Article
Environmental Sciences
Zhonghu Jiao, Xinjian Shan
Summary: This study developed a temporal integrated anomaly (TIA) method to predict pre-seismic anomalies and validated its effectiveness through retrospective testing and synthetic earthquakes. The results highlight the importance of multiparameter anomalies and reveal certain unexplained pre-seismic phenomena.
Article
Environmental Sciences
Kang Liu, Jian Yang, Shengyang Li
Summary: This paper presents a cross-domain dataset for remote-sensing scene classification and evaluates various domain adaptation algorithms on different tasks. The results show that the algorithms can reduce data distribution differences between domains and improve task accuracy to some extent. Furthermore, the dataset also achieves good results in cross-domain data annotation, weakly supervised object detection, and data retrieval.
Article
Geosciences, Multidisciplinary
Inan Ulusoy, Caner Diker, Erdal Sen, H. Evren Cubukcu, Erdal Gumus
Summary: Hasandag is a double-peaked long-dormant volcano with poorly known volcanic risk. Through thermal remote sensing analysis, weak fumaroles and water vapor emissions were observed on the western flank of the volcano. Statistical analysis of long-term temperature data and comparison with meteorological data revealed temporal thermal anomalies. The thermal radiation characteristics and its dependence on the volcano's structure were investigated using thermal remote sensing techniques. It is recommended to establish a permanent ground-based thermal observation station for direct and remote thermal monitoring of the volcano's fumarole zone.
JOURNAL OF VOLCANOLOGY AND GEOTHERMAL RESEARCH
(2022)
Review
Plant Sciences
Martha M. Farella, Joshua B. Fisher, Wenzhe Jiao, Kesondra B. Key, Mallory L. Barnes
Summary: This study emphasizes the untapped potential of remote sensing in plant ecology. Remote sensing in the thermal infrared domain can provide valuable information on plant behavior and stress conditions. It can evaluate plant species, traits, and structure, and offer unique insights into species distribution and phenology under changing climate conditions. Integrated understanding of processes and technology is crucial for scaling leaf traits, canopy structure, and regional patterns. The synergies between thermal remote sensing and other data sources provide a timely opportunity for ecologists to advance their understanding of plant physiology, ecology, and biogeography.
JOURNAL OF ECOLOGY
(2022)
Article
Environmental Sciences
Eberhard Parlow
Summary: This paper highlights the complexity and pitfalls of thermal infrared data analysis in urban heat island studies. Authors often jump into UHI research without fully understanding the phenomenon, leading to incorrect conclusions and results. Proper correction of data, consideration of signal source area, and understanding of radiation and heat fluxes are crucial for accurate UHI studies.
Article
Green & Sustainable Science & Technology
Xiaomin Du, Dongqi Sun, Feng Li, Jing Tong
Summary: This study uses nighttime thermal infrared images and an adaptive-edge-threshold algorithm to extract time-series for underground coal fire areas and proposes a method for analyzing the propagation law of underground coal fires based on the geometric centers of these areas. The results suggest that this method can accurately identify coal fires and represent their propagation direction and intensity variation.
Article
Environmental Sciences
Sankaran Rajendran, Hamad Al Saad Al Kuwari, Fadhil N. Sadooni, Sobhi Nasir, Himanshu Govil, Habes Ghrefat
Summary: The study maps aeolian deposits in part of the Arabian Desert using ASTER data and examines their impact on desertification, land encroachment, and degradation, as well as agricultural development in arid regions. The analysis of sand deposits' emissive spectra revealed triplet absorptions, which were then mapped using ASTER spectral bands. The study of the Abu Samra region in Qatar from 2000 to 2021 using ASTER quartz index (QI) images showed significant changes in desertification and land degradation.
ENVIRONMENTAL RESEARCH
(2023)
Article
Environmental Sciences
Mitchell S. Maguire, Christopher M. U. Neale, Wayne E. Woldt
Summary: Unmanned aerial systems have been increasingly used for remote sensing, with thermal infrared cameras being a common sensor choice. This study compared surface temperature measurements from a UAS thermal camera and field infrared thermometers, finding a RMSE of 2.24 degrees Celsius and a R-2 value of 0.85. Different models were explored for correcting the thermal imagery, with the linear model performing the best with a RMSE of 1.27 degrees Celsius and a R-2 value of 0.93. Additionally, laboratory experiments showed the need for a warm-up period to achieve measurement stability with the thermal camera.
Article
Environmental Sciences
Guibin Hao, Hongbo Su, Renhua Zhang, Jing Tian, Shaohui Chen
Summary: This study proposed an improved method for estimating soil moisture based on fusing land-surface temperature data and utilizing a two-source normalized soil thermal inertia model. The results showed that the proposed method increased the accuracy of temperature prediction and provided a more comprehensive characterization of soil moisture at different depths. It has the potential to support hydrological model simulations and improve agricultural management.
Article
Environmental Sciences
Liyuan Li, Linyi Jiang, Jingwen Zhang, Siqi Wang, Fansheng Chen
Summary: In this paper, a complete YOLO-based ship detection method (CYSDM) for thermal infrared remote sensing images (TIRSIs) under complex backgrounds is proposed. The method utilizes a thermal infrared ship dataset and an improved YOLOv5s model. Test results show that CYSDM achieves a precision of 98.68%, which is 9.07% higher than the YOLOv5s algorithm. CYSDM provides an effective reference for large-scale, all-day ship detection.
Article
Environmental Sciences
Junfang Yang, Yabin Hu, Jie Zhang, Yi Ma, Zhongwei Li, Zongchen Jiang
Summary: This paper designed and implemented two outdoor oil spill simulation experiments, obtained hyperspectral and thermal infrared remote sensing data of different oil spill pollution types, and constructed a hyperspectral recognition algorithm to improve the identification ability of different oil spill pollution types. The combination of hyperspectral and thermal infrared remote sensing can effectively improve the recognition accuracy of different oils, providing important technical support for emergency response to maritime emergencies and oil spill monitoring business.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Construction & Building Technology
Yafei Wu, Yao Shan, Yuanming Lai, Shunhua Zhou
Summary: By rewriting the infrared radiation transmission equation and utilizing multi-source data, a method for retrieving urban land surface temperatures at a block scale is proposed for effective evaluation of micro urban thermal environment. This method can be used for quantitative analysis of urban thermal environment and urban heat island effect at a block scale.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Geosciences, Multidisciplinary
Lin Way, Matthew E. Pritchard, Linden Wike, Kevin Reath, Hendra Gunawan, Oktory Prambada, Devy Syahbana
Summary: Through long-term analysis of satellite thermal infrared data, more volcanic thermal features have been detected in active volcanoes in Indonesia, which is significant for monitoring volcanic activity and eruption precursors.
JOURNAL OF VOLCANOLOGY AND GEOTHERMAL RESEARCH
(2022)
Article
Engineering, Marine
Julian E. Londono-Londono, Maria Teresa Condesso de Melo, Joao N. Nascimento, Ana C. F. Silva
Summary: This study developed a straightforward tool for mapping potential Submarine Groundwater Discharge (SGD) areas in the coastal ecosystems of Portugal using thermal infrared remote sensing. Over 20 potential SGD areas were identified through thermal analysis. This research is significant for understanding the occurrence, importance, and effects of SGD.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)