Article
Geosciences, Multidisciplinary
Zhigang Cao, Ming Shen, Tiit Kutser, Miao Liu, Tianci Qi, Jinge Ma, Ronghua Ma, Hongtao Duan
Summary: This study comprehensively evaluated the performance of MODIS R_land products in global inland and coastal waters and found that it overestimates reflectance and cannot accurately estimate chlorophyll-a and suspended particulate matter. Machine learning models showed good performance in estimating suspended particulate matter but unreliable in estimating chlorophyll-a.
EARTH-SCIENCE REVIEWS
(2022)
Article
Environmental Sciences
Jianwei Wei, Menghua Wang, Karlis Mikelsons, Lide Jiang, Susanne Kratzer, Zhongping Lee, Tim Moore, Heidi M. Sosik, Dimitry Van der Zande
Summary: This study reports a new water class product for global waters from VIIRS, which divides the ocean, coastal, and inland waters into 23 water classes using a hyperspectral scheme. The results show that these water classes are distinguishable by their distinct bio-optical and biogeochemical properties, and the accuracy of the water class products is validated globally.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Pedro Henrique M. Ananias, Rogerio G. Negri, Mauricio A. Dias, Erivaldo A. Silva, Wallace Casaca
Summary: This paper introduces a fully automated framework for algal bloom prediction in inland water bodies, which utilizes machine learning and remotely sensed image data to build anomaly detection models. Through experimental tests, it was found that combining this framework with the random forest model achieved the best algal bloom predictions. Case studies were conducted to demonstrate the effectiveness and flexibility of this learning approach.
Article
Environmental Sciences
Ilias Agathangelidis, Constantinos Cartalis, Anastasios Polydoros, Thaleia Mavrakou, Kostas Philippopoulos
Summary: This study examines heatwave events in the Mediterranean region using surface temperature data and satellite remote sensing technology. The results demonstrate that remotely sensed land surface temperature can effectively indicate heatwave events, with a higher correlation to extremely hot days and long-duration heatwaves.
Article
Geochemistry & Geophysics
Dan Zhao, Lian Feng, Kun Sun
Summary: The study proposes a practical Atmospheric Correction algorithm for inland and nearshore coastal waters (ACLANC), which uses interpolated aerosol optical depth products from nearby land surfaces and simulates aerosol reflectance spectrum. ACLANC outperforms existing atmospheric correction algorithms in accuracy and data coverage, providing high accuracy and wide coverage of remote-sensing reflectance for global inland and nearshore coastal waters.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Rejane S. Paulino, Vitor S. Martins, Evlyn M. L. M. Novo, Claudio C. F. Barbosa, Lino A. S. de Carvalho, Felipe N. Begliomini
Summary: This research used a physical-based approach with three empirical methods to correct and characterize the adjacency effects in Sentinel-2 images over Brazilian inland waters. The importance of determining the H-Adj parameter for low water reflectance values was highlighted, and the importance of adjacency correction under high aerosol loading and extremely dark, low-reflectance waters was emphasized.
Article
Geosciences, Multidisciplinary
Alexandre Castagna, Luz Amadei Martinez, Margarita Bogorad, Ilse Daveloose, Renaat Dasseville, Heidi Melita Dierssen, Matthew Beck, Jonas Mortelmans, Heloise Lavigne, Ana Dogliotti, David Doxaran, Kevin Ruddick, Wim Vyverman, Koen Sabbe
Summary: An extensive sampling campaign was conducted in Belgian waters from 2017 to 2019 to provide paired data of optical and biogeochemical properties for optical monitoring research. The campaign focused on inland waters, including lakes and a coastal lagoon, and also covered the Scheldt estuary and Belgian coastal zone. The measured parameters included optical properties, biogeochemical properties, and water body diversity and conditions. The dataset is available for further research.
EARTH SYSTEM SCIENCE DATA
(2022)
Article
Engineering, Environmental
Shuyuan Wei, Emilio Berti, Diting Ma, Qiqian Wu, Yan Peng, Chaoxiang Yuan, Zemin Zhao, Xia Jin, Xiangyin Ni, Fuzhong Wu, Kai Yue
Summary: This study assessed the spatial distribution and drivers of lead (Pb) concentration in inland waters worldwide by analyzing 1790 observations collected from 386 independent publications. The results showed that Pb concentration in inland waters was mainly driven by potential evapotranspiration, elevation, road density, and absolute latitude.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Multidisciplinary Sciences
Shenglei Wang, Junsheng Li, Wenzhi Zhang, Chang Cao, Fangfang Zhang, Qian Shen, Xianfeng Zhang, Bing Zhang
Summary: This paper provides the first time series Forel-Ule Index dataset for large global lakes from 2000-2018 based on MODIS observations, which could be valuable for studies investigating the drivers and interaction mechanisms of lake colour change.
Article
Geography, Physical
Yuchao Zhang, Kun Shi, Zhen Cao, Lai Lai, Jianping Geng, Kuiting Yu, Pengfei Zhan, Zhaomin Liu
Summary: This study found that lower temporal resolutions in satellite data can result in inaccurate derivation of phytoplankton bloom trends and can also affect the response of phytoplankton blooms to climatic factors.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Agronomy
Juwon Kong, Youngryel Ryu, Yan Huang, Benjamin Dechant, Rasmus Houborg, Kaiyu Guan, Xiaolin Zhu
Summary: Satellite image fusion methods can improve spatial and temporal resolution for understanding ecosystem dynamics. Evaluation of four state-of-the-art image fusion NDVI products showed strong linear relationships with in situ data, with larger performance differences in spatial variation than in temporal variation.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Review
Medicine, Research & Experimental
Sabeeha Ali, Manzar Alam, Fatima Khatoon, Urooj Fatima, Abdelbaset Mohamed Elasbali, Mohd Adnan, Asimul Islam, Md. Imtaiyaz Hassan, Mejdi Snoussi, Vincenzo De Feo
Summary: The unexpected emergence of COVID-19 has had a significant impact on the global population, emphasizing the need for effective preventive and therapeutic measures. Natural compounds have been found to possess antiviral properties and have gained interest in developing drugs against SARS-CoV-2. This study investigates the antiviral potential of selected natural products and provides mechanistic insights. Consumption of certain natural products can enhance immune response and show excellent therapeutic potential.
BIOMEDICINE & PHARMACOTHERAPY
(2022)
Review
Oncology
Jiahuan Dong, Yufan Qian, Guangtao Zhang, Lu Lu, Shengan Zhang, Guang Ji, Aiguang Zhao, Hanchen Xu
Summary: Colorectal cancer is a common cancer that poses a threat to human health. Immunotherapy is widely used in cancer treatment, but most colorectal cancer patients are not responsive to it. Therefore, developing an effective combination therapy is a goal in cancer research. Natural products, with their diverse immunomodulatory effects, have the potential to be used in comprehensive cancer treatment options.
FRONTIERS IN ONCOLOGY
(2022)
Article
Environmental Sciences
Iuliia Burdun, Ain Kull, Martin Maddison, Gert Veber, Oleksandr Karasov, Valentina Sagris, Ulo Mander
Summary: This study explored the potential of using remotely sensed land surface temperature (LST) to monitor ecosystem respiration (R-eco) in disturbed peatlands, finding that in disturbed sites, in situ temperatures were a stronger driver of CO2 fluxes and LST had a higher association with in situ measured temperatures.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2021)
Article
Engineering, Civil
Jiafeng Xu, Ying Zhao, Heng Lyu, Huaiqing Liu, Xianzhang Dong, Yunmei Li, Kai Cao, Jie Xu, Yangyang Li, Huaijing Wang, Honglei Guo
Summary: In this study, an optimal optical indicator for estimating Chla/TSM was found and a semianalytical algorithm was proposed. The algorithm showed favorable performance in inland waters and had higher estimation accuracy compared to other algorithms.
JOURNAL OF HYDROLOGY
(2022)
Article
Geography, Physical
Xuehui Pi, Lian Feng, Weifeng Li, Junguo Liu, Xingxing Kuang, Kun Shi, Wei Qi, Deliang Chen, Jing Tang
Summary: This study provided a comprehensive investigation of temporal-spatial variations in Chl-a concentrations in 82 lakes across the Tibetan Plateau region. The results revealed that lakes with high Chl-a concentrations were mainly concentrated in the eastern, southern, and northeastern parts of the Tibetan Plateau.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2021)
Article
Engineering, Civil
Qu Zhou, Jianru Wang, Liqiao Tian, Lian Feng, Jian Li, Qianguo Xing
Summary: The study analyzes water turbidity data in Wuhan and finds that climatic conditions affect seasonal variations in turbidity, while human factors have long-term impacts on it. Careful consideration of human activities during urbanization is required to strike a balance between water quality protection and urban development.
JOURNAL OF HYDROLOGY
(2021)
Letter
Multidisciplinary Sciences
Lian Feng, Yanhui Dai, Xuejiao Hou, Yang Xu, Junguo Liu, Chunmiao Zheng
Article
Oceanography
Jun Wang, Yan Tong, Lian Feng, Dan Zhao, Chunmiao Zheng, Jing Tang
Summary: By analyzing data collected from two field surveys in the Pearl River Estuary of China, this study found that water turbidity is significantly decreasing at a rate of 0.11 nephelometric turbidity units (NTU) per year. This decline is linked to sea-level rise and the retreat of estuarine turbidity maxima (ETMs), both effects resulting from similar processes such as urbanization. Furthermore, a high correlation between water turbidity and salinity was observed, which could facilitate monitoring of saltwater intrusions in the region.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2021)
Article
Geography, Physical
Xin Jiang, Shijing Liang, Xinyue He, Alan D. Ziegler, Peirong Lin, Ming Pan, Dashan Wang, Junyu Zou, Dalei Hao, Ganquan Mao, Yelu Zeng, Jie Yin, Lian Feng, Chiyuan Miao, Eric F. Wood, Zhenzhong Zeng
Summary: The study introduces a segmentation algorithm integrating SAR satellite imagery with unsupervised machine learning approach (Felz-CNN) for automatic flood mapping. The algorithm demonstrated high accuracy in mapping flood inundation during the 2020 Yangtze River flood, producing large-scale maps of affected areas within minutes. This efficient method provides crucial support for global disaster governance and mitigation efforts.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Yanhui Dai, Lian Feng, Xuejiao Hou, Jing Tang
Summary: An automatic SAV classification algorithm using Landsat imagery was developed in this study, with automatically determined thresholds for key parameters. The algorithm showed high accuracy in classifying SAV in Yangtze Plain lakes and obtaining long-term SAV areal data. It is insensitive to Chl-a concentration in the water column, but has a detection limit below the water surface.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Chemistry, Analytical
Jing Shi, Chuanmin Hu
Summary: The study evaluates the quality of thermal data collected by ECOSTRESS over South Florida estuaries, Chesapeake Bay, and Lake Okeechobee, finding a slight underestimation of sea surface temperature which can be corrected for evaluating thermal environments of small water bodies.
Article
Geosciences, Multidisciplinary
Xuejiao Hou, Lian Feng, Yanhui Dai, Chuanmin Hu, Luke Gibson, Jing Tang, Zhongping Lee, Ying Wang, Xiaobin Cai, Junguo Liu, Yi Zheng, Chunmiao Zheng
Summary: Algal blooms, an emerging threat to global inland water quality, are occurring more frequently, especially in developing countries in Asia and Africa where agricultural fertilizer is heavily used. The establishment of a global bloom database is crucial for future risk assessments and mitigation efforts.
Article
Astronomy & Astrophysics
Wei Qi, Junguo Liu, Hong Yang, Deliang Chen, Lian Feng
Summary: GLDAS2.0 provides important hydrometeorological data sets for water-related studies in transboundary rivers. This work assessed the data and developed approaches to correct their uncertainties in the Tibetan Plateau and Northeast China. The findings showed that the GLDAS2.0 data can reasonably simulate seasonal variations, but specific humidity, wind speed, and summer precipitation have large uncertainties. The corrected data improved the performance in hydrological simulations, demonstrating the usefulness of the methodology for transboundary river studies.
EARTH AND SPACE SCIENCE
(2022)
Correction
Multidisciplinary Sciences
Xuehui Pi, Qiuqi Luo, Lian Feng, Yang Xu, Jing Tang, Xiuyu Liang, Enze Ma, Ran Cheng, Rasmus Fensholt, Martin Brandt, Xiaobin Cai, Luke Gibson, Junguo Liu, Chunmiao Zheng, Weifeng Li, Brett A. Bryan
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Xuehui Pi, Qiuqi Luo, Lian Feng, Yang Xu, Jing Tang, Xiuyu Liang, Enze Ma, Ran Cheng, Rasmus Fensholt, Martin Brandt, Xiaobin Cai, Luke Gibson, Junguo Liu, Chunmiao Zheng, Weifeng Li, Brett A. Bryan
Summary: Lakes are important natural resources and sources of carbon emissions, and they are undergoing rapid changes worldwide in response to climate change and human activities. Through a global characterization of lakes, we found that lake area has increased over the past four decades, with a significant contribution from reservoirs. Although small lakes account for a small percentage of the global lake area, they have a significant impact on the variability of total lake size. The increase in lake area has led to higher carbon emissions, with small lakes playing a major role.
NATURE COMMUNICATIONS
(2022)
Article
Environmental Sciences
Kelsey E. Roberts, Lance P. Garrison, Joel Ortega-Ortiz, Chuanmin Hu, Yingjun Zhang, Christopher R. Sasso, Margaret Lamont, Kristen M. Hart
Summary: The lack of baseline data for marine turtles in the Gulf of Mexico, especially after the Deepwater Horizon oil spill in 2010, has been highlighted. In this study, we analyzed dive and spatial data from satellite tags attached to threatened or endangered marine turtles over a period of 10 years. By examining environmental factors such as depth, salinity, and frontal features, we found that these factors are associated with the time marine turtles spend at the surface. This research contributes to a better understanding of turtle density and abundance estimates.
Article
Environmental Sciences
Lian Feng, Xuehui Pi, Qiuqi Luo, Weifeng Li
Summary: This study proposes an improved algorithm for monitoring inland water bodies using remote sensing images. The algorithm addresses the issue of missing data caused by clouds and other adverse conditions, and achieves high accuracy in recovering contaminated pixels. The algorithm improves the temporal coverage of the water area time series and provides valuable data for further analysis of lake dynamics.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Remote Sensing
Yan Tong, Lian Feng, Dan Zhao, Wang Xu, Chunmiao Zheng
Summary: This study fills the gap in the comprehensive characterization of chlorophyll-alpha (Chl-alpha) in the Greater Bay Area (GBA) of China by utilizing long-term satellite observations. A novel hybrid Chl-alpha retrieval algorithm is developed to accurately monitor Chl-alpha content in the coastal oceans, revealing different trends in different regions. This research is of great significance for further coastal conservation and management efforts.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Remote Sensing
Charles-Robin Gruel, Edward Park, Adam D. Switzer, Sonu Kumar, Sameh Kantoush, Lian Feng, Huu Loc Ho, Doan Van Binh
Summary: This study provides the first systematic estimation of the sand mining budget in the Mekong Delta based on field surveys. It introduces a new approach for monitoring and quantifying sand mining activities that is essential for future projections on environmental impacts.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)