GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Effects of Variation in Tamarix chinensis Plantations on Soil Microbial Community Composition in the Middle Yellow River Floodplain
    MDPI AG ; 2023
    In:  International Journal of Environmental Research and Public Health Vol. 20, No. 6 ( 2023-03-12), p. 5015-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 20, No. 6 ( 2023-03-12), p. 5015-
    Abstract: Floodplains have important ecological and hydrological functions in terrestrial ecosystems, experience severe soil erosion, and are vulnerable to losing soil fertility. Tamarix chinensis Lour. plantation is the main vegetation restoration measure for maintaining soil quality in floodplains. Soil microorganisms are essential for driving biogeochemical cycling processes. However, the effects of sampling location and shrub patch size on soil microbial community composition remain unclear. In this study, we characterized changes in microbial structure, as well as the factors driving them, in inside- and outside-canopy soils of three patch sizes (small, medium, large) of T. chinensis plants in the middle Yellow River floodplain. Compared with the outside-canopy soils, inside-canopy had higher microbial phospholipid fatty acids (PLFAs), including fungi, bacteria, Gram-positive bacteria (GP), Gram-negative bacteria (GN), and arbuscular mycorrhizal fungi. The ratio of fungi to bacteria and GP to GN gradually decreased as shrub patch size increased. Differences between inside-canopy and outside-canopy soils in soil nutrients (organic matter, total nitrogen, and available phosphorus) and soil salt content increased by 59.73%, 40.75%, 34.41%, and 110.08% from small to large shrub patch size. Changes in microbial community composition were mainly driven by variation in soil organic matter, which accounted for 61.90% of the variation in inside-canopy soils. Resource islands could alter microbial community structure, and this effect was stronger when shrub patch size was large. The results indicated that T. chinensis plantations enhanced the soil nutrient contents (organic matter, total nitrogen, and available phosphorus) and elevated soil microbial biomass and changed microbial community composition; T. chinensis plantations might thus provide a suitable approach for restoring degraded floodplain ecosystems.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph20065015
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    A Meta-Analysis of Risk Factors for Post-Traumatic Stress Disorder (PTSD) in Adults and Children after Earthquakes
    MDPI AG ; 2017
    In:  International Journal of Environmental Research and Public Health Vol. 14, No. 12 ( 2017-12-08), p. 1537-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 14, No. 12 ( 2017-12-08), p. 1537-
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph14121537
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    Near-Ultraviolet to Near-Infrared Band Thresholds Cloud Detection Algorithm for TANSAT-CAPI
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 10 ( 2021-05-13), p. 1906-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 10 ( 2021-05-13), p. 1906-
    Abstract: Cloud and aerosol polarization imaging detector (CAPI) is one of the important payloads on the China Carbon Dioxide Observation Satellite (TANSAT), which can realize multispectral polarization detection and accurate on-orbit calibration. The main function of the instrument is to identify the interference of clouds and aerosols in the atmospheric detection path and to improve the retrieval accuracy of greenhouse gases. Therefore, it is of great significance to accurately identify the clouds in remote sensing images. However, in order to meet the requirement of lightweight design, CAPI is only equipped with channels in the near-ultraviolet to near-infrared bands. It is difficult to achieve effective cloud recognition using traditional visible light to thermal infrared band spectral threshold cloud detection algorithms. In order to solve the above problem, this paper innovatively proposes a cloud detection method based on different threshold tests from near ultraviolet to near infrared (NNDT). This algorithm first introduces the 0.38 μm band and the ratio of 0.38 μm band to 1.64 μm band, to realize the separation of cloud pixels and clear sky pixels, which can take advantage of the obvious difference in radiation characteristics between clouds and ground objects in the near-ultraviolet band and the advantages of the band ratio in identifying clouds on the snow surface. The experimental results show that the cloud recognition hit rate (PODcloud) reaches 0.94 (ocean), 0.98 (vegetation), 0.99 (desert), and 0.86 (polar), which therefore achieve the application standard of CAPI data cloud detection The research shows that the NNDT algorithm replaces the demand for thermal infrared bands for cloud detection, gets rid of the dependence on the minimum surface reflectance database that is embodied in traditional cloud recognition algorithms, and lays the foundation for aerosol and CO2 parameter inversion.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13101906
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    Inter-Comparison of Four Models for Detecting Forest Fire Disturbance from MOD13A2 Time Series
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 6 ( 2022-03-17), p. 1446-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 6 ( 2022-03-17), p. 1446-
    Abstract: Many models for change point detection from time series remote sensing images have been developed to date. For forest ecosystems, fire disturbance detection models have always been an important topic. However, due to a lack of benchmark datasets, it is difficult to determine which model is appropriate. Therefore, we collected and generated a benchmark dataset specifically for forest fire disturbance detection, named CUG-FFireMCD1. The CUG-FFireMCD1 contains a total of 132 pieces of MODIS MOD13A2 time series, and each time series contains at least one fire disturbance. The occurrence time for a forest fire disturbance was determined using the National Cryosphere DesertDataCenter(NCDC) website, and the precise latitude and longitude coordinates were determined using the FireCCI51 dataset. In addition, we selected four commonly used time series change detection models and validate the advantages and limitations of the four models through dataset analysis. Finally, we use the detection results of the models and their applicable scenarios to label the additional change points. The four models we used are breaks for additive season and trend (BFAST), Prophet, continuous change detection and classification (CCDC), and Landsat-based detection of trends in disturbance and recovery (LandTrendR). The experiments show that the BFAST outperformed the other three models in forest fire disturbance detection from MOD13A2 time series, with the successful-detection-proportion rate of 96.2% with the benchmark dataset. The detection effect of the Prophet model is not as good as that of BFAST, but it also performs well, with the successful-detection-proportion rate of 87.9%. The detection results of CCDC and LandTrendR are similar, and the detection success rate is lower than that of BFAST and Prophet, but their detection results can be used as data support for labeling work. However, to apply them perfectly to MOD13A2 time series change detection, it is best to do some model adaptation. In summary, the CUG-FFireMCD1 data were verified using different types of time series change detection models, and the change points we marked are credible. The CUG-FFireMCD1 will surely provide a reliable benchmark for model optimization and the accuracy verification of remote sensing time series change detection.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14061446
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Strategies for the Efficient Estimation of Soil Moisture through Spectroscopy: Sensitive Wavelength Algorithm, Spectral Resampling and Signal-to-Noise Ratio Selection
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 2 ( 2022-01-14), p. 826-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 2 ( 2022-01-14), p. 826-
    Abstract: It is found that the remote sensing parameters such as spectral range, spectral resolution and signal-to-noise ratio directly affect the estimation accuracy of soil moisture content. However, the lack of research on the relationship between the parameters and estimation accuracy restricts the prolongation of application. Therefore, this study took the demand for this application as the foothold for developing spectrometry. Firstly, a method based on sensitivity analysis of soil radiative transfer model-successive projection algorithm (SA-SPA) was proposed to select sensitive wavelengths. Then, the spectral resampling method was used to select the best spectral resolution in the corresponding sensitive wavelengths. Finally, the noise-free spectral data simulated by the soil radiative transfer model was added with Gaussian random noise to change the signal-to-noise ratio, so as to explore the influence of signal-to-noise ratio on the estimation accuracy. The research results show that the estimation accuracy obtained through the SA-SPA (RMSEP 〈 12.1 g kg−1) is generally superior to that from full-spectrum data (RMSEP 〈 14 g kg−1). At selected sensitive wavelengths, the best spectral resolution is 34 nm, and the applicable signal-to-noise ratio ranges from 150 to 350. This study provides technical support for the efficient estimation of soil moisture content and the development of spectrometry, which comprehensively considers the common influence of spectral range, spectral resolution and signal-to-noise ratio on the estimation accuracy of soil moisture content.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app12020826
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 6
    Online Resource
    Online Resource
    Shear-Wave Tomography Using Ocean Ambient Noise with Interference
    MDPI AG ; 2020
    In:  Remote Sensing Vol. 12, No. 18 ( 2020-09-11), p. 2969-
    Details
    In: Remote Sensing, MDPI AG, Vol. 12, No. 18 ( 2020-09-11), p. 2969-
    Abstract: Ambient noise carries abundant subsurface structure information and attracts ever-increasing attention in the past decades. However, there are lots of interference factors in the ambient noise in the real world, making the noise difficult to be utilized in seismic interferometry. The paper performs shear-wave tomography on a very short recording of ocean ambient noise with interference. An adapted eigenvalue-based filter is adopted as a pre-processing method to deal with the strong, directional interference problem. Beamforming and the noise crosscorrelation analyses show that the filter works well on the noise recorded by the array. Directional energy is significantly suppressed and the background diffuse component of the noise is relatively enhanced. The shear-wave tomography shows a 4-layer subsurface structure of the area covered by the array, with relatively homogeneous distribution of the shear-wave velocity values in the top three layers and a complicated structure in the bottom layer. Moreover, 3 high-velocity zones can be recognized in the bottom layer. The result is compared with several other tomography results using different methods and data. It demonstrates that, although the ambient noise used in this paper is very short and severely contaminated, a reasonable tomography result can be obtained by applying the adapted eigenvalue-based filter. Since it is the first application of the adapted eigenvalue-based filter in seismic tomography using ambient noise, the paper proves the effectiveness of this technique and shows the potential of the technique in ambient noise processing and passive seismic interferometry.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs12182969
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 7
    Online Resource
    Online Resource
    A Framework for Four-Dimensional Variational Data Assimilation Based on Machine Learning
    MDPI AG ; 2022
    In:  Entropy Vol. 24, No. 2 ( 2022-02-12), p. 264-
    Details
    In: Entropy, MDPI AG, Vol. 24, No. 2 ( 2022-02-12), p. 264-
    Abstract: The initial field has a crucial influence on numerical weather prediction (NWP). Data assimilation (DA) is a reliable method to obtain the initial field of the forecast model. At the same time, data are the carriers of information. Observational data are a concrete representation of information. DA is also the process of sorting observation data, during which entropy gradually decreases. Four-dimensional variational assimilation (4D-Var) is the most popular approach. However, due to the complexity of the physical model, the tangent linear and adjoint models, and other processes, the realization of a 4D-Var system is complicated, and the computational efficiency is expensive. Machine learning (ML) is a method of gaining simulation results by training a large amount of data. It achieves remarkable success in various applications, and operational NWP and DA are no exception. In this work, we synthesize insights and techniques from previous studies to design a pure data-driven 4D-Var implementation framework named ML-4DVAR based on the bilinear neural network (BNN). The framework replaces the traditional physical model with the BNN model for prediction. Moreover, it directly makes use of the ML model obtained from the simulation data to implement the primary process of 4D-Var, including the realization of the short-term forecast process and the tangent linear and adjoint models. We test a strong-constraint 4D-Var system with the Lorenz-96 model, and we compared the traditional 4D-Var system with ML-4DVAR. The experimental results demonstrate that the ML-4DVAR framework can achieve better assimilation results and significantly improve computational efficiency.
    Type of Medium: Online Resource
    ISSN: 1099-4300
    URL: Article
    DOI: 10.3390/e24020264
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2014734-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 8
    Online Resource
    Online Resource
    Investigation and Improvement of Test Methods for Capacitance and DCESR of EDLC Cells
    MDPI AG ; 2023
    In:  Sensors Vol. 23, No. 10 ( 2023-05-12), p. 4717-
    Details
    In: Sensors, MDPI AG, Vol. 23, No. 10 ( 2023-05-12), p. 4717-
    Abstract: The quick and accurate characterization of commercial electrochemical double-layer capacitor (EDLC) cells, especially their capacitance and direct-current equivalent series internal resistance (DCESR), is of great significance for the design, maintenance, and monitoring of EDLCs used in areas of energy, sensors, electric power, construction machinery, rail transit, automobile transportation, and military. In this study, the capacitance and DCESR of three commercial EDLC cells with similar performance were determined and compared by following the three commonly-used standards of IEC 62391, Maxwell, and QC/T741-2014, which are significantly different in test procedures and calculation methods. The analysis of the test procedures and results demonstrated that the IEC 62391 standard has the disadvantages of a large testing current, long testing time, and a complex and inaccurate DCESR calculation, whereas the Maxwell standard has the disadvantages of a large testing current, a small capacitance, and large DCESR testing results, and furthermore the QC/T 741 standard has the disadvantages of a high resolution requirement for the equipment and small DCESR results. Therefore, an improved method was proposed to determine the capacitance and DCESR of EDLC cells by short-time constant voltage charging and discharging interruption methods, respectively, with the advantages of high accuracy, low equipment requirements, short testing time, and the easy calculation of DCESR over the original three standards.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s23104717
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2052857-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 9
    Online Resource
    Online Resource
    Which Specific Exercise Models Are Most Effective on Global Cognition in Patients with Cognitive Impairment? A Network Meta-Analysis
    MDPI AG ; 2023
    In:  International Journal of Environmental Research and Public Health Vol. 20, No. 4 ( 2023-02-04), p. 2790-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 20, No. 4 ( 2023-02-04), p. 2790-
    Abstract: (1) Introduction: Physical exercise interventions can impart significant cognitive benefits to older adults suffering from cognitive impairment (CI). However, the efficacy of these interventions can vary widely, depending on the type, intensity, duration and frequency of exercise. (2) Aim: To systematically review the efficacy of exercise therapy on global cognition in patients with CI using a network meta-analysis (NMA). (3) Methods: The PubMed, Embase, Sport Discus (EBSCO) and Cochrane Library databases were electronically searched to collect randomized controlled trials (RCTs) on exercise for patients with CI from inception to 7 August 2022. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. The NMA was performed using the consistency model. (4) Results: A total of 29 RCTs comprising 2458 CI patients were included. The effects of different types of exercise on patients with CI were ranked as follows: multicomponent exercise (SMD = 0.84, 95% CI 0.31 to 1.36, p = 0.002), short duration (≤45 min) (SMD = 0.83, 95% CI 0.18 to 1.19, p = 0.001), vigorous intensity (SMD = 0.77, 95% CI 0.18 to 1.36, p = 0.011) and high frequency (5–7 times/week) (SMD = 1.28, 95% CI 0.41 to 2.14, p = 0.004). (5) Conclusion: These results suggested that multicomponent, short-duration, high-intensity, and high-frequency exercise may be the most effective type of exercise in improving global cognition in CI patients. However, more RCTs based on direct comparison of the effects of different exercise interventions are needed. (6) NMA registration identifier: CRD42022354978.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph20042790
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...