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Article ; Online: Aboveground Forest Biomass Estimation Using Tent Mapping Atom Search Optimized Backpropagation Neural Network with Landsat 8 and Sentinel-1A Data

Zhao Chen / Zhibin Sun / Huaiqing Zhang / Huacong Zhang / Hanqing Qiu

Remote Sensing, Vol 15, Iss 24, p

2023 Volume 5653

Abstract: Accurate forest biomass estimation serves as the foundation of forest management and holds critical significance for a comprehensive understanding of forest carbon storage and balance. This study aimed to integrate Landsat 8 OLI and Sentinel-1A SAR ... ...

Abstract	Accurate forest biomass estimation serves as the foundation of forest management and holds critical significance for a comprehensive understanding of forest carbon storage and balance. This study aimed to integrate Landsat 8 OLI and Sentinel-1A SAR satellite image data and selected a portion of the Shanxia Experimental Forest in Jiangxi Province as the study area to establish a biomass estimation model by screening influencing factors. Firstly, we extracted spectral information, vegetation indices, principal component features, and texture features within 3 × 3-pixel neighborhoods from Landsat 8 OLI. Moreover, we incorporated Sentinel-1’s VV (vertical transmit–vertical receive) and VH (vertical transmit–horizontal receive) polarizations. We proposed an ensemble AGB (aboveground biomass) model based on a neural network. In addition to the neural network model, namely the tent mapping atom search optimized BP neural network (Tent_ASO_BP) model, partial least squares regression (PLSR), support vector machine (SVR), and random forest (RF) regression prediction techniques were also employed to establish the relationship between multisource remote sensing data and forest biomass. Optical variables (Landsat 8 OLI), SAR variables (Sentinel-1A), and their combinations were input into the four prediction models. The results indicate that Tent_ ASO_ BP model can better estimate forest biomass. Compared to pure optical or single microwave data, the Tent_ASO_BP model with the optimal combination of optical and microwave input features achieved the highest accuracy. Its R 2 was 0.74, root mean square error (RMSE) was 11.54 Mg/ha, and mean absolute error (MAE) was 9.06 Mg/ha. Following this, the RF model (R 2 = 0.54, RMSE = 21.33 Mg/ha, MAE = 17.35 Mg/ha), SVR (R 2 = 0.52, RMSE = 17.66 Mg/ha, MAE = 15.11 Mg/ha), and PLSR (R 2 = 0.50, RMSE = 16.52 Mg/ha, MAE = 12.15 Mg/ha) models were employed. In conclusion, the BP neural network model improved by tent mapping atom search optimization algorithm significantly enhanced the ...
Keywords	Landsat 8 OLI ; Sentinel-1A ; combined optical and SAR indices ; tent mapping atom search optimized BP neural network (Tent_ASO_BP) ; aboveground biomass ; Science ; Q
Subject code	333
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Lake algal bloom monitoring via remote sensing with biomimetic and computational intelligence

Zhibin Sun / Ni-Bin Chang / Chi-Farn Chen / Wei Gao

International Journal of Applied Earth Observations and Geoinformation, Vol 113, Iss , Pp 102991- (2022)

2022

Abstract: Traditional supervised classifications for remote sensing-based water quality monitoring count on a set of classifiers to retrieve features and improve their prediction accuracies based on ground truth samples. However, many existing feature extraction ... ...

Abstract	Traditional supervised classifications for remote sensing-based water quality monitoring count on a set of classifiers to retrieve features and improve their prediction accuracies based on ground truth samples. However, many existing feature extraction methods in remote sensing are unable to exhibit multiple-instance nonlinear spatial pattern recognition at scales via ensemble learning. This paper designed for lake algal bloom monitoring presents intelligent feature extraction for harmonizing local and global features via tensor flow-based ensemble learning with integrated biomimetic and computational intelligence. To explore such complexity, an Integrated Biomimetic and Ensemble Learning Algorithm (IBELA) was developed to synthesize the contribution from different classifiers associated with the biomimetic philosophy of integrated bands. It leads to strengthened multiple-instance spatial pattern recognition in lake algal bloom monitoring via image fusion at the decision level. With the implementation of IBELA, a case study of a eutrophic freshwater lake, Lake Managua, for water quality monitoring leads to demonstrate six input visual senses showing different impacts on retrieving Chl-a concentrations in the dry and wet season, respectively. The input of total nitrogen from the watershed plays the most important role in water quality variations in both seasons in a watershed-based food–water nexus. Although ultraviolet and microwave bands are important in the dry season, Secchi disk depth is critical in the wet season for water quality monitoring.
Keywords	Eutrophication ; Biomimetic intelligence ; Computational intelligence ; Ensemble learning ; Food-water nexus ; Decision level fusion ; Physical geography ; GB3-5030 ; Environmental sciences ; GE1-350
Subject code	333
Language	English
Publishing date	2022-09-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Failure Detection in Eucalyptus Plantation Based on UAV Images

Huanxin Zhao / Yixiang Wang / Zhibin Sun / Qi Xu / Dan Liang

Forests, Vol 12, Iss 1250, p

2021 Volume 1250

Abstract: The information of the locations and numbers of failures is crucial to precise management of new afforestation, especially during seedling replanting in young forests. In practice, foresters are more accustomed to determining the locations of failures ... ...

Abstract	The information of the locations and numbers of failures is crucial to precise management of new afforestation, especially during seedling replanting in young forests. In practice, foresters are more accustomed to determining the locations of failures according to their rows than based on their geographical coordinates. The relative locations of failures are more difficult to collect than the absolute geographic coordinates which are available from an orthoimage. This paper develops a novel methodology for obtaining the relative locations of failures in rows and counting the number of failures in each row. The methodology contains two parts: (1) the interpretation of the direction angle of seedlings rows on an unmanned aerial vehicle (UAV) orthoimage based on the probability statistical theory (called the grid-variance (GV) method); (2) the recognition of the centerline of each seedling rows using K-means and the approach to counting failures in each row based on the distribution of canopy pixels near the centerline of each seedling row (called the centerline (CL) method). The experimental results showed that the GV method can accurately interpret the direction angle of rows (45°) in an orthoimage and the CL method can quickly and accurately obtain the numbers and relative locations of failures in rows. The failure detection rates in the two experimental areas were 91.8% and 95%, respectively. These research findings can provide technical support for the precise cultivation of planted seedling forests.
Keywords	UAV remote sensing ; forest plantation ; number of failures ; relative location ; Plant ecology ; QK900-989
Subject code	910
Language	English
Publishing date	2021-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Study on the Relationship between Richness and Morphological Diversity of Higher Taxa in the Darkling Beetles (Coleoptera

Liangxue Cheng / Yijie Tong / Yuchen Zhao / Zhibin Sun / Xinpu Wang / Fangzhou Ma / Ming Bai

Diversity, Vol 14, Iss 60, p

Tenebrionidae)

2022 Volume 60

Abstract: Many studies have found that the correlation between species richness (SR) and morphological diversity (MD) is positive, but the correlation degree of these parameters is not always consistent due to differences in categories and various ecological ... ...

Abstract	Many studies have found that the correlation between species richness (SR) and morphological diversity (MD) is positive, but the correlation degree of these parameters is not always consistent due to differences in categories and various ecological factors in the living environment. Based on this, related studies have revealed the good performance of using higher taxa in biodiversity research, not only by shifting the testing group scale from local communities to worldwide datasets but also by adding different taxonomic levels, such as the genus level. However, it remains unclear whether this positive correlation can also be applied to other categories or groups. Here, we evaluated the applicability of higher taxa in the biodiversity study of darkling beetles by using 3407 species (9 subfamilies, 89 tribes, and 678 genera), based on the correlation between taxa richness and morphological diversity in the tribe/genus/species. In addition, the continuous features prevalent in the tenebrionids, pronotum and elytron, were selected, and the morphological diversity of various groups was obtained by the geometric morphometric approach to quantify the morphologic information of features. This study found that genus/species richness in subfamilies Pimelinae and Stenochiinae was positively correlated with the change trend of MD, and the correlation between the MD of elytron and taxa richness gradually decreased from the tribe-level to the genus-level to the species-level test. The results confirm the stable morphology and simple function of the elytron and the applicability of tribe level in biodiversity research.
Keywords	biodiversity ; higher taxa ; darkling beetles ; pronotum ; elytron ; Biology (General) ; QH301-705.5
Subject code	590
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identifying Core Wavelengths of Oil Tree’s Hyperspectral Data by Taylor Expansion

Zhibin Sun / Xinyue Jiang / Xuehai Tang / Lipeng Yan / Fan Kuang / Xiaozhou Li / Min Dou / Bin Wang / Xiang Gao

Remote Sensing, Vol 15, Iss 3137, p

2023 Volume 3137

Abstract: The interference of background noise leads to the extremely high spatial complexity of hyperspectral data. Sensitive band selecting is an important task to minimize or eliminate the influence of non-target elements. In this study, Taylor expansion is ... ...

Abstract	The interference of background noise leads to the extremely high spatial complexity of hyperspectral data. Sensitive band selecting is an important task to minimize or eliminate the influence of non-target elements. In this study, Taylor expansion is innovatively used to identify core wavelengths/bands of hyperspectral data. Unlike other traditional methods, this proposed Taylor-CC method considers more local and global information of spectral function to estimate the linear/nonlinear correlation between two wavelengths. Using samples of hyperspectral data with a wavelength range of 350–2500 nm and SPAD for Camellia oleifera, this Taylor-CC method is compared with the traditional PCC method derived from the Pearson correlation coefficient. Using the 240 samples with their different 57 core wavelengths identified by the Taylor-CC method and PCC method, three machine models (i.e., random forest-RF, linear regression-LR, and artificial neural network-ANN) are trained to compare their performances. Their results show that the correlation matrix from the Taylor-CC method represents a clear diagonal pattern with near zero values at most locations away from the diagonal, and all three models confirm that the Taylor-CC method is superior to the PCC method. Moreover, the SPAD spectral response relationship based on machine learning algorithms is constructed, and ANN is the best prediction performance among the three models when using the core wavelengths identified by the Taylor-CC method. The Taylor-CC method proposed in this study not only lays a mathematical foundation for the next analysis of the response mechanism between spectral characteristics and nutrient content of Camellia leaf, but also provides a new idea for the correlation analysis of adjacent spectral bands for hyperspectral signals in many applications.
Keywords	ANN ; hyperspectral ; oil tree ; SPAD ; Taylor expansion ; wavelength identification ; Science ; Q
Subject code	310
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Atmospheric Charge Separation Mechanism Due to Gas Release from the Crust before an Earthquake

Wen Li / Zhibin Sun / Tao Chen / Zhaoai Yan / Zhongsong Ma / Chunlin Cai / Zhaohai He / Jing Luo / Shihan Wang

Applied Sciences, Vol 14, Iss 1, p

2023 Volume 245

Abstract: In fair weather, the vertical atmospheric electric field is oriented downward (positive in the earth surface ordinate system) in the global atmospheric circuit. Some researchers have revealed the unique phenomenon whereby once an upward vertical ... ...

Abstract	In fair weather, the vertical atmospheric electric field is oriented downward (positive in the earth surface ordinate system) in the global atmospheric circuit. Some researchers have revealed the unique phenomenon whereby once an upward vertical atmospheric electric field is observed in fair weather, an earthquake (EQ) follows within 2–48 h regardless of the EQ magnitude. However, the mechanism has not been explained with a suitable physical model. In this paper, a physical model is presented considering four types of forces acting on charged particles in the air. It is demonstrated that the heavier positive ions and lighter negative ions are rapidly separated. Finally, a reversed fair weather electrostatic field is formed by the above charge separation process. The simulation results have instructive significance for future observations and hazard predictions and still need further research.
Keywords	charge separation ; reverse vertical atmospheric electric field ; multiple forces ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	620
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Current Status of Single Particle Imaging with X-ray Lasers

Zhibin Sun / Jiadong Fan / Haoyuan Li / Huaidong Jiang

Applied Sciences, Vol 8, Iss 1, p

2018 Volume 132

Abstract: The advent of ultrafast X-ray free-electron lasers (XFELs) opens the tantalizing possibility of the atomic-resolution imaging of reproducible objects such as viruses, nanoparticles, single molecules, clusters, and perhaps biological cells, achieving a ... ...

Abstract	The advent of ultrafast X-ray free-electron lasers (XFELs) opens the tantalizing possibility of the atomic-resolution imaging of reproducible objects such as viruses, nanoparticles, single molecules, clusters, and perhaps biological cells, achieving a resolution for single particle imaging better than a few tens of nanometers. Improving upon this is a significant challenge which has been the focus of a global single particle imaging (SPI) initiative launched in December 2014 at the Linac Coherent Light Source (LCLS), SLAC National Accelerator Laboratory, USA. A roadmap was outlined, and significant multi-disciplinary effort has since been devoted to work on the technical challenges of SPI such as radiation damage, beam characterization, beamline instrumentation and optics, sample preparation and delivery and algorithm development at multiple institutions involved in the SPI initiative. Currently, the SPI initiative has achieved 3D imaging of rice dwarf virus (RDV) and coliphage PR772 viruses at ~10 nm resolution by using soft X-ray FEL pulses at the Atomic Molecular and Optical (AMO) instrument of LCLS. Meanwhile, diffraction patterns with signal above noise up to the corner of the detector with a resolution of ~6 Ångström (Å) were also recorded with hard X-rays at the Coherent X-ray Imaging (CXI) instrument, also at LCLS. Achieving atomic resolution is truly a grand challenge and there is still a long way to go in light of recent developments in electron microscopy. However, the potential for studying dynamics at physiological conditions and capturing ultrafast biological, chemical and physical processes represents a tremendous potential application, attracting continued interest in pursuing further method development. In this paper, we give a brief introduction of SPI developments and look ahead to further method development.
Keywords	X-ray free-electron lasers ; XFEL ; coherent diffraction imaging ; single particle imaging ; resolution ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	535
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Genuine and Secure Identity-Based Public Audit for the Stored Data in Healthcare Cloud

Jianhong Zhang / Zhibin Sun / Jian Mao

Journal of Healthcare Engineering, Vol

2018 Volume 2018

Abstract: Cloud storage has attracted more and more concern since it permits cloud users to save and employ the corresponding outsourced files at arbitrary time, with arbitrary facility and from arbitrary place. To make sure data integrality, numerous public ... ...

Abstract	Cloud storage has attracted more and more concern since it permits cloud users to save and employ the corresponding outsourced files at arbitrary time, with arbitrary facility and from arbitrary place. To make sure data integrality, numerous public auditing constructions have been presented. However, existing constructions mainly have built on the PKI. In these constructions, to achieve data integrality, the auditor first must authenticate the legality of PKC, which leads to a great burden for the auditor. To eliminate the verification of time-consuming certificate, in this work, we present an efficient identity-based public auditing proposal. Our construction is an identity-based data auditing system in the true sense in that the algorithm to calculate authentication signature is an identity-based signature algorithm. By extensive security evaluation and experimental testing, the consequences demonstrate that our proposal is safe and effective; it can efficiently hold back forgery attack and replay attack. Finally, compared with the two identity-based public auditing proposals, our proposal outperforms the two proposals under the condition of overall considering computational cost, communication overhead, and security strength.
Keywords	Medicine (General) ; R5-920 ; Medical technology ; R855-855.5
Subject code	005
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An Ensemble Algorithm Based Component for Geomagnetic Data Assimilation

Zhibin Sun and Weijia Kuang

Terrestrial, Atmospheric and Oceanic Sciences, Vol 26, Iss 1, p

2015 Volume 53

Abstract: Geomagnetic data assimilation is one of the most recent developments in geomagnetic studies. It combines geodynamo model outputs and surface geomagnetic observations to provide more accurate estimates of the core dynamic state and provide accurate ... ...

Abstract	Geomagnetic data assimilation is one of the most recent developments in geomagnetic studies. It combines geodynamo model outputs and surface geomagnetic observations to provide more accurate estimates of the core dynamic state and provide accurate geomagnetic secular variation forecasting. To facilitate geomagnetic data assimilation studies, we develop a stand-alone data assimilation component for the geomagnetic community. This component is used to calculate the forecast error covariance matrices and the gain matrix from a given geodynamo solution, which can then be used for sequential geomagnetic data assimilation. This component is very flexible and can be executed independently. It can also be easily integrated with arbitrary dynamo models.
Keywords	geophysics ; geology ; atmospheric science ; space science ; oceanic science ; hydrology ; QE1-996.5 ; Geophysics. Cosmic physics ; QC801-809
Language	English
Publishing date	2015-01-01T00:00:00Z
Publisher	Springer
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Application of transcriptome analysis to investigate the effects of long-term low temperature stress on liver function in the tiger puffer (Takifugu rubripes)

Zhifeng Liu / Liguang Zhu / Xinan Wang / Shiying Liu / Aijun Ma / Haowen Chang / Zhibin Sun / Fei Xu / Haichi Zhao

Frontiers in Marine Science, Vol

2022 Volume 9

Abstract: The tiger puffer (Takifugu rubripes) is an important economic fish species in northern China. However, it is a warm-temperature species, and low winter temperatures can result in high mortality in aquaculture. Understanding the mechanisms of cold ... ...

Abstract	The tiger puffer (Takifugu rubripes) is an important economic fish species in northern China. However, it is a warm-temperature species, and low winter temperatures can result in high mortality in aquaculture. Understanding the mechanisms of cold resistance in tiger puffers will thus provide critical information to help cope with winter cold. In this study, we performed transcriptome analysis of livers from puffer fish kept at different temperatures (18°C, 13°C, and 8°C) to identify the key pathways and genes involved in the response to low-temperature stress. We also detected serum levels of proteases, arginine, and proline to obtain further information on the response to cold adaption. Totals of 51, 942, and 195 differentially expressed genes were identified in the 18°C vs 13°C, 18°C vs 8°C, and 13°C vs 8°C groups, respectively. Pathway analysis showed that significantly enriched pathways were mainly related to digestion, metabolism, and environmental adaptation. Most genes in the pathways related to digestion and metabolism were down-regulated, while most genes in the pathways related to environmental adaptation were up-regulated. Serum levels of proteases were significantly lower in the low-temperature groups (13°C and 8°C) compared with the control group (18°C), while arginine and proline levels were significantly higher in the 8°C group compared with the other two groups. These results suggest that low temperature caused digestive and metabolic disorders, as well as adaptive changes to low temperature in tiger puffers. On this premise, we found that some up-regulated genes in the pancreatic secretion pathway, arginine and proline metabolism pathway, and circadian rhythm pathway played important roles in the survival, growth, and development of tiger puffers under low-temperature stress. The accumulation of arginine and proline can maintain metabolism and circulation and resist cold stress. The circadian rhythm is closely related to digestion and metabolism, which is an adaptive change and plays a positive ...
Keywords	Takifugu rubripes ; low temperature ; liver ; transcriptome ; qPCR ; Science ; Q ; General. Including nature conservation ; geographical distribution ; QH1-199.5
Subject code	333
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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