Article
Environmental Sciences
Yunlin Zhang, Lei Zhou, Yongqiang Zhou, Liuqing Zhang, Xiaolong Yao, Kun Shi, Erik Jeppesen, Qian Yu, Weining Zhu
Summary: Chromophoric dissolved organic matter (CDOM) is crucial in the biogeochemical cycle of aquatic ecosystems. Recent studies have focused on characterizing CDOM, mapping its distribution through remote sensing, and investigating the biogeochemical processes involved. Watershed-related processes play a key role in CDOM dynamics, with photochemical degradation and microbial decomposition being significant removal mechanisms.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Fisheries
Liangliang Shi, Zhihua Mao, Yiwei Zhang
Summary: A novel approach was developed to analytically retrieve the absorption coefficient of chromophoric dissolved organic matter in non-turbid waters, based on NASA Bio-Optical Marine Algorithm Dataset and in situ datasets. The algorithm performed well in retrieving a(CDOM), with mean R-2 and mean absolute percentage error values of 0.84 and 42.8%, respectively, compared to other models tested. Additionally, the algorithm was successful in retrieving a(CDOM) from MERIS satellite data, which can be used to explore biogeochemical effects on aquatic environments.
MARINE AND FRESHWATER RESEARCH
(2021)
Article
Environmental Sciences
Wen-Zhuo Zhu, Shu-Heng Wang, De-Zhong Wang, Wei-Hua Feng, Bo Li, Hong-Hai Zhang
Summary: This study investigated the photodegradation behavior of chromophoric dissolved organic matter (CDOM) from different sources under different light treatments. The results showed that UVB had a direct degradation effect on allochthonous CDOM, while UVA had a stronger degradation effect on autochthonous CDOM. The photochemical processes of CDOM can significantly impact its biogeochemical cycle in marine environments.
Article
Computer Science, Information Systems
Jie Zhan, Dianjun Zhang, Lifeng Tan, Guangyun Zhang, Robert Zupan
Summary: In this study, three versions of the Quasi-Analytical Algorithm (QAA) were compared for their performance in seawater component concentration determination. The results showed that QAA_V4 model performed the best for absorption coefficient inversion at 443 nm, while QAA_V6 showed the highest accuracy at 555 nm and 670 nm wavelengths. The QAA model demonstrated high accuracy and robust applicability for absorption coefficient inversion at shorter wavelengths, indicating its potential for ocean color remote sensing research.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Review
Oceanography
Toru Hirawake, Joji Oida, Youhei Yamashita, Hisatomo Waga, Hiroto Abe, Jun Nishioka, Daiki Nomura, Hiromichi Ueno, Atsushi Ooki
Summary: The study demonstrates that water mass classification using CDOM parameters is effective in complex coastal sea areas such as the northern Bering Sea and southern Chukchi Sea.
PROGRESS IN OCEANOGRAPHY
(2021)
Article
Environmental Sciences
Daniel S. F. Jorge, Hubert Loisel, Cedric Jamet, David Dessailly, Julien Demaria, Annick Bricaud, Stephane Maritorena, Xiaodong Zhang, David Antoine, Tiit Kutser, Simon Belanger, Vittorio O. Brando, Jeremy Werdell, Ewa Kwiatkowska, Antoine Mangin, Odile Fanton D'Andon
Summary: A three-step inverse model (3SAA) was presented for estimating the inherent optical properties (IOPs) of surface waters from remote sensing reflectance spectra. The model showed good performance in oceanic waters with small degradation in bio-optical complex inland waters. The performance of 3SAA was evaluated through in situ dataset and comparisons with other standard semi-analytical algorithms.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Xiao Sun, Yunlin Zhang, Yibo Zhang, Kun Shi, Yongqiang Zhou, Na Li
Summary: The study developed a robust CDOM estimation model using different machine learning algorithms, with Gaussian process regression showing higher stability and accuracy compared to other models such as backpropagation neural network, random forest regression, and support vector regression. These models achieved more than 70% accuracy for CDOM absorption coefficient estimation, with better performance in eutrophic lakes. Machine learning algorithms have great potential for CDOM monitoring in inland waters based on large datasets.
Article
Environmental Sciences
Ganghui Tong, Xueling Yang, Yun Li, Meng Jin, Xubiao Yu, Ying Huang, Rongyue Zheng, Jun-Jian Wang, Huan Chen
Summary: Sunlight plays a significant role in water ecosystems, but the widespread air pollutant, haze, affects the photochemical transformation of dissolved organic matter (CDOM). This study conducted an experiment in a city in China frequently affected by haze pollution and found that haze reduced the intensity of UV light and decreased the loss of dissolved organic carbon. The study also observed that haze influenced the bleaching of CDOM, and UV intensity played a critical role in the composition characteristics of CDOM. Therefore, long-term and large-scale haze may adversely impact water ecosystems through pollutant/nutrient accumulation.
ENVIRONMENTAL RESEARCH
(2022)
Article
Environmental Sciences
Nittala S. Sarma, G. Chiranjeevulu, Sudarsana Rao Pandi, Dokala Bhaskara Rao, V. V. S. S. Sarma
Summary: This study investigates the coupling between Chromophoric Dissolved Organic Matter (CDOM) and Dissolved Inorganic Carbon (DIC) in eighteen Indian estuaries. The study reveals a significant linear relationship between DIC, CDOM abundance, and pH level in most estuaries, with some estuaries showing elevated DIC levels and other indicators suggesting anthropogenic influence. CDOM properties, such as spectral slope and spectral slope ratio, align with these findings. The study also finds that CDOM contributes different proportions of DIC in different estuaries, indicating its importance in the organic alkalinity of estuaries.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Ruosha Zeng, Chris M. Mannaerts, Caroline Lievens
Summary: UV-VIS spectral analysis methods were used to quantify CDOM absorption properties. Spectroscopic parameters were evaluated for their correlation with H/C and O/C ratios, and S275-295 showed the strongest correlation with H/C ratio, while S-R and E-4/E-6 showed strong correlation with O/C ratio. Gaussian fitting was suitable for single CDOM components, while derivative analysis could be used for single-component discrimination.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2023)
Article
Environmental Sciences
Yihao Huang, Jiayi Pan, Adam T. Devlin
Summary: In this study, machine learning algorithms were used to retrieve CDOM data from Landsat-8 OLI observations in the Pearl River estuary. The XGBoost algorithm performed best, with an R-2 value of 0.9 and the lowest CDOM root mean square error of 0.37 m(-1), outperforming empirical algorithms. Tides and winds were identified as the primary driving forces behind the spatial and temporal variability of CDOM in the estuary.
Article
Environmental Sciences
Aobo Ju, Hu Wang, Lequan Wang, Yuang Weng
Summary: In this study, machine learning models (BPNN, RF, and XGBoost) were used to predict the CDOM ultraviolet absorption spectra between 215 and 350 nm based on the raw absorption spectra of seawater. The results showed that all three models were able to effectively predict the CDOM absorption spectra, with the XGBoost model performing the best. The predicted spectra were then used to calculate the spectra slopes at shorter wavelengths (S215-240 and S215-275), which were found to be similar to the widely used spectra slopes at longer wavelengths (S275-295).
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Engineering, Civil
Qi Huang, Lizhen Liu, Jiacong Huang, Dianwei Chi, Adam Thomas Devlin, Huawu Wu
Summary: The seasonal dynamics of CDOM and DOC in Poyang Lake are important for understanding biogeochemical processes and water quality. Rivers and wetlands greatly influence the quantity and quality of CDOM. The alternations of flood and dry periods have different effects on CDOM and DOC. Wetlands contribute a higher abundance of CDOM and DOC to the lake with lower aromaticity.
JOURNAL OF HYDROLOGY
(2022)
Article
Engineering, Environmental
Yu Zeng, Qinglong Fu, Dionysios D. Dionysiou, Mingyang Zhang, Mabo Li, Bo Ye, Ning Chen, Juan Gao, Yujun Wang, Dongmei Zhou, Guodong Fang
Summary: This study investigated the photo-transformation of Imidacloprid (IMD) during rice growth and found that the presence of different reactive intermediates (RIs) significantly enhanced the degradation rate of IMD. Evaluation of the photodegradation products of IMD showed that some were harmful to aquatic animals, while others were detoxification processes. A model was developed to predict the photodegradation kinetics of IMD in paddy waters at different stages of rice growth.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Geosciences, Multidisciplinary
Nikita Kaushal, Nivedita Sanwlani, Jani T. I. Tanzil, Nagur Cherukuru, Syamil Sahar, Moritz Mueller, Aazani Mujahid, Jen N. Lee, Nathalie F. Goodkin, Patrick Martin
Summary: Terrigenous dissolved organic matter (tDOM) carried by rivers is an important carbon flux to the coastal ocean, rich in light-absorbent chromophoric dissolved organic matter (CDOM). Luminescence green-to-blue (G/B) ratios in coral cores correlate strongly with remote sensing-derived CDOM absorption, indicating control by rainfall and solar radiation.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
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)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)