Elsevier

Urban Climate

Volume 41, January 2022, 101068
Urban Climate

A novel methodology to obtain ambient temperatures using multi-rotor UAV-mounted sensors

https://doi.org/10.1016/j.uclim.2021.101068Get rights and content

Highlights

  • Developed a novel methodology to obtain ambient temperatures using the multi-rotor UAV.

  • Conducted field experiments to figure out the settling time to obtain a stable air temperature.

  • Achieved a 0.3 °C measurement accuracy of obtaining ambient temperatures.

Abstract

Unmanned Aerial Vehicle (UAV)-mounted temperature sensors can collect a large amount of valuable 3-dimensional environmental data, especially at locations unsuitable for the installation of traditional weather stations. This paper developed a novel methodology to obtain accurate ambient temperature data using a multi-rotor UAV. Firstly, air temperature sensors and a multi-rotor UAV model were selected based on the objectives of this study. Secondly, field experiments were conducted to determine the influence of in-flight multi-rotor UAV on ambient temperature, to determine the most appropriate locations for the temperature sensor, namely underneath the multi-rotor UAV center and between the landing gears. The data collection, processing, and analysis methods were thus proposed. Thirdly, the accuracy of the proposed methodology was evaluated at a target height by comparing the measured result with that measured by a nearby weather station, and comparing the vertical profile of measured data with the data released by National Environment Agency (NEA) in Singapore. A satisfactory agreement between the two results was observed with an error of between 0 and 0.3 °C. In addition, a case study was conducted to compare ambient temperatures at various heights above different ground materials utilizing the proposed methodology in a park. Besides, the correlation analysis results provided the directions to improve the measurement accuracy.

Introduction

Nowadays, more than half of the world's population lives in urban areas, and this proportion is estimated to increase to 68% by 2050 (. o. E. a. S. A. Unied Nations, 2019a). According to the World Population Prospects 2019, there will be a rapid influx of migrants from rural to urban areas in the decades to come, and another 2.5 billion population is projected to live in urban areas by 2050, with close to 90% of the increase in Asian and African cities (D. o. E. a. S. A. Unied Nations, 2019b). Although urban development is imperative for economic growth and national development, it also leads to a general deterioration of the urban environment and causes environmental issues, such as the gradually rising urban temperatures (Brennan, 1999). The air temperatures in urban cities are higher than the surrounding rural areas, which is known as Urban Heat Island (UHI) effect (Jusuf et al., 2007; Tan et al., 2010). In urban areas, heatwaves could lead to the outdoor thermal discomfort (Alexandri and Jones, 2008; Pantavou et al., 2011) and excessive energy consumption (de Munck et al., 2013), as well as exacerbate the UHI phenomenon (Tan et al., 2010; Cantat, 2004; Lemonsu et al., 2015).

A comprehensive understanding of the urban microclimate can assist planners, architects and engineers to create a better urban design for thermal comfort (Li et al., 2016) and conduct more accurate building energy simulations. For example, investigating the thermal profile (air temperature distribution) inside the urban canyons along different streets could help urban planners understand how urban morphology configures and affects the microclimatic conditions in a specific area (Dimoudi et al., 2013). Comparing and analyzing the air temperature differences between building indoor environment and its outdoor conditions will help researchers or engineers analyze anthropogenic heat releases and further design effective countermeasures to the UHI effect at the urban microscale (Miguel et al., 2021). In addition, with the height increases, the outdoor air temperature will decrease, which leads to the lower air temperature within the indoor unit at the higher floor (Aflaki et al., 2014). The differences between the weather data at a traditional 1.5 m to 2 m level which are normally used for building energy simulation, and the actual air temperature at the higher floor are significant, especially for high rise and super high-rise buildings. And the differences could affect the accuracy of the simulation results. A case study of high-rise office building energy consumption in Hong Kong indicated that when the temperature increased 1 °C, the total energy consumption would increase 8.0%, while the HVAC energy consumption would increase 11.5% in the summer (Ma and Yu, 2020). Therefore, utilizing the corresponding outdoor air temperatures at different heights as the input of the simulation instead of the traditional weather station data could contribute to the simulation accuracy. Therefore, comprehensive environmental monitoring and effective data collection technologies are required. Among all the affecting meteorological elements, the spatial differentiation of air temperature could be more significant comparing with other elements, such as solar radiation and humidity, especially in urban areas. Additionally, the evaluating criterion of UHI is the air temperature difference between rural and urban areas (Yuan et al., 2020). Therefore, air temperature is selected as the main focus in this study. However, measurement of air temperature is conventionally done by installing weather stations at fixed positions or handheld measurement near the ground or roof, which is inflexible when vertical variations in air temperature or more dense data are required.

There are a variety of traditional technologies and applications for macro-scale meteorological observation. For decades, weather balloons with sensors provide valuable kinematic and thermodynamic data for the weather conditions in the upper atmosphere (Sankar and Norman, 2009). Parasails are used to collect environmental data as well. However, weather balloons and parasails are designed with less maneuverability and can be difficult to control because of their high susceptibility to ambient environmental conditions (Jensen et al., 2007; Inoue et al., 2000). Instrumented towers can measure weather data continually for a long period, but only at a fixed location. Manned aircrafts are used to conduct atmospheric research, measuring air temperature, wind and humidity, atmospheric turbulence for decades (Witte et al., 2017). Nevertheless, the manufacturing cost and operation cost are relatively high (Villa et al., 2016).

Recently, Unmanned Aerial Vehicles (UAVs) have been proven to be the prospective technology in assisting industrial and commercial activities (Mohammed et al., 2014). The technological developments and cost reduction opened up opportunities to conduct three-dimensional environmental monitoring with UAV-based sensors (Dunbabin and Marques, 2012). Compared with the UAV-based data collection methodology, the conventional fixed-point thermometers could merely collect air temperatures near to building facades but were not applicable to the following scenarios, shown in Fig. 1. The red indicated the possible areas that the conventional fixed thermometers could be applied, while the UAV icons indicated the other possible positions that the UAV-based sensors might arrive.

Firstly, high-rise buildings, especially the office buildings in central business district areas, were usually encased in huge curtain walls of glass. It could be hard to open the windows and install the conventional equipment to collect the outside air temperatures. However, the UAV-based sensors could measure the data at each target position and develop the vertical air temperature distribution around the building. Secondly, heritage buildings and ancient villages. Under the consideration of protecting and keeping the original building environment and building structures, it would be better to simply hover the UAV around them to obtain the ambient temperatures for micro-climate research than installing several traditional weather stations. Thirdly, densely built areas of cities. Currently, there have been relevant papers using meteorological towers to collect air temperatures at different heights in the street canyon (Miguel et al., 2021). However, it was inconvenient to set up a meteorological tower at densely populated places. Besides, although the conventional thermometers could be applied for measurement and fixed to the equipment less than 2 m away from the building facades, the measurement of air temperatures between the two neighboring buildings, or for the urban street canyon could be difficult. Fourthly, ecological protection areas, especially over a large dense forest. It could be challenging and costly to set up and maintain a series of weather stations at high levels. The UAV-based sensors could collect the air temperatures at any required height and position without ecological damage to the ground plants. Fifthly, hills or mountains, especially the steep hill. It might be difficult to set up the weather stations among these areas. And it is quite dangerous for manual measurements. Sixthly, the air temperatures above the waterbody, such as rivers, lakes, and seas, were normally measured by infrared thermography or the weather stations on a boat, with height limits. However, the UAV-based sensors could solve these problems and perform as a convenient and cost-effective tool.

UAVs that can obtain the weather data can be classified into three types, fixed-wing UAVs, helicopter UAVs and multi-rotor UAVs, as shown in Fig. 2. Fixed-wing UAVs are widely used to measure the atmospheric state between the convective boundary layer and the stably stratified free atmosphere with remote sensing instruments (Martin et al., 2014; Bonin et al., 2015) and thermodynamic sensors (Wildmann et al., 2015; Cassano et al., 2016; Reineman, 2013), including air temperature, pressure, humidity and wind (Houston et al., 2012; Wildmann et al., 2013). Helicopter UAVs with meteorological sensors can measure the turbulent fluxes in the boundary layer (Buschmann et al., 2004), as well as air temperature and relative humidity (Fan et al., 2017) directly. In addition, helicopter UAVs with multispectral imaging sensors can measure the surface temperatures using remote sensing technology (Berni et al., 2009). As for multi-rotor UAVs, they are used more often for in situ observations in the lower atmosphere. In 2016, Ortega-Farías et al. placed multispectral and infrared thermal cameras on an octocopter to obtain the surface energy balance components and meteorological variables at 6 cm × 6 cm high resolution (Ortega-Farías et al., 2016). In 2019, Dugdale et al. utilized the multi-rotor UAV-based thermal infrared imager to collect the radiant temperature (Dugdale et al., 2019). Matrix quadcopters can also be applied to lift and suspend fiber optic cables of a few dozen kilometers with high spatial and temporal resolutions to measure temperature (Higgins et al., 2018). In addition, multi-rotor UAVs were applied to obtain sensible heat flux (Kim and Kwon, 2019), wind speed and directions (Palomaki et al., 2017) in the atmospheric boundary layer.

Compared with helicopter UAVs and multi-rotor UAVs, fixed-wing UAVs have a relatively high operating velocity and could cover a significantly larger area during the same time interval, as well as more flexible to mount sensors since they do not have propellers or rotors (Ozdemir et al., 2014; Su et al., 2011; Fahlstrom and Gleason, 2012; Wyllie, 2001). However, fixed-wing UAVs are unable to hover at a certain location and require a certain operating height and runways for taking-off and landing, which makes them unsuitable for data collection at a targetted position. The operation of helicopter and multi-rotor UAVs is relatively easier as there is no strict site requirement for taking-off and landing. Additionally, they could hover at the targetted position. However, sensor location requires more considerations to eliminate the impact of propellers and rotors (Villa et al., 2016). Compared with helicopter UAVs, multi-rotor UAVs are more flexible in the accurate operation of hovering, turning around and changing speed. Furthermore, with the popularization of the multi-rotor UAV, its operation cost has become much lower and its flight stability has greatly enhanced, especially in urban areas. Therefore, multi-rotor UAVs were selected to establish the UAV-based outdoor temperature measurement methodology.

Until now, there have been some applications using multi-rotor UAVs equipped with thermal sensors. For example, an International Met Systems iMet-XQ UAV sensor was mounted below one of the rotors of a DJI S1000 octocopter to measure temperature (Bailey et al., 2020). An EMRC Heli's hexacopter with an Anemoment's TriSonica mini wind and weather sensor attached underneath was utilized to obtain real-time atmospheric data, such as air temperature and wind velocity (Gagne, 2020). However, there are two problems with the sensor locations. Firstly, if the sensors are located near the body of the UAV, the strong turbulent airflow generated by the rotating propellers around the UAV will intermix the surrounding air, which can lead to measurement errors. Secondly, sensors mounted furthest underneath the multi-rotor UAV might increase the risk of overbalance during flight under an unstable weather environment and lead to rollover of the multi-rotor UAV during its take-off and landing. In addition, it cannot measure the air temperatures when near the ground.

To fill the gaps, this study developed a safe, flexible and accurate methodology to obtain the ambient temperature at a specific position using a multi-rotor UAV. Firstly, the selection criteria for air temperature sensors and the multi-rotor UAV were proposed, based on the measurement requirements. Secondly, the most appropriate sensor location was determined after testing the influencing distance of in-flight UAV on the ambient temperature. The corresponding data collection and analysis methods were proposed to obtain accurate measurement results. Then, the accuracy of the proposed methodology was evaluated by comparing the measured results with those from a nearby stationary weather station. Furthermore, a case study was conducted to measure the ambient temperatures at different heights above different ground surfaces utilizing the proposed methodology. In the end, some recommendations were proposed to implement this methodology properly as well as improve the measurement accuracy in the future.

Section snippets

Development of methodology

This study developed a methodology to measure the ambient temperature utilizing multi-rotor UAV, and the development process mainly includes two stages as shown in Fig. 3. At the preparation stage, the types of air temperature sensors and the model of the multi-rotor UAV were selected. The accuracy, weight, size and response time of the air temperature sensor, as well as the payload, operation mode and flight stability of the multi-rotor UAV were considered during the selection. At the

Case study - ambient temperature tests under different scenarios

The proposed methodology utilizing the multi-rotor UAV-mounted temperature sensors was applied to conduct a case study measuring ambient temperatures under different scenarios. This case study was also used to prove the feasibility of the proposed methodology that it can obtain similar air temperature values to traditional air temperature collection methods, such as stationary weather stations. The experiment results were analyzed to compare the temperature distribution at different heights

Conclusion and limitations

In this study, a novel methodology to obtain the ambient temperature using a multi-rotor UAV was developed and evaluated. To implement the methodology, the shaded thermocouple with a short response time of 3 s and the multi-rotor UAV model (e.g., DJI m600 pro) were selected after careful consideration. Through the field experiments, the best installation location for the temperature sensors was found to be directly underneath the multi-rotor UAV center, at the same plane of the bottom of the

Author statement

All persons who meet authorship criteria are listed as authors, and all authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing, or revision of the manuscript. Furthermore, each author certifies that this material or similar material has not been and will not be submitted to or published in any other publication before its appearance in the Urban Climate.

Authorship contributions

Conception and design of study: Xu Ruohan, Zhang Wen, Wong Nyuk Hien, Tong Shanshan.

Conduct experiment and acquire data: Xu Ruohan, Zhang Wen, Tong Shanshan, Wu Xinyi.

Analyze data: Xu Ruohan, Zhang Wen.

Draft the manuscript: Xu Ruohan, Zhang Wen.

Review & Edit: Wong Nyuk Hien, Tong Shanshan.

Supervision: Wong Nyuk Hien.

Approval of the version of the manuscript to be published (the names of all authors must be listed): Xu Ruohan, Zhang Wen, Wong Nyuk Hien, Tong Shanshan, Wu Xinyi.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

The authors gratefully acknowledge valuable scientific discussions with Dr. He Yang, Dr. Daniel Hii Jun Chung, Mr. Chen Shisheng, Mr. Song Chao and Ms. Wen Jianxiu from the National University of Singapore and Prof. Zhang Yukun and Prof. Li Zhe from Tianjin University, China. This work was supported by the National Research Foundation Singapore (NRF2018NRF-NSFC003ES-012).

All persons who have made substantial contributions to the work reported in the manuscript, but who do not meet the criteria

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