Article
Multidisciplinary Sciences
Rongjin Yang, Lu Liu, Qiang Liu, Xiuhong Li, Lizeyan Yin, Xuejie Hao, Yushuang Ma, Qiao Song
Summary: Accurate measurement of leaf area index (LAI) is crucial for agricultural analysis and crop yield estimation, which can be obtained through ground station measurement or remote sensing satellite monitoring. Recent progress has been made in long-term automatic LAI observation using wireless sensor networks. The focus has been on improving system algorithms and data validation for more realistic LAI values.
SCIENTIFIC REPORTS
(2022)
Article
Geosciences, Multidisciplinary
Han Ma, Shunlin Liang, Changhao Xiong, Qian Wang, Aolin Jia, Bing Li
Summary: The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical land surface variable for carbon cycle modeling and ecological monitoring. However, current FAPAR products suffer from spatiotemporal inconsistency. Deep learning approaches that utilize temporal information in satellite data can improve the spatiotemporal continuity and accuracy of FAPAR products.
EARTH SYSTEM SCIENCE DATA
(2022)
Article
Remote Sensing
Ilina Kamenova, Petar Dimitrov
Summary: The study evaluated the utility of 40 spectral Vegetation Indices for deriving Leaf Area Index, fraction of Absorbed Photosynthetically Active Radiation, and fraction of vegetation Cover of winter wheat crop. It was found that using all-season models could accurately predict fAPAR and fCover of winter wheat crop, while the accuracy of predicting LAI was lower.
EUROPEAN JOURNAL OF REMOTE SENSING
(2021)
Proceedings Paper
Geosciences, Multidisciplinary
Vikas Dugesar, Prashant K. Srivastava, V. K. Kumra
Summary: The study aims to validate the LAI product derived from Sentinel-2 Level 2 Prototype Processor (SNAP-SL2P) and compare it with ground observations and other global LAI products for consistency.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
(2022)
Article
Geography, Physical
Luke A. Brown, Richard Fernandes, Najib Djamai, Courtney Meier, Nadine Gobron, Harry Morris, Francis Canisius, Gabriele Bai, Christophe Lerebourg, Christian Lanconelli, Marco Clerici, Jadunandan Dash
Summary: The study shows that SL2P performs well in agricultural environments but poorly in heterogeneous canopies like forests. The modified version SL2P-D exhibits reduced bias and higher number of valid retrievals compared to SL2P.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Geosciences, Multidisciplinary
Yongzhe Chen, Xiaoming Feng, Bojie Fu
Summary: The study calibrated and fused 11 microwave remote-sensing soil moisture products since 2003 using a neural network approach, creating a global remote-sensing-based surface soil moisture dataset with a temporal resolution of approximately 10 days, exhibiting superior quality performance.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Geochemistry & Geophysics
Siqi Yang, Naijie Peng, Dechao Zhai, Yunzhu Tao, Qunchao He, Xihan Mu, Yi Li, Wenjie Fan
Summary: In this study, we propose an improved geometry-based method for accurately measuring fisheye-based forest LAI at high spatial resolution. Our method considers average tree height, crown depth, and high-resolution pixel size to enhance accuracy. Experimental results show that our method significantly reduces the root mean square error and achieves better results when using different instruments for measurement.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Engineering, Aerospace
Georgi Jelev, Petar Dimitrov, Eugenia Roumenina
Summary: This paper presents the results of a study that aimed to map the dynamic of biophysical variables of winter wheat crops during different growth stages using multispectral camera data from an Unmanned Aerial Vehicle (UAV). Linear and exponential regression models were used to predict the biophysical variables, and the best predictor was found to be the OSAVI index. The chosen models were then used to create maps of the biophysical variables for the studied fields.
AEROSPACE RESEARCH IN BULGARIA
(2022)
Article
Environmental Sciences
Birgitta Putzenlechner, Philip Marzahn, Philipp Koal, Arturo Sanchez-Azofeifa
Summary: This study investigated the use of remotely sensed FCOVER as a proxy for in situ FAPAR in a dense mixed-coniferous forest. The results showed that UAV-derived FCOVER was close to in situ FAPAR during the peak vegetation period, while the Sentinel-2 FCOVER product underestimated both. The study recommends integrating the spatial variability of UAV-derived FCOVER into quality assessments and using it to benchmark sampling sizes for in situ FAPAR measurements.
Article
Environmental Sciences
Richard Fernandes, Luke Brown, Francis Canisius, Jadu Dash, Liming He, Gang Hong, Lucy Huang, Nhu Quynh Le, Camryn MacDougall, Courtney Meier, Patrick Osei Darko, Hemit Shah, Lynsay Spafford, Lixin Sun
Summary: Canopy biophysical variables such as fCOVER, fAPAR, and LAI are widely used for ecosystem modelling and monitoring. The Sentinel-2 mission aims to map these variables globally using imagery from the MultiSpectral Instrument. However, the Simplified Level 2 Prototype Processor (SL2P) underestimates LAI over forests. This study validates the Sentinel-2 products and provides empirical bias correction functions for each variable.
REMOTE SENSING OF ENVIRONMENT
(2023)
Editorial Material
Biochemistry & Molecular Biology
Lien B. Lai, Venkat Gopalan, Martin D. Jansson, Qi Chen, Xudong Zhang, Maik Wolfram-Schauerte, Katharina Hofer
Summary: This article focuses on the importance of nucleic acids in biochemistry, specifically RNA, and discusses the generation of figures representing their structures. Several authors provide insights into the factors to consider when creating such figures, preferred software, and examples from their own research.
TRENDS IN BIOCHEMICAL SCIENCES
(2023)
Article
Multidisciplinary Sciences
Bowen Song, Liangyun Liu, Shanshan Du, Xiao Zhang, Xidong Chen, Helin Zhang
Summary: This study established a fine-resolution LAI dataset with 80 reference maps to validate the MODIS LAI product. The dataset serves as a bridge connecting small sampling plots with coarse-resolution pixels, significantly improving the validation of coarse-resolution LAI products.
Article
Environmental Sciences
Bernardo Mota, Nadine Gobron, Olivier Morgan, Fabrizio Cappucci, Christian Lanconelli, Monica Robustelli
Summary: A framework was proposed to assess the physical consistency between two terrestrial Essential Climate Variables products retrieved from Earth Observation at a global scale. The study found that CGLS products lacked consistency in spatial and temporal changes, while MCD15A3 products had the highest number of non-coherent changes between the two ECVs. JRC-TIP products showed high consistency in temporal and spatial changes.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Agronomy
Ibrahim Arslan, Mehmet Topakci, Nusret Demir
Summary: The decrease in water resources due to climate change has significant impacts on agriculture. This study used Sentinel-1 and Sentinel-2 satellite images to monitor maize growth, and found that different indicators are sensitive to maize height and planting operations.
Article
Engineering, Electrical & Electronic
Bowen Song, Liangyun Liu, Jingjing Zhao, Xidong Chen, Helin Zhang, Yuan Gao, Xiao Zhang
Summary: The study assessed the accuracy of four global leaf area index (LAI) products over croplands in China, finding that GEOV2 had the highest accuracy compared to the other products. There were uncertainties in different regions, with the products showing overestimation or underestimation. The seasonal variation was minor, but scaling effects led to varying degrees of overestimation or underestimation in different areas.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Tianxiang Cui, Rui Sun, Chen Qiao, Qiang Zhang, Tao Yu, Gang Liu, Zhigang Liu
Article
Environmental Sciences
Tao Yu, Rui Sun, Zhiqiang Xiao, Qiang Zhang, Gang Liu, Tianxiang Cui, Juanmin Wang
Article
Environmental Sciences
Mengjia Wang, Rui Sun, Zhiqiang Xiao
Article
Environmental Sciences
Tao Yu, Rui Sun, Zhiqiang Xiao, Qiang Zhang, Juanmin Wang, Gang Liu
Article
Environmental Sciences
Bo Hu, Xingying Zhang, Rui Sun, Xianchun Zhu
Article
Environmental Sciences
Mengjia Wang, Rui Sun, Anran Zhu, Zhiqiang Xiao
Article
Environmental Sciences
Helin Zhang, Rui Sun, Dailiang Peng, Xiaohua Yang, Yan Wang, Yueming Hu, Shijun Zheng, Jingyu Zhang, Jia Bai, Qi Li
Summary: This paper evaluates the impact of China's rapid urbanization on NPP, showing a decrease in NPP in urban areas but an increase in NPP in buffer zones, primarily influenced by temperature and sunshine duration. Increasing temperature promotes NPP growth, while sunshine duration and vegetation loss contribute to NPP decline in urban agglomerations.
Article
Environmental Sciences
Jingyu Zhang, Jindi Wang, Rui Sun, Hongmin Zhou, Helin Zhang
Article
Environmental Sciences
Tao Yu, Qiang Zhang, Rui Sun
Summary: This study successfully upscaled ground eddy covariance systems' gross primary production (GPP) to a regional scale using machine learning methods, with random forest achieving the highest accuracy in the validation process.
Article
Engineering, Electrical & Electronic
Qinru Liu, Liang Zhao, Rui Sun, Tao Yu, Shun Cheng, Mengjia Wang, Anran Zhu, Qi Li
Summary: In this study, vegetation net primary productivity (NPP) in the upper Luanhe River Basin from 2000 to 2017 was generated using a data fusion model and the MuSyQ NPP model. The results showed a fluctuating increasing trend in annual NPP, with precipitation being a significant factor for the interannual variation. Temperature had a weak influence on NPP. Additionally, human activities could change the trend of annual NPP.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Tao Yu, Qiang Zhang, Rui Sun
Summary: Studying the spatial representativeness of carbon flux measurement data for typical land cover types in the Heihe River Basin, China, revealed climate footprint distances ranging from about 500 m to 1500 m. Validating multiple-scale GPP products at footprint scale showed higher accuracy compared to field scale, indicating that precision may be higher when validating remote sensing GPP products at the footprint scale.
Article
Environmental Sciences
Juan Li, Zhiqiang Xiao, Rui Sun, Jinling Song
Summary: This paper proposes an unsupervised domain adaptation-based method to estimate LAI values from VIIRS surface reflectance dataset. The method utilizes a transfer component analysis (TCA) algorithm to reduce the distribution discrepancies between MODIS and VIIRS surface reflectance, and trains general regression neural networks (GRNNs) using embedded data from MODIS surface reflectance dataset. The results show that the method effectively estimates LAI values with high accuracy.
Article
Environmental Sciences
Helin Zhang, Jia Bai, Rui Sun, Yan Wang, Yuhao Pan, Patrick C. C. McGuire, Zhiqiang Xiao
Summary: This study generated a global GPP dataset based on an improved LUE model, considering temperature, water, atmospheric CO2 concentrations, radiation components, and nitrogen index. The dataset showed good spatial consistency and provides a reliable alternative for large-scale carbon cycle research and long-term GPP monitoring.
Article
Computer Science, Information Systems
Tao Yu, Yong Pang, Rui Sun, Xiaodong Niu
Summary: In this paper, a spatial downscaling method based on deep learning methods was used to generate high resolution GPP/NPP data in the forest areas of the upper Luanhe River basin in China. The results showed that the downscaled GPP/NPP using convolutional neural network achieved the highest accuracy.
