Article
Environmental Sciences
Yineng Li, Shaotian Li, Shiqiu Peng, Yuhang Zhu, Fenghua Zhou, Shilin Tang
Summary: This study introduces an updated version of the real-time Experimental Platform of Marine Environment Forecasting system for the North Indian Ocean, called EPMEF-NIO. The updates include adding the western Indian Ocean to the regions for weather, surge, and wave forecasts, increasing the horizontal resolutions for the two-domain weather forecast, adding a three-domain-nested wave forecast, and extending the length of the forecast time. The assessment based on substantial observations shows that the EPMEF-NIO performs well in weather, wave, and storm surge forecasts, thanks to the spectacular techniques employed in the system.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Environmental Sciences
Hossein Zare, Tobias K. D. Weber, Joachim Ingwersen, Wolfgang Nowak, Sebastian Gayler, Thilo Streck
Summary: This study proposes a method for early forecasting of winter wheat yields in low-information systems, which integrates satellite and in-situ green leaf area index (LAI) data using a particle filtering method. The results show that assimilating even noisy LAI data substantially improves the accuracy and precision of yield prediction, reducing errors caused by uncertainties in weather data, incomplete knowledge about management, and model calibration uncertainty.
Article
Biodiversity Conservation
Yihao Wang, Chunjiang Zhao, Daming Dong, Kun Wang
Summary: Monitoring animal activities is crucial for assessing the impact of environmental conditions and human activities on different species. Recent developments in entomology-based monitoring methods, such as radar and machine vision, have greatly improved the accuracy and efficiency of data collection. This study focuses on laser-based monitoring methods, which allow real-time observation of insect activity and the study of their responses to environmental changes. We summarize four specific applications of these methods, including electronic trapping, collecting backscattered light or fluorescence, and indirectly monitoring insect populations by analyzing forest canopy characteristics. We also discuss the challenges and opportunities of these methods and highlight future research directions.
ECOLOGICAL INDICATORS
(2023)
Article
Multidisciplinary Sciences
Niels Andela, Douglas C. Morton, Wilfrid Schroeder, Yang Chen, Paulo M. Brando, James T. Randerson
Summary: A near-real-time approach for tracking contributions from different types of fires to burned area and emissions can effectively assess the impacts of fires and improve management outcomes during fire emergencies.
Article
Environmental Sciences
Shuai Zhang, Tamlin M. Pavelsky, Christopher D. Arp, Xiao Yang
Summary: A remote sensing-derived lake ice phenology database covering all lakes in Alaska from 2000 to 2019 was constructed to analyze the trends of earlier breakup and later freezeup of lake ice in the region. The dataset showed significant trends towards earlier or later ice breakup and freezeup for various lakes, with most significant trends observed in lakes north of the Brooks Range. This dataset contributes to the understanding of interactions between lake processes and climate change, supporting research on biogeochemical, limnological, and ecological regimes in Alaska and pan-Arctic regions.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Water Resources
Akhilesh S. Nair, Rohit Mangla, P. Thiruvengadam, J. Indu
Summary: This paper reviews the studies of hydrological data assimilation using Kalman filters and summarizes the recent applications. It also briefly describes the challenges in data assimilation studies and presents three case study examples.
HYDROLOGICAL SCIENCES JOURNAL
(2022)
Article
Environmental Sciences
Huanhuan Zhang, Jidong Gao, Qin Xu, Lingkun Ran
Summary: By sampling perturbed state vectors from each ensemble forecast at additional time levels shifted by +/- t, time-expanded sampling (TES) can effectively sample timing errors and triple the analysis ensemble size for covariance construction without increasing the forecast ensemble size. In this study, TES was applied to the convection-allowing ensemble-based warn-on-forecast system (WoFS) to reduce computational costs in assimilating remote-sensing data and generating short-term severe-weather forecasts. The results showed that TES had little impact on assimilation statistics while reducing costs, and the forecasts produced using TES had similar capability and quality compared to the control experiment.
Article
Environmental Sciences
Shuangling Chen, Yu Meng
Summary: Accurate and robust measurements from ocean color satellites are crucial for studying changes in surface ocean properties. In this study, a locally-tuned chlorophyll algorithm was used to investigate the spatial expansion of phytoplankton blooms in the Ross Sea. The results showed that the blooms were larger than previously estimated and correlated with sea surface temperature, wind speed, and sea ice concentration.
Article
Engineering, Marine
Timothy T. Wynne, Michelle C. Tomlinson, Travis O. Briggs, Sachidananda Mishra, Andrew Meredith, Ronald L. Vogel, Richard P. Stumpf
Summary: This manuscript describes methods for evaluating the efficacy of five satellite-based Chlorophyll-a algorithms in Chesapeake Bay. The results show that a two-band algorithm based on the red-edge portion of the electromagnetic spectrum exhibited the lowest overall error when applied to OLCI imagery.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Environmental Sciences
Ronghao Li, Pengqi Gao, Xiangyuan Cai, Xiaotong Chen, Jiangnan Wei, Yinqian Cheng, Hongying Zhao
Summary: In this paper, a real-time incremental UAV image mosaicking framework is proposed, which only uses the UAV image sequence and does not rely on GPS, CGPs, or other auxiliary information. The framework aims to reduce spatial distortion, increase the speed of the mosaicking process, and output high-quality panorama.
Article
Environmental Sciences
Tebatso M. Moloto, Sandy J. Thomalla, Marie E. Smith, Bettina Martin, Deon C. Louw, Rolf Koppelmann
Summary: In this study, a multispectral remote sensing approach is used to detect dominant phytoplankton groups in the northern Benguela upwelling system. This ocean colour remote sensing algorithm has the potential to map the phenology of phytoplankton groups on unprecedented spatial and temporal scales, advancing our understanding of ecosystems and environmental monitoring.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Remote Sensing
Weicheng Xu, Pengchao Chen, Yilong Zhan, Shengde Chen, Lei Zhang, Yubin Lan
Summary: This study established a cotton yield estimation model based on time series UAV remote sensing data, combined with multispectral images and neural network prediction to achieve large-area and small-scale forecasting of cotton yields, providing a new idea for cotton yield measurement and breeding screening.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Engineering, Environmental
Weijia Wang, Kun Shi, Yibo Zhang, Na Li, Xiao Sun, Dong Zhang, Yunlin Zhang, Boqiang Qin, Guangwei Zhu
Summary: The worldwide expansion of phytoplankton blooms poses a serious threat to water quality, food webs, habitat stability, and human health. To address the need for high-frequency and continuous observations of phytoplankton bloom dynamics, a novel ground-based remote sensing system (GRSS) is proposed. The GRSS successfully captured rapid changes in chlorophyll a concentrations (Chla) in inland waters and demonstrated its potential for high-frequency monitoring of phytoplankton blooms. The random forest regression algorithm achieved the best performance in deriving Chla.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Environmental Sciences
Md Ataullah Raza Khan, Shaktiman Singh, Pratima Pandey, Anshuman Bhardwaj, Sheikh Nawaz Ali, Vasudha Chaturvedi, Prashant Kumar Champati Ray
Summary: This study quantified the distribution of permafrost in the Western Himalaya using multisource satellite datasets, revealing a large portion of barren land and majority of the area with a mean annual air temperature below 1 degree Celsius. The research also showed high interannual variability in permafrost distribution and a significant decrease in permafrost cover from 2002 to 2020.
Article
Environmental Sciences
Soodabeh Namdari, Ali Ibrahim Zghair Alnasrawi, Omid Ghorbanzadeh, Armin Sorooshian, Khalil Valizadeh Kamran, Pedram Ghamisi
Summary: Motivated by the lack of research on land cover and dust activity in the Middle East, this study explores the relationship between vegetation cover and dust emission in the region. The results show that the decrease in vegetation cover is closely related to increased dust intensity. The study also reveals spatial variability in the relationship between Aerosol Optical Depth (AOD) and Normalized Difference Vegetation Index (NDVI) in different time periods.
Article
Engineering, Environmental
Dong Liu, Zhandong Sun, Ming Shen, Liqiao Tian, Shujie Yu, Xintong Jiang, Hongtao Duan
Summary: A new method has been developed to remotely observe the three-dimensional distribution of particulate organic carbon (POC) storage in shallow eutrophic lakes using satellite data. This study is significant for understanding the carbon cycle in such lakes.
Article
Environmental Sciences
Yuanshan Liao, Haijin Lan, Xinyue Zhang, Zhenjing Liu, Mi Zhang, Zhenghua Hu, Hongtao Duan, Qitao Xiao
Summary: Lakes are important sources of atmospheric methane, and the emissions from the river inlet region are less studied. Field measurements at Lake Taihu over six years show that the river inlet region is a hot spot of CH4 emission, with a seven times higher annual mean value compared to the pelagic region. The variability of CH4 emission is linked to pollution loadings and CH4-rich water in the inflowing river.
Article
Environmental Sciences
Xintong Jiang, Dong Liu, Junli Li, Hongtao Duan
Summary: Dissolved organic matter (DOM) plays a vital role in the global lake carbon cycle. This study focused on the changes in DOM components in different lake types based on in situ data from ten lakes in northwestern China. The results showed that human activities and salinity were the main contributors to the variations in DOM concentration and composition in the western arid lakes. The study also proposed a feasible flowchart for remotely estimating DOM in saline lakes using satellite data.
ENVIRONMENTAL RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
Zhigang Cao, John M. M. Melack, Miao Liu, Tiit Kutser, Hongtao Duan, Ronghua Ma
Summary: A study of 2,550 Chinese lakes from 1984 to 2021 revealed that 68% of the lakes experienced a shift towards shorter visual wavelengths in color. Lakes in the Tibetan Plateau showed larger declines in wavelength compared to lakes in other areas. The factors associated with these color shifts varied in different ecoregions, with warmer and wetter climate influencing deep lakes in western China towards a blue color, while increased vegetation and reduced wind influenced shallow lakes in eastern China towards a green-cyan color. This study highlights the heterogeneous controls of climate and human activities on lake color patterns.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Yinguo Qiu, Yaqin Jiao, Juhua Luo, Zhenyu Tan, Linsheng Huang, Jinling Zhao, Qitao Xiao, Hongtao Duan
Summary: This paper proposes a novel rapid reconstruction scheme for water regions in 3D models of oblique photography, which can achieve fast and accurate reconstruction. Experimental results show that this scheme can improve the current UAV oblique photography 3D modeling technique and expand its application in twin watershed, twin city, and other areas.
Article
Engineering, Environmental
Hongtao Duan, Qitao Xiao, Tianci Qi, Cheng Hu, Mi Zhang, Ming Shen, Zhenghua Hu, Wei Wang, Wei Xiao, Yinguo Qiu, Juhua Luo, Xuhui Lee
Summary: This study compares eight machine learning models to predict methane emissions from lakes using satellite remote sensing. The random forest model achieves the best accuracy. The study also finds that climate warming and algal blooms contribute to the long-term increase in methane emissions.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Environmental Sciences
Qitao Xiao, Wei Xiao, Juhua Luo, Yinguo Qiu, Cheng Hu, Mi Zhang, Tianci Qi, Hongtao Duan
Summary: This study investigated the CO2 partial pressure (pCO2) of two urban lakes in eastern China based on 16-year field measurements and found that CO2 emissions from these lakes were significant, with strong links to human-derived nutrients and organic carbon. The study also suggested that management actions, such as ecological restoration and municipal engineering, could help mitigate CO2 emissions in aquatic ecosystems.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Environmental Sciences
Ming Shen, Jiquan Lin, Ying Ye, Yuxiao Ren, Junfu Zhao, Hongtao Duan
Summary: This study utilized satellite remote sensing to quantitatively analyze the spatial and temporal distribution of Secchi disk depth (SDD) in the coastal waters of Hainan Island, China, revealing the impacts of environmental investments on the coastal water environment. The results showed that the water quality in Hainan coastal waters has significantly improved over the past 20 years, but the increasing global oceanic wind speed has counteracted a portion of the effectiveness of remedial management in protecting and restoring the coastal ecosystem.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Engineering, Environmental
Ming Shen, Zhigang Cao, Liqiang Xie, Yanyan Zhao, Tianci Qi, Kaishan Song, Lili Lyu, Dian Wang, Jinge Ma, Hongtao Duan
Summary: Cyanobacterial blooms and the release of algal toxins pose a serious threat to the safety of drinking water sources. However, the monitoring and evaluation of algal toxins in lake water have not been carried out regularly. This study developed a remote sensing scheme based on satellite data to assess the risk of algal toxins and found that most large lakes in eastern China had experienced high risk at least once. Fortunately, the frequency of high human health risks in terms of lake areas was low, indicating the potential to set drinking water intakes in most waters while reducing cyanobacterial blooms.
Article
Remote Sensing
Zhenyu Tan, Chen Yang, Yinguo Qiu, Wei Jia, Chenxi Gao, Hongtao Duan
Summary: This paper proposes a novel machine learning approach that can effectively extract harmful algal blooms (HABs) from images captured under various shooting poses. The approach was applied in Lake Chaohu and consistently reports the real-time status of HABs along the bank.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Spectroscopy
Jiang Xin-tong, Xiao Qi-tao, Li Yi-min, Liao Yuan-shan, Liu Dong, Duan Hong-tao
Summary: Lake Bosten, the largest inland freshwater lake in the northwest arid zone of China, has been heavily impacted by human activities and wastewater discharge, affecting the lake ecosystem and drinking water safety. The study analyzed the three-dimensional fluorescence spectra of coloured dissolved organic matter (CDOM) and found three fractions of CDOM in Lake Bosten. The influence of river input on Lake Bosten's dissolved organic matter (DOM) varied between seasons and correlated with the change in river water quality.
SPECTROSCOPY AND SPECTRAL ANALYSIS
(2023)
Article
Environmental Sciences
Yuanshan Liao, Qitao Xiao, Yimin Li, Chen Yang, Junli Li, Hongtao Duan
Summary: Saline lakes are integral components of the global carbon cycle and play a significant role in greenhouse gas emissions. This study focuses on Bosten Lake, an inland saline lake in China, and reveals that it is a significant source of atmospheric carbon emissions. The emissions are influenced by temporal variations in salinity and trophic state. Additionally, spatial heterogeneity in carbon emissions is driven by exogenous inputs. This study provides valuable insights into greenhouse gas emissions from saline lakes in arid regions and contributes to a better understanding of the carbon cycle in different types of lakes.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Remote Sensing
Zhuting Tan, Zhengyu Tan, Juhua Luo, Hongtao Duan
Summary: This study proposes a new method for cotton sample selection and employs machine learning to effectively identify long time series cotton planting areas at a 30-meter resolution scale. The study uses Bortala and Shuanghe in Xinjiang, China as case studies to demonstrate the approach. The results show that the method can achieve high accuracy and reveal the spatiotemporal distribution characteristics of cotton planting areas.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Article
Biodiversity Conservation
Yinguo Qiu, Hao Liu, Fuzhang Liu, Dexin Li, Chengzhao Liu, Weixin Liu, Jiacong Huang, Qitao Xiao, Juhua Luo, Hongtao Duan
Summary: This study developed a novel framework that can timely and accurately grasp both present conditions and accumulation risks of harmful algal blooms (HABs) in nearshore areas of lakes. By using quantitative monitoring and simulation modeling, the framework showed high value in monitoring and emergency prevention of HABs.
ECOLOGICAL INDICATORS
(2023)
Article
Engineering, Electrical & Electronic
Chen Yang, Zhenyu Tan, Yimin Li, Ming Shen, Hongtao Duan
Summary: This article presents the performance of multiple machine learning (ML) algorithms in detecting algal blooms in Chinese eutrophic inland lakes. The random forest (RF) model stands out among the four tested ML models, achieving an overall accuracy above 0.90. Even with data from a single lake used as training samples, the RF model maintains a fairly high accuracy of 0.88 for other lakes. These ML models show promising potential for algal bloom detection across different lakes and provide practical references for further applications.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)