, ISO, and other styles

39

Iwaszczuk, D., and U. Stilla. "QUALITY ASSESSMENT OF BUILDING TEXTURES EXTRACTED FROM OBLIQUE AIRBORNE THERMAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 3–8. http://dx.doi.org/10.5194/isprsannals-iii-1-3-2016.

Full text

Abstract:

Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.

APA, Harvard, Vancouver, ISO, and other styles

40

Iwaszczuk, D., and U. Stilla. "QUALITY ASSESSMENT OF BUILDING TEXTURES EXTRACTED FROM OBLIQUE AIRBORNE THERMAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 3–8. http://dx.doi.org/10.5194/isprs-annals-iii-1-3-2016.

Full text

Abstract:

Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.

APA, Harvard, Vancouver, ISO, and other styles

41

Brunton, Elizabeth A., Javier X. Leon, and Scott E. Burnett. "Evaluating the Efficacy and Optimal Deployment of Thermal Infrared and True-Colour Imaging When Using Drones for Monitoring Kangaroos." Drones 4, no. 2 (May 27, 2020): 20. http://dx.doi.org/10.3390/drones4020020.

Full text

Abstract:

Advances in drone technology have given rise to much interest in the use of drone-mounted thermal imagery in wildlife monitoring. This research tested the feasibility of monitoring large mammals in an urban environment and investigated the influence of drone flight parameters and environmental conditions on their successful detection using thermal infrared (TIR) and true-colour (RGB) imagery. We conducted 18 drone flights at different altitudes on the Sunshine Coast, Queensland, Australia. Eastern grey kangaroos (Macropus giganteus) were detected from TIR (n=39) and RGB orthomosaics (n=33) using manual image interpretation. Factors that predicted the detection of kangaroos from drone images were identified using unbiased recursive partitioning. Drone-mounted imagery achieved an overall 73.2% detection success rate using TIR imagery and 67.2% using RGB imagery when compared to on-ground counts of kangaroos. We showed that the successful detection of kangaroos using TIR images was influenced by vegetation type, whereas detection using RGB images was influenced by vegetation type, time of day that the drone was deployed, and weather conditions. Kangaroo detection was highest in grasslands, and kangaroos were not successfully detected in shrublands. Drone-mounted TIR and RGB imagery are effective at detecting large mammals in urban and peri-urban environments.

APA, Harvard, Vancouver, ISO, and other styles

42

Edwards, Justin, and Mohamed El-Sharkawy. "FTFNet: Multispectral Image Segmentation." Journal of Low Power Electronics and Applications 13, no. 3 (June 30, 2023): 42. http://dx.doi.org/10.3390/jlpea13030042.

Full text

Abstract:

Semantic segmentation is a machine learning task that is seeing increased utilization in multiple fields, from medical imagery to land demarcation and autonomous vehicles. A real-time autonomous system must be lightweight while maintaining reasonable accuracy. This research focuses on leveraging the fusion of long-wave infrared (LWIR) imagery with visual spectrum imagery to fill in the inherent performance gaps when using visual imagery alone. This approach culminated in the Fast Thermal Fusion Network (FTFNet), which shows marked improvement over the baseline architecture of the Multispectral Fusion Network (MFNet) while maintaining a low footprint.

APA, Harvard, Vancouver, ISO, and other styles

43

Plank, Marchese, Filizzola, Pergola, Neri, Nolde, and Martinis. "The July/August 2019 Lava Flows at the Sciara del Fuoco, Stromboli–Analysis from Multi-Sensor Infrared Satellite Imagery." Remote Sensing 11, no. 23 (December 3, 2019): 2879. http://dx.doi.org/10.3390/rs11232879.

Full text

Abstract:

On 3 July 2019 a rapid sequence of paroxysmal explosions at the summit craters of Stromboli (Aeolian-Islands, Italy) occurred, followed by a period of intense Strombolian and effusive activity in July, and continuing until the end of August 2019. We present a joint analysis of multi-sensor infrared satellite imagery to investigate this eruption episode. Data from the Spinning-Enhanced-Visible-and-InfraRed-Imager (SEVIRI) was used in combination with those from the Multispectral-Instrument (MSI), the Operational-Land-Imager (OLI), the Advanced-Very High-Resolution-Radiometer (AVHRR), and the Visible-Infrared-Imaging-Radiometer-Suite (VIIRS). The analysis of infrared SEVIRI-data allowed us to detect eruption onset and to investigate short-term variations of thermal volcanic activity, providing information in agreement with that inferred by nighttime-AVHRR-observations. By using Sentinel-2-MSI and Landsat-8-OLI imagery, we better localized the active lava-flows. The latter were quantitatively characterized using infrared VIIRS-data, estimating an erupted lava volume of 6.33×106±3.17×106 m3 and a mean output rate of 1.26 ± 0.63 m3/s for the July/August 2019 eruption period. The estimated mean-output-rate was higher than the ones in the 2002–2003 and 2014 Stromboli effusive eruptions, but was lower than in the 2007-eruption. These results confirmed that a multi-sensor-approach might provide a relevant contribution to investigate, monitor and characterize thermal volcanic activity in high-risk areas.

APA, Harvard, Vancouver, ISO, and other styles

44

Fryskowska, A., M. Wojtkowska, P. Delis, and A. Grochala. "SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 647–52. http://dx.doi.org/10.5194/isprs-archives-xli-b7-647-2016.

Full text

Abstract:

The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5&dash;0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4&dash;0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2) and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.

APA, Harvard, Vancouver, ISO, and other styles

45

Fryskowska, A., M. Wojtkowska, P. Delis, and A. Grochala. "SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 647–52. http://dx.doi.org/10.5194/isprsarchives-xli-b7-647-2016.

Full text

Abstract:

The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5&dash;0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4&dash;0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2) and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.

APA, Harvard, Vancouver, ISO, and other styles

46

Lin, D., A. Eltner, H. Sardemann, and H. G. Maas. "AUTOMATIC SPATIO-TEMPORAL FLOW VELOCITY MEASUREMENT IN SMALL RIVERS USING THERMAL IMAGE SEQUENCES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2 (May 28, 2018): 201–8. http://dx.doi.org/10.5194/isprs-annals-iv-2-201-2018.

Full text

Abstract:

An automatic spatio-temporal flow velocity measurement approach, using an uncooled thermal camera, is proposed in this paper. The basic principle of the method is to track visible thermal features at the water surface in thermal camera image sequences. Radiometric and geometric calibrations are firstly implemented to remove vignetting effects in thermal imagery and to get the interior orientation parameters of the camera. An object-based unsupervised classification approach is then applied to detect the interest regions for data referencing and thermal feature tracking. Subsequently, GCPs are extracted to orient the river image sequences and local hot points are identified as tracking features. Afterwards, accurate dense tracking outputs are obtained using pyramidal Lucas-Kanade method. To validate the accuracy potential of the method, measurements obtained from thermal feature tracking are compared with reference measurements taken by a propeller gauge. Results show a great potential of automatic flow velocity measurement in small rivers using imagery from a thermal camera.

APA, Harvard, Vancouver, ISO, and other styles

47

Bird, Clara N., Allison H. Dawn, Julian Dale, and David W. Johnston. "A Semi-Automated Method for Estimating Adélie Penguin Colony Abundance from a Fusion of Multispectral and Thermal Imagery Collected with Unoccupied Aircraft Systems." Remote Sensing 12, no. 22 (November 11, 2020): 3692. http://dx.doi.org/10.3390/rs12223692.

Full text

Abstract:

Monitoring Adélie penguin (Pygoscelis adeliae) populations on the Western Antarctic Peninsula (WAP) provides information about the health of the species and the WAP marine ecosystem itself. In January 2017, surveys of Adélie penguin colonies at Avian Island and Torgersen Island off the WAP were conducted via unoccupied aircraft systems (UAS) collecting optical Red Green Blue (RGB), thermal, and multispectral imagery. A semi-automated workflow to count individual penguins using a fusion of multispectral and thermal imagery was developed and combined into an ArcGIS workflow. This workflow isolates colonies using multispectral imagery and detects and counts individuals by thermal signatures. Two analysts conducted manual counts from synoptic RGB UAS imagery. The automated system deviated from analyst counts by −3.96% on Avian Island and by 17.83% on Torgersen Island. However, colony-by-colony comparisons revealed that the greatest deviations occurred at larger colonies. Matched pairs analysis revealed no significant differences between automated and manual counts at both locations (p > 0.31) and linear regressions of colony sizes from both methods revealed significant positive relationships approaching unity (p < 0.0002. R2 = 0.91). These results indicate that combining UAS surveys with sensor fusion techniques and semi-automated workflows provide efficient and accurate methods for monitoring seabird colonies in remote environments.

APA, Harvard, Vancouver, ISO, and other styles

48

Pintér, Krisztina, and Zoltán Nagy. "Building a UAV Based System to Acquire High Spatial Resolution Thermal Imagery for Energy Balance Modelling." Sensors 22, no. 9 (April 23, 2022): 3251. http://dx.doi.org/10.3390/s22093251.

Full text

Abstract:

High spatial resolution and geolocation accuracy canopy evapotranspiration (ET) maps are well suited tools for evaluation of small plot field trials. While creating such a map by use of an energy balance model is routinely performed, the acquisition of the necessary imagery at a suitable quality is still challenging. An UAV based thermal/RGB integrated imaging system was built using the RaspberryPi (RPi) microcomputer as a central unit. The imagery served as input to the two-source energy balance model pyTSEB to derive the ET map. The setup’s flexibility and modularity are based on the multiple interfaces provided by the RPi and the software development kit (SDK) provided for the thermal camera. The SDK was installed on the RPi and used to trigger cameras, retrieve and store images and geolocation information from an onboard GNSS rover for PPK processing. The system allows acquisition of 8 cm spatial resolution thermal imagery from a 60 m height of flight and less than 7 cm geolocation accuracy of the mosaicked RGB imagery. Modelled latent heat flux data have been validated against latent heat fluxes measured by eddy covariance stations at two locations with RMSE of 75 W/m2 over a two-year study period.

APA, Harvard, Vancouver, ISO, and other styles

49

Ackerman, S. A., A. S. Bachmeier, K. Strabala, and M. Gunshor. "A Unique Satellite Perspective of the 13–14 January 2004 Record Cold Outbreak in the Northeast." Weather and Forecasting 20, no. 2 (April 1, 2005): 222–25. http://dx.doi.org/10.1175/waf842.1.

Full text

Abstract:

Abstract A cold, dry arctic air mass occupied southeastern Canada and the northeastern United States on 13–14 January 2004. This air mass was quite dry—total column precipitable water values at Pickle Lake, Ontario, Canada, and The Pas, Manitoba, Canada, were as low as 0.02 in. (0.5 mm)—allowing significant amounts of radiation originating from the surface to be detected using Geostationary Operational Environmental Satellite (GOES) 6.5-μm “water vapor channel” imagery. On this day the strong thermal gradient between the very cold snow-covered land surface in southern Canada and the warmer, unfrozen, cloud-free water along the northern portion of the Great Lakes was quite evident in GOES-12 imager water vapor channel data. Several hours later, as the cold dry air mass moved eastward, the coast of Maine, Cape Cod, and the Saint Lawrence River were also apparent in the water vapor channel imagery.

APA, Harvard, Vancouver, ISO, and other styles

50

Garrett, Alfred J., Robert J. Kurzeja, Eliel Villa-Aleman, James S. Bollinger, and Malcolm M. Pendergast. "Remote Measurement of Heat Flux from Power Plant Cooling Lakes." Journal of Applied Meteorology and Climatology 52, no. 6 (June 2013): 1366–78. http://dx.doi.org/10.1175/jamc-d-12-0158.1.

Full text

Abstract:

AbstractLaboratory experiments have demonstrated a correlation between the rate of heat loss q″ from an experimental fluid to the air above and the standard deviation σ of the thermal variability in images of the fluid surface. These experimental results imply that q″ can be derived directly from thermal imagery by computing σ. This paper analyses thermal imagery collected over two power plant cooling lakes to determine if the same relationship exists. Turbulent boundary layer theory predicts a linear relationship between q″ and σ when both forced (wind driven) and free (buoyancy driven) convection are present. Datasets derived from ground- and helicopter-based imagery collections had correlation coefficients between σ and q″ of 0.45 and 0.76, respectively. Values of q″ computed from a function of σ and friction velocity u* derived from turbulent boundary layer theory had higher correlations with measured values of q″ (0.84 and 0.89). This research may be applicable to the problem of calculating losses of heat from the ocean to the atmosphere during high-latitude cold-air outbreaks because it does not require the information typically needed to compute sensible, evaporative, and thermal radiation energy losses to the atmosphere.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Thermal imagery'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles