Normalized Method for Land Surface Temperature Monitoring on Coastal Reclaimed Areas

Mohamadi, Bahaa; Chen, Shuisen; Balz, Timo; Gulshad, Khansa; McClure, Stephen C.

doi:10.3390/s19224836

Cited by 12 publications

(5 citation statements)

References 35 publications

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“…There are different methods and algorithms for extracting LST from the TIR band (Jiménez-Muñoz et al, 2014;Sattari and Hashim, 2014;Mohamadi et al, 2019;Hulley et al, 2019;Dousset et al, 2019;Weng, 2019;Vlassova et al, 2014;Soleimani Vosta Kolaei and Akhoondzadeh, 2018). This procedure is based on the inversion of the Planck's law and the brightness temperature obtained from the atmospheric radiance from the TIR band sensor (Mathew et al, 2016).…”

Section: Techniques and Methodologymentioning

confidence: 99%

Spatial effect of anti-COVID measures on land surface temperature (LST) in urban areas: A case study of a medium-sized city

Kovács¹,

Haidu²

2022

Időjárás

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This case study investigates the magnitude and nature of the spatial effect generated by the anti-COVID measures on land surface temperature (LST) in the city of Târgu Mureș (Marosvásárhely), Romania. The measures were taken by the Romanian government during the state of emergency (March 16 – May 14, 2020) due to the SARS-CoV-2 coronavirus pandemic. The study shows that – contrary to previous studies carried out on cities in China and India – in most of the urban areas of Marosvásárhely LST has increased in the period of health emergency in 2020 concerning the large average of the years 2000–2019. Remote sensing data from the MODIS and the Landsat satellites show, that MODIS data, having a moderate spatial (approximately 1 km) but good temporal resolution (daily measurements), show a temperature increase of +0.78 °C, while Landsat data, having better spatial (30 m) but lower temporal resolution, show an even greater increase, +2.36 °C in the built-up areas. The difference in temperature increase is mainly due to the spatial resolution difference between the two TIR band sensors. The LST anomaly analysis performed with MODIS data also shows a positive anomaly increase of 1 °C. However, despite this increase, with the help of the hotspot-coldspot analysis of the Getis-Ord Gi* statistic we were able to identify 46 significant coldspots that showed a 1–2 °C decrease of LST in April 2020 compared to the average of the previous years in April. Most of these coldspots correspond to factory areas, public transport epicenters, shopping centers, industrial polygons, and non-residential areas. This shows that anti-COVID measures in the medium-sized city of Marosvásárhely had many effects on LST in particular areas that have links to the local economy, trade, and transport. Paired sample t-test for areas identified with LST decrease shows that there is a statistically significant difference in the average LST observed before and after anti-COVID measures were applied. MODIS-based LST is satisfactory for recognizing patterns and trends at large or moderate geographical scales. However, for a hotspot-coldspot analysis of the urban heat islands, it is more suitable to use Landsat data.

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Section: Techniques and Methodologymentioning

confidence: 99%

Spatial effect of anti-COVID measures on land surface temperature (LST) in urban areas: A case study of a medium-sized city

Kovács¹,

Haidu²

2022

Időjárás

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“…T‐based validation arguably offers the most high‐quality validation available; however, it is problematic because of the difficulties of conducting in situ LST measurements and of obtaining representative reference LST at the scale of a pixel co‐located with the satellite footprint (Mohamadi et al., 2019). Accurate in situ LST measurements are often challenging to obtain because they heavily rely on measurement instruments and procedures.…”

Section: Validation Of Lst Productsmentioning

confidence: 99%

Satellite Remote Sensing of Global Land Surface Temperature: Definition, Methods, Products, and Applications

Duan

et al. 2023

Reviews of Geophysics

215

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Land surface temperature (LST) is a crucial parameter that reflects land-atmosphere interaction and has thus attracted wide interest from geoscientists. Owing to the rapid development of Earth observation technologies, remotely sensed LST is playing an increasingly essential role in various fields. This review aims to summarize the progress in LST estimation algorithms and accelerate its further applications. Thus, we briefly review the most-used thermal infrared (TIR) LST estimation algorithms. More importantly, this review provides a comprehensive collection of the widely used TIR-based LST products and offers important insights into the uncertainties in these products with respect to different land cover conditions via a systematic intercomparison analysis of several representative products. In addition to the discussion on product accuracy, we address problems related to the spatial discontinuity, spatiotemporal incomparability, and short time span of current LST products by introducing the most effective methods. With the aim of overcoming these challenges in available LST products, much progress has been made in developing spatiotemporal seamless LST data, which significantly promotes the successful applications of these products in the field of surface evapotranspiration and soil moisture estimation, agriculture drought monitoring, thermal environment monitoring, thermal anomaly monitoring, and climate change. Overall, this review encompasses the most recent advances in TIR-based LST and the state-of-the-art of applications of LST products at various spatial and temporal scales, identifies critical further research needs and directions to advance and optimize retrieval methods, and promotes the application of LST to improve the understanding of surface thermal dynamics and exchanges.Plain Language Summary Land surface temperature (LST) is a crucial geophysical parameter related to surface energy and water balance of the land-atmosphere system. Satellite remote sensing provides the best way to measure LST and generate various LST products at regional and global scales. In this review, to facilitate the application of LST products in different fields, we first present the physical meaning of satellite-derived LST. Subsequently, we summarize recent advances in LST retrieval and validation methods, with a special focus on the state-of-the-art product collections, product accuracies and intercomparisons, and main problems in current LST products as well as their possible solutions. Additionally, we also review the major applications of LST products in agricultural drought monitoring, thermal environment monitoring, thermal anomaly monitoring, and climate change. Finally, we offer recommendations or perspectives to promote LST retrieval methods and their applications. This review will aid the user in gaining a thorough comprehensive understanding of satellite-derived LST products and promoting their appropriate applications. LI ET AL.

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“…The first attempts to obtain data from passive sensors were performed in the 1990s, i.e., compared to thermal sensors, there are limitations of historical and coverage areas [76][77][78].…”

Section: Passive Microwave Sensorsmentioning

confidence: 99%

Study of the Urban Heat Island (UHI) Using Remote Sensing Data/Techniques: A Systematic Review

2021

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Urban Heat Islands (UHI) consist of the occurrence of higher temperatures in urbanized areas when compared to rural areas. During the warmer seasons, this effect can lead to thermal discomfort, higher energy consumption, and aggravated pollution effects. The application of Remote Sensing (RS) data/techniques using thermal sensors onboard satellites, drones, or aircraft, allow for the estimation of Land Surface Temperature (LST). This article presents a systematic review of publications in Scopus and Web of Science (WOS) on UHI analysis using RS data/techniques and LST, from 2000 to 2020. The selection of articles considered keywords, title, abstract, and when deemed necessary, the full text. The process was conducted by two independent researchers and 579 articles, published in English, were selected. Qualitative and quantitative analyses were performed. Cfa climate areas are the most represented, as the Northern Hemisphere concentrates the most studied areas, especially in Asia (69.94%); Landsat products were the most applied to estimates LST (68.39%) and LULC (55.96%); ArcGIS (30.74%) was most used software for data treatment, and correlation (38.69%) was the most applied statistic technique. There is an increasing number of publications, especially from 2016, and the transversality of UHI studies corroborates the relevance of this topic.

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Normalized Method for Land Surface Temperature Monitoring on Coastal Reclaimed Areas

Cited by 12 publications

References 35 publications

Spatial effect of anti-COVID measures on land surface temperature (LST) in urban areas: A case study of a medium-sized city

Spatial effect of anti-COVID measures on land surface temperature (LST) in urban areas: A case study of a medium-sized city

Satellite Remote Sensing of Global Land Surface Temperature: Definition, Methods, Products, and Applications

Study of the Urban Heat Island (UHI) Using Remote Sensing Data/Techniques: A Systematic Review

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