Article
Engineering, Electrical & Electronic
Long Liang, Jing Li, Yunhao Chen, Haiping Xia, Qiang Chen
Summary: The study introduces an auto-adjusted kernel (AAK) method in thermal sharpening, aiming to address the issue of selecting suitable kernels for different windows in OWS and LWS. Experimental results show that the AAK method generally outperforms the FK method, significantly improving accuracy at various downscaling ratios, enhancing accuracy in specific areas, and reducing extreme-value points.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Lu Jiang, Wenfeng Zhan, Leiqiu Hu, Fan Huang, Falu Hong, Zihan Liu, Jiameng Lai, Chenguang Wang
Summary: This study systematically evaluated three single-kernel and eight dual-kernel parametric models for adjusting satellite-derived urban land surface temperatures. The dual-kernel models generally performed better, with those containing the hotspot kernel KHotspot_rou showing higher accuracy. The multi-kernel models sometimes had better accuracies but limited performance improvements compared to single- and dual-kernel models.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Geography, Physical
Pan Dong, Wenfeng Zhan, Chenguang Wang, Sida Jiang, Huilin Du, Zihan Liu, Yangyi Chen, Long Li, Shasha Wang, Yingying Ji
Summary: This study proposes a simple and effective downscaling algorithm, named Simple and Effective Downscaling (SED), which integrates kernel-based and fusion-based methods to downscale MODIS LST using a single adjacent Landsat image. The SED algorithm outperforms four benchmark algorithms in terms of accuracy and global applicability in 50 different study areas worldwide. Particularly, it achieves higher accuracies in tropical and temperate regions, urban areas, and savannas, as well as when using Landsat images closer to MODIS LST. The SED algorithm contributes to the generation of high-quality and high spatiotemporal resolution LST over global lands.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Huazhong Ren, Xin Ye, Jing Nie, Jinjie Meng, Wenjie Fan, Qiming Qin, Yanzhen Liang, Hongcheng Liu
Summary: A novel feature-band linear-format hybrid (FebLihy) algorithm combining deep neural network (DNN) model and physical model was proposed for simultaneous retrieval of atmospheric parameters, land surface temperature (LST), and emissivity from thermal hyperspectral remote sensing data. The algorithm showed promising results in terms of accuracy and effectiveness in both simulation and real data experiments. Future studies will focus on further optimizing the model and data for improved performance.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Biao Cao, Jean-Louis Roujean, Jean-Philippe Gastellu-Etchegorry, Qinhuo Liu, Yongming Du, Jean-Pierre Lagouarde, Huaguo Huange, Hua Li, Zunjian Bian, Tian Hu, Boxiong Qin, Xueting Ran, Qing Xiao
Summary: A new general framework of TIR kernel-driven modeling has been proposed in this study with four specific 4-parameter models, which have shown significant improvement in mimicking the patterns of the directional brightness temperature for both continuous and discrete vegetation canopies compared to the existing three-parameter models.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Xiaopo Zheng, Zhao-Liang Li, Tianxing Wang, Huabing Huang, Francoise Nerry
Summary: In this study, the SW-TES method was extended for global application and comprehensively evaluated, showing that it can be used to accurately retrieve LST with some limitations under certain conditions.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Dandan Wang, Yunhao Chen, Leiqiu Hu, James A. Voogt, Xiaoyu He
Summary: Remotely sensed land surface temperature (LST) is widely used in urban climate research, but it is subject to considerable angular variation due to non-isothermal facades and sensor viewing angles. This study modified and validated a satellite-based approach to estimate thermal anisotropy and compared the seasonal and diurnal variations in 25 global cities. The results show that urban thermal anisotropy is influenced by sensor angles, solar angles, urban surface properties, and geographic location. The findings provide insights for addressing anisotropy in satellite products and understanding its impact on LST applications in cities.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Dandan Wang, Yunhao Chen, Leiqiu Hu, James A. Voogt, Jean-Philippe Gastellu-Etchegorry, E. Scott Krayenhoff
Summary: Satellite observation of land surface temperature in urban areas is influenced by the three-dimensional structure, making it challenging to accurately characterize urban thermal anisotropy. This study compares airborne observations and MODIS LST signals to investigate seasonal and diurnal patterns of thermal anisotropy, providing insights into modeling methods for assessing urban thermal environments in the future.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Geochemistry & Geophysics
Xueting Ran, Biao Cao, Boxiong Qin, Zunjian Bian, Yongming Du, Hua Li, Qing Xiao, Qinhuo Liu
Summary: The fitting ability of five kernel-driven models for angular correction of land surface temperature with limited observation angles was studied, providing insights for model selection in applications.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Han Wang, Kebiao Mao, Zijin Yuan, Jiancheng Shi, Mengmeng Cao, Zhihao Qin, Sibo Duan, Bohui Tang
Summary: A novel land surface temperature retrieval method, MDK-DL, is proposed based on model-data-knowledge-driven and deep learning. The method optimizes band combination and data analysis to improve retrieval accuracy.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Yingzuo Qin, Yan Li, Ru Xu, Chengcheng Hou, Alona Armstrong, Eviatar Bach, Yang Wang, Bojie Fu
Summary: This study used satellite data to quantify the impacts of wind farms on local climate and vegetation in the United States. The results showed significant warming of nighttime land surface temperature (LST) due to wind farms, while daytime impacts were insignificant. Infrastructure construction led to a decrease in vegetation index around wind farms. The size and distance of wind farms played a role in their impacts.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Geochemistry & Geophysics
Yao Xiao, Wei Zhao, Mingguo Ma, Wenping Yu, Lei Fan, Yajun Huang, Xupeng Sun, Qing Lang
Summary: LST retrieval based on TIR remote sensing suffers from spatial discontinuities due to clouds. This study proposed an integrated method using Terra/MODIS and CLDAS LST to reconstruct cloudy LSTs. The method was separated into two parts: a random forest reconstruction method was used for days with high clear-sky pixel ratio, while CLDAS LST was used for the rest of the days. The proposed method showed good potential in generating gap-free LST dataset, especially for mountainous regions with heavy clouds.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Remote Sensing
Cheolhee Yoo, Jungho Im, Dongjin Cho, Yeonsu Lee, Dukwon Bae, Panagiotis Sismanidis
Summary: This study proposes a new approach to downscale 1 km MODIS nighttime LST to higher resolution using local linear regression. The method shows high accuracy and spatial correlation in the empirical study conducted in three cities.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Geography, Physical
Ziwei Wang, Ji Zhou, Jin Ma, Yong Wang, Shaomin Liu, Lirong Ding, Wenbin Tang, Nuradili Pakezhamu, Lingxuan Meng
Summary: A method called DRAT is proposed in this paper to remove temperature drift and temporal variation of a thermal infrared imager mounted on an unmanned aerial vehicle. Test results show that the method significantly improves the visual effect of the images and obtains more reasonable temperature distribution.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Shumin Wang, Youming Luo, Mengyao Li, Kaixiang Yang, Qiang Liu, Xiuhong Li
Summary: This study analyzes the scale effect in the process of land surface temperature (LST) downscaling and proposes a new algorithm based on Taylor expansion. The algorithm improves the downscaled results compared to traditional methods. However, it may introduce temporal discrepancy in some cases.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Yihang She, Zihan Liu, Wenfeng Zhan, Jiameng Lai, Fan Huang
Summary: This study investigated the day-to-day variations of Surface Urban Heat Island (SUHI) intensity (SUHII) in over 10,000 cities worldwide, and found that meteorological variables related to thermal admittance have a larger regulation on SUHII variations than those related to air conditions. The study also found that the impact of meteorological factors on SUHII variations differs greatly by background climates, with specific humidity having a significant control in arid zones and wind speed being weakened prominently in equatorial zones. Furthermore, precipitation was observed to mitigate SUHII variations globally, particularly in equatorial and arid zones.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Geosciences, Multidisciplinary
Zihan Liu, Jiameng Lai, Wenfeng Zhan, Benjamin Bechtel, James Voogt, Jinling Quan, Leiqiu Hu, Peng Fu, Fan Huang, Long Li, Zheng Guo, Jiufeng Li
Summary: The reduction in human activities during lockdown has led to a significant decline in urban heat islands.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Construction & Building Technology
Pan Dong, Sida Jiang, Wenfeng Zhan, Chunli Wang, Shiqi Miao, Huilin Du, Jiufeng Li, Shasha Wang, Lu Jiang
Summary: Investigated the diurnally continuous dynamics of surface urban heat island intensities (SUHIIs) of various local climate zones (LCZs) in Nanjing, China, and discovered some patterns.
BUILDING AND ENVIRONMENT
(2022)
Article
Construction & Building Technology
Jike Chen, Wenfeng Zhan, Peijun Du, Long Li, Jiufeng Li, Zihan Liu, Fan Huang, Jiameng Lai, Junshi Xia
Summary: This study investigated the seasonal differences in the impacts of 2D and 3D building and tree morphologies on land surface temperature (LST). The results showed that the percent cover of buildings predominantly influenced LST in spring and summer, while the sky view factor had a greater impact in autumn and winter. The study also found that the overall impacts of 2D and 3D building structures on LST were mainly direct, with the indirect impacts originating from tree structures.
BUILDING AND ENVIRONMENT
(2022)
Article
Geography, Physical
Zihan Liu, Wenfeng Zhan, Jiameng Lai, Benjamin Bechtel, Xuhui Lee, Falu Hong, Long Li, Fan Huang, Jiufeng Li
Summary: Understanding the dynamics of urban heat islands (UHI) at different time scales is crucial for comprehending their variations. This study reveals that UHI dynamics exhibit various patterns and are influenced by both climate and land cover types. These findings contribute to a deeper understanding of UHI dynamics.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Construction & Building Technology
Lu Jiang, Wenfeng Zhan, Lili Tu, Pan Dong, Shasha Wang, Long Li, Chunli Wang, Chenguang Wang
Summary: This study designed a straightforward and efficient protocol to obtain quasi-synchronous multi-angle urban surface temperature (UST) data using a lightweight unmanned aerial vehicle (UAV). The results showed that the thermal anisotropy (UTA) intensity during the day and night corresponds well with air temperature variations. Additionally, the study found that nighttime temperature variations are dependent on viewing zenith and azimuth angles, and a slight hotspot effect was identified. These findings provide valuable insights for a better understanding of diurnal UTA variations and validating UTA models.
BUILDING AND ENVIRONMENT
(2022)
Article
Construction & Building Technology
Shasha Wang, Wenfeng Zhan, Huilin Du, Chenguang Wang, Long Li, Sida Jiang, Huyan Fu, Shiqi Miao, Fan Huang
Summary: This study investigates the future thermal comfort analogs of 352 cities in China under different emission scenarios, and reveals significant spatial differentiation and shifts in analogs with time and increased anthropogenic emissions, providing insights into future climate change and heat-related health risks.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Construction & Building Technology
Shiqi Miao, Wenfeng Zhan, Jiameng Lai, Long Li, Huilin Du, Chenguang Wang, Chunli Wang, Jiufeng Li, Fan Huang, Zihan Liu, Pan Dong
Summary: This study used MODIS land surface temperature data to investigate the responsiveness of surface urban heat islands (SUHIs) to heat waves (HWs) in 354 cities in seven climate zones across China. It was found that during HW periods, the SUHI and surface urban cool island are augmented in the humid and arid regions of China, respectively. With the intensification of HWs, this augmentation effect can be further enhanced in certain climate zones.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Geosciences, Multidisciplinary
Wenfeng Zhan, Zihan Liu, Benjamin Bechtel, Jiufeng Li, Jiameng Lai, Huyan Fu, Long Li, Fan Huang, Chunli Wang, Yangyi Chen
Summary: Research on 31 Chinese capitals shows that there is a decrease in urban heat island intensity (UHII) during the Chinese New Year period. The reduction in UHII is more significant at night and in northern subtropical and warm temperate climates.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Meteorology & Atmospheric Sciences
Chunli Wang, Wenfeng Zhan, Xue Liu, Zihan Liu, Shiqi Miao, Huilin Du, Jiufeng Li, Chenguang Wang, Long Li, Wenze Yue
Summary: The study found that the UHI weekend effect in Beijing varies with season and time, with stronger intensity in winter compared to summer. The difference in UHI intensity is strongly influenced by anthropogenic heat flux (AHF), urban morphology, and weather conditions.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2022)
Article
Construction & Building Technology
Lei Ma, Guoan Huang, Brian Alan Johnson, Zhenjie Chen, Manchun Li, Ziyun Yan, Wenfeng Zhan, Heng Lu, Weiqiang He, Dongjie Lian
Summary: Assessing heat-related health risks is crucial for sustainable urban development. This study proposes an LCZ-based risk assessment approach and generates an LCZ map of Changzhou city using data and machine-learning techniques. The results show that LCZ 6 (open low-rise) would benefit more from heat hazard mitigation and climate adaptation strategies.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Environmental Studies
Yangyi Chen, Wenfeng Zhan, Zihan Liu, Pan Dong, Huyan Fu, Shiqi Miao, Yingying Ji, Lu Jiang, Sida Jiang
Summary: An improved ATC model (ATC_GL) is proposed, which combines global and local interpolations to generate land surface temperature (LST) products with higher accuracy. The ATC_GL model outperforms other LST reconstruction methods in terms of accuracy and sensitivity to data gaps and overcast conditions.
Article
Environmental Sciences
Long Li, Wenfeng Zhan, Weimin Ju, Josep Penuelas, Zaichun Zhu, Shushi Peng, Xiaolin Zhu, Zihan Liu, Yuyu Zhou, Jiufeng Li, Jiameng Lai, Fan Huang, Gaofei Yin, Yongshuo Fu, Manchun Li, Chao Yu
Summary: Urban vegetation is influenced by complex urban environments. The study reveals that greenness trends decrease from urban cores to urban new towns, and brownish trends are observed in urban fringes. These results highlight the joint influence of biogeochemical drivers and land-cover changes on the urban-rural gradient in vegetation trends, providing insights into future global vegetation change.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Zihan Liu, Wenfeng Zhan, Benjamin Bechtel, James Voogt, Jiameng Lai, Tirthankar Chakraborty, Zhi-Hua Wang, Manchun Li, Fan Huang, Xuhui Lee
Summary: The rate of surface warming in cities exceeds that in rural areas, but urban greening can partly offset enhanced urban warming that is driven by climate change and urban expansion. Based on the analysis of satellite land surface temperature data, it is found that warming trends in cities are influenced by both climate processes and urbanization. The average surface warming trend in the urban core of city clusters worldwide is higher than that in rural background, and background climate change is the largest contributor. In city clusters in China and India, urban expansion also plays a significant role. Additionally, evidence of urban greening in some European cities is found, which helps mitigate background surface warming.
COMMUNICATIONS EARTH & ENVIRONMENT
(2022)
Article
Geosciences, Multidisciplinary
Falu Hong, Wenfeng Zhan, Frank-M. Gottsche, Zihan Liu, Pan Dong, Huyan Fu, Fan Huang, Xiaodong Zhang
Summary: This study proposes an improved framework based on the annual and diurnal temperature cycle to generate global spatiotemporally seamless daily mean land surface temperature (LST) products. The framework significantly reduces the systematic sampling bias and shows good accuracy in validation. This research is important for various applications such as global and regional climate change analysis.
EARTH SYSTEM SCIENCE DATA
(2022)