scholarly journals Thermal Sensor Calibration for Unmanned Aerial Systems Using an External Heated Shutter

Drones ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 119
Author(s):  
Jacob Virtue ◽  
Darren Turner ◽  
Guy Williams ◽  
Stephanie Zeliadt ◽  
Matthew McCabe ◽  
...  
Keyword(s):  
Thermal Infrared ◽  
Field Trials ◽  
Sensor Calibration ◽  
Unmanned Aerial Systems ◽  
Thermal Sensor ◽  
Infrared Sensors ◽  
Calibration Source ◽  
Blackbody Source ◽  
Temperature Ranges ◽  
Aerial Systems

Uncooled thermal infrared sensors are increasingly being deployed on unmanned aerial systems (UAS) for agriculture, forestry, wildlife surveys, and surveillance. The acquisition of thermal data requires accurate and uniform testing of equipment to ensure precise temperature measurements. We modified an uncooled thermal infrared sensor, specifically designed for UAS remote sensing, with a proprietary external heated shutter as a calibration source. The performance of the modified thermal sensor and a standard thermal sensor (i.e., without a heated shutter) was compared under both field and temperature modulated laboratory conditions. During laboratory trials with a blackbody source at 35 °C over a 150 min testing period, the modified and unmodified thermal sensor produced temperature ranges of 34.3–35.6 °C and 33.5–36.4 °C, respectively. A laboratory experiment also included the simulation of flight conditions by introducing airflow over the thermal sensor at a rate of 4 m/s. With the blackbody source held at a constant temperature of 25 °C, the introduction of 2 min air flow resulted in a ’shock cooling’ event in both the modified and unmodified sensors, oscillating between 19–30 °C and -15–65 °C, respectively. Following the initial ‘shock cooling’ event, the modified and unmodified thermal sensor oscillated between 22–27 °C and 5–45 °C, respectively. During field trials conducted over a pine plantation, the modified thermal sensor also outperformed the unmodified sensor in a side-by-side comparison. We found that the use of a mounted heated shutter improved thermal measurements, producing more consistent accurate temperature data for thermal mapping projects.

Thermal Infrared Polarimetric Sensor for Automated Detection of Oil Spills

2017 ◽  
Vol 2017 (1) ◽  
pp. 2017402
Author(s):  
David B. Chenault ◽  
Justin P. Vaden ◽  
Douglas A. Mitchell ◽  
Erik D. Demicco
Keyword(s):  
Early Detection ◽  
Oil Spill ◽  
Oil Spills ◽  
Detection System ◽  
Thermal Infrared ◽  
Automated Detection ◽  
Unmanned Aerial Systems ◽  
Detection Approach ◽  
Thermal Cameras ◽  
Aerial Systems

One of the most effective ways of minimizing oil spill impact is early detection. Effective early detection requires automated detection that relies as little as possible on an operator and can operate 24/7. A new and innovative optical detection system exploits the polarization of light, the same physics used to reduce glare through the use of polarized glasses but in the thermal infrared (TIR) portion of the optical spectrum. Measuring the polarization of thermally emitted radiation from an oil spill enhances the detection over conventional thermal cameras and has the potential to provide automated day / night monitoring and surveillance. The sensors developed thus far are relatively small and inexpensive and can be easily mounted in areas that need monitoring and installed in unmanned aerial systems (UAS). Since the sensor is adapted from a conventional TIR camera, thermal imagery as currently used is collected in addition to the polarimetric imagery to further improve the detection performance. Lens options enable wide area coverage at shorter ranges and higher resolution at longer ranges from the camera position. A TIR Polarimetric camera was tested at Ohmsett to establish performance under a variety of conditions. The Polarimetric camera was tested during the day and at night, under several different wave conditions generated in the wave tank, and with oil of different compositions and thicknesses. The imagery collected was analyzed to establish the contrast improvement through the polarimetric properties of the oil and to assess the automation of the detection process. In this poster, the sensor and test setup will be briefly described with detailed description of the results and the potential of this detection approach for automated detection.

scholarly journals Unmanned aerial system–assisted wilderness search and rescue mission

2019 ◽  
Vol 15 (6) ◽  
pp. 155014771985071 ◽  
Author(s):  
Truong Duy Dinh ◽  
Rustam Pirmagomedov ◽  
Van Dai Pham ◽  
Aram A Ahmed ◽  
Ruslan Kirichek ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Access Point ◽  
Search And Rescue ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Infrared Sensors ◽  
Rescue Mission ◽  
Time Required ◽  
The Cost ◽  
Aerial Systems

The success of the wilderness search and rescue missions is highly dependent on the time required to search for the lost person. The use of unmanned aerial systems may enhance search and rescue missions by supplying aerial support of the search process. There are unmanned aerial system–based solutions, which are capable of detecting the lost person using computer vision, infrared sensors, and detection of a mobile phone signal. The most pressing issue is reducing the cost of a search and rescue mission. Thus, to improve the efficiency of the resource utilization in wilderness search scenario, we consider the use of unmanned aerial system for both mobile phone detection and enabling Wi-Fi communication for the ground portion of the search and rescue team. Such an approach does not require specific additional tools (e.g. access point, specific user equipment) for communication, which reduces the cost and improves the scalability and coordination of the search and rescue mission. As a result, the article provides methods of searching the wilderness for a person using beacon signals from a mobile phone for two situations: when the distance to the source of emergency signals is unknown and when the distance is known. In addition, the voice transmission delay and the number of unmanned aircrafts are found to guaranty the quality of a call.

Remote Quantification of Land Surface Temperature and Evapotranspiration Using Thermal Infrared Observations from Unmanned Aerial Systems

2020 ◽  
Author(s):  
Darren Drewry ◽  
Debsunder Dutta ◽  
Kaniska Mallick ◽  
William Johnson ◽  
Roland Brockers
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Field Experiments ◽  
Full Range ◽  
Thermal Infrared ◽  
Absolute Temperature ◽  
Field Conditions ◽  
Unmanned Aerial Systems ◽  
Aerial Systems

<p>Thermal infrared (TIR) remote sensing has a wide array of applications in the environmental sciences, but such applications often require absolute temperature estimates with a high degree of accuracy. Low cost microbolometer-based imaging sensors present a possible alternative for such applications, being lightweight enough for deployment on small Unmanned Aerial Systems (UASs), and thus potentially opening up a new range of applications requiring high spatial or temporal resolution and flexible flight planning. These sensors however lack temperature stabilization of the imaging focal plane array (FPA), prohibiting the reliable retrieval of absolute temperature. Here we present a radiometric calibration methodology developed in laboratory settings using a temperature-controlled chamber and programmable blackbody, allowing for independent control of sensor and target temperatures. These laboratory data provided the basis for linear calibration equations that account for both mean and non-uniformity corrections of the FPA raw radiance counts, as a function of ambient sensor operating temperature. Multiple independent experimental trials were used to extensively validate the algorithm in the laboratory, demonstrating a retrieval error of less than 1 degree Celsius. The calibration methodology was tested under realistic field conditions during a two-day field campaign that utilized ground-based observations of land surface temperature (LST) for both a collection of ground targets with a range of reflectance / emissivity properties, and agricultural plots in Northern California. These field experiments included the deployment of the uncooled microbolometer imaging sensor on a UAS, with acquisitions made throughout a highly variable diurnal period. These UAS experiments demonstrated the effectiveness of the pre-flight calibration methodology under field conditions with excellent agreement between retrieved LST and ground-based infrared thermometers for both homogeneous tarps (R^2 = 0.95) and heterogeneous vegetation plots (R^2 = 0.69 across all crop types), with the full range of target temperatures spanning approximately 15-60 degrees Celsius throughout the campaign. The prediction error for absolute temperature estimates of field targets was found to be within 1 degree Celsius, within the range considered acceptable for many vegetation monitoring applications. We further present results of the application of these UAS-based remote measurements of LST to quantify evapotranspiration (ET) for multiple crop systems. UAS flights were conducted over wheat, soybean and maize fields throughout diurnal periods during the growing season of each crop. LST observations were integrated into the Surface Temperature Initiated Closure (STIC) biophysical evapotranspiration model to estimate ET. Validation against eddy covariance system estimates of evapotranspiration (latent energy flux) shows high predictive accuracy (R^2 > 0.95).</p>

scholarly journals Assessing Radiometric Correction Approaches for Multi-Spectral UAS Imagery for Horticultural Applications

2018 ◽  
Vol 10 (11) ◽  
pp. 1684 ◽  
Author(s):  
Yu-Hsuan Tu ◽  
Stuart Phinn ◽  
Kasper Johansen ◽  
Andrew Robson
Keyword(s):  
Sensor Calibration ◽  
Unmanned Aerial Systems ◽  
Surface Reflectance ◽  
Radiometric Correction ◽  
Crop Monitoring ◽  
Horticultural Crops ◽  
Industry Standard ◽  
Multi Temporal ◽  
Aerial Systems ◽  
Bidirectional Reflectance Distribution

Multi-spectral imagery captured from unmanned aerial systems (UAS) is becoming increasingly popular for the improved monitoring and managing of various horticultural crops. However, for UAS-based data to be used as an industry standard for assessing tree structure and condition as well as production parameters, it is imperative that the appropriate data collection and pre-processing protocols are established to enable multi-temporal comparison. There are several UAS-based radiometric correction methods commonly used for precision agricultural purposes. However, their relative accuracies have not been assessed for data acquired in complex horticultural environments. This study assessed the variations in estimated surface reflectance values of different radiometric corrections applied to multi-spectral UAS imagery acquired in both avocado and banana orchards. We found that inaccurate calibration panel measurements, inaccurate signal-to-reflectance conversion, and high variation in geometry between illumination, surface, and sensor viewing produced significant radiometric variations in at-surface reflectance estimates. Potential solutions to address these limitations included appropriate panel deployment, site-specific sensor calibration, and appropriate bidirectional reflectance distribution function (BRDF) correction. Future UAS-based horticultural crop monitoring can benefit from the proposed solutions to radiometric corrections to ensure they are using comparable image-based maps of multi-temporal biophysical properties.

scholarly journals Using Thermal Infrared Cameras to Detect Avian Chicks at Various Distances and Vegetative Coverages

2020 ◽  
Vol 11 (1) ◽  
pp. 245-257
Author(s):  
Diann J. Prosser ◽  
Tom Collier ◽  
Jeffery D. Sullivan ◽  
Katherine E. Dale ◽  
Carl R. Callahan ◽  
...  
Keyword(s):  
Threshold Value ◽  
Thermal Infrared ◽  
Common Tern ◽  
Alternative Methods ◽  
Controlled Study ◽  
Unmanned Aerial Systems ◽  
Maximum Height ◽  
Threshold Values ◽  
Infrared Cameras ◽  
Aerial Systems

Abstract Population monitoring of nesting waterbirds often involves frequent entries into the colony, but alternative methods such as local remotely sensed thermal imaging may help reduce disturbance while providing a cost-effective way to survey breeding populations. Such an approach can have high initial costs, however, which may have reduced the number of studies investigating functionality of paired thermal infrared camera and small unmanned aerial systems. Here, we take the first step of exploring the ability of two thermal infrared cameras to detect an avian chick under varying vegetative cover and distances, preceding field-mounting applications on a small unmanned aerial system. We created seven “bioboxes” to simulate a range of natural vegetation types and densities for a globally important colonial ground-nesting waterbird species, the common tern Sterna hirundo. We placed a juvenile chicken Gallus gallus (surrogate for the locally endangered common tern) in each box, and we tested two market-accessible infrared cameras (produced by FLIR Systems and Infrared Cameras, Inc.) at five elevations using a stationary boom (maximum height = 12 m). We applied computer-based digital thresholding to collected images, identifying pixels meeting one of seven threshold values. The chick was visible from at least one threshold value in 19 and 31 of 35 processed by the FLIR Systems and Infrared Cameras, respectively. Percentage of the chick identified across thresholds was generally highest at lower threshold values and elevations and decreased as elevation and threshold increased; however, the relative importance of each variable changed dramatically across bioboxes and camera types. Ability to detect a chick from processed images generally decreased with increasing elevation, and although we made no quantitative comparisons among boxes, detectability appeared greatest in images from both cameras when little or no vegetation was present. Interestingly, no single threshold value was best for all bioboxes. We observed notable differences between cameras including visual resolution of detected temperature differentials and image processing speed. Results of this controlled study show promise for the use of thermal infrared systems for detecting cryptic species in vegetation. Future research should work to combine thermal infrared and visual sensors with small unmanned aerial systems to test applicability in a mobile field application.

LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

2019 ◽  
Vol 3 ◽  
pp. 1255
Author(s):  
Ahmad Salahuddin Mohd Harithuddin ◽  
Mohd Fazri Sedan ◽  
Syaril Azrad Md Ali ◽  
Shattri Mansor ◽  
Hamid Reza Jifroudi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Management ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Border Control ◽  
Aerial Vehicles ◽  
Operational Safety ◽  
In Situ Methods ◽  
Aerial Systems

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.

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