TY - JOUR
T1 - A new Global Navigation Satellite System (GNSS) based method for urban heat island intensity monitoring
AU - Mendez-Astudillo, Jorge
AU - Lau, Lawrence
AU - Tang, Yu-Ting
AU - Moore, Terry
N1 - Funding Information:
This work was supported by financial support from the International Doctoral Innovation Centre , Ningbo Education Bureau , Ningbo Science and Technology Bureau , and the University of Nottingham . This work was also supported by the UK Engineering and Physical Sciences Research Council [grant number [ EP/L015463/1 ]. We would like to thank two anonymous reviewers whose comments and suggestions were of great value for this contribution.
Publisher Copyright:
© 2020 The Author(s)
PY - 2021/2
Y1 - 2021/2
N2 - The Urban Heat Island (UHI) effect occurs when an urban area experiences higher temperatures than its rural surrounding because of heat being absorbed by built structures and heat being released by anthropogenic sources. UHIs can cause adverse effects to human health and increase energy consumption used for cooling buildings. Therefore, it is important to monitor accurately the UHI effect. The intensity of UHIs are usually monitored using satellite imagery, airborne sensors, and surface temperature sensors. Satellite imagery can cover a large area but requires a clear sky to obtain good images. Moreover, airborne sensors are expensive and also require a clear sky to obtain good data. A large network of surface temperature sensors is required to monitor the UHI of an entire region, which can also be expensive. In this paper, we present a three-step algorithm to monitor UHI intensity using data from Global Navigation Satellite Systems (GNSS). The advantages of using GNSS data to monitor the UHI effect are the increased availability of observation data, high temporal resolution and high geographical resolution. The first step of the algorithm is the calculation of a priori environmental parameters (i.e., water vapour partial pressure, troposphere height, surface pressure, and the vertical profile of refractivity) from radiosonde data. The second step is the calculation of temperature from GNSS data. The last step is the UHI intensity computation. The algorithm presented in this paper has been tested and validated using publicly available GNSS and meteorological data from Los Angeles, California, USA. The validation of the algorithm is done by comparing the UHI intensity estimated from the algorithm with temperature data obtained from weather stations. In the validation, the proposed algorithm can achieve an accuracy of 1.71 °C at 95 % confidence level.
AB - The Urban Heat Island (UHI) effect occurs when an urban area experiences higher temperatures than its rural surrounding because of heat being absorbed by built structures and heat being released by anthropogenic sources. UHIs can cause adverse effects to human health and increase energy consumption used for cooling buildings. Therefore, it is important to monitor accurately the UHI effect. The intensity of UHIs are usually monitored using satellite imagery, airborne sensors, and surface temperature sensors. Satellite imagery can cover a large area but requires a clear sky to obtain good images. Moreover, airborne sensors are expensive and also require a clear sky to obtain good data. A large network of surface temperature sensors is required to monitor the UHI of an entire region, which can also be expensive. In this paper, we present a three-step algorithm to monitor UHI intensity using data from Global Navigation Satellite Systems (GNSS). The advantages of using GNSS data to monitor the UHI effect are the increased availability of observation data, high temporal resolution and high geographical resolution. The first step of the algorithm is the calculation of a priori environmental parameters (i.e., water vapour partial pressure, troposphere height, surface pressure, and the vertical profile of refractivity) from radiosonde data. The second step is the calculation of temperature from GNSS data. The last step is the UHI intensity computation. The algorithm presented in this paper has been tested and validated using publicly available GNSS and meteorological data from Los Angeles, California, USA. The validation of the algorithm is done by comparing the UHI intensity estimated from the algorithm with temperature data obtained from weather stations. In the validation, the proposed algorithm can achieve an accuracy of 1.71 °C at 95 % confidence level.
KW - Urban heat island
KW - GNSS
KW - GNSS remote sensing
KW - Zenith tropospheric delay
UR - http://www.scopus.com/inward/record.url?scp=85117229282&partnerID=8YFLogxK
U2 - 10.1016/j.jag.2020.102222
DO - 10.1016/j.jag.2020.102222
M3 - Journal article
SN - 0303-2434
VL - 94
JO - International Journal of Applied Earth Observation and Geoinformation
JF - International Journal of Applied Earth Observation and Geoinformation
M1 - 102222
ER -