Forest stand spectrum reconstruction using spectrum spatial feature gathering and multilayer perceptron

IntroductionThree-dimensional spectral distributions of forest stands can provide spatial information on the physiological and biochemical status of forests, which is vital for forest management. However, three-dimensional spectral studies of forest stands are limited.MethodsIn this study, LiDAR and multispectral data were collected from Masson pine stands in southern Fujian Province, China, and a method was proposed for inverting forest spectra using point clouds as a unit. First, multispectral values were mapped to a point cloud, and the isolated forest algorithm combined with K-means clustering was applied to characterize fusion data. Second, five deep learning algorithms were selected for semantic segmentation, and the overall accuracy (oAcc) and mean intersection ratio (mIoU) were used to evaluate the performance of various algorithms on the fusion data set. Third, the semantic segmentation model was used to reconfigure the class 3D spectral distribution, and the model inversion outcomes were evaluated by the peaks and valleys of the curve of the predicted values and distribution gaps.ResultsThe results show that the correlations between spectral attributes and between spatial attributes were both greater than 0.98, while the correlation between spectral and spatial attributes was 0.43. The most applicable method was PointMLP, highest oAcc was 0.84, highest mIoU was 0.75, peak interval of the prediction curve tended to be consistent with the true values, and maximum difference between the predicted value and the true value of the point cloud spectrum was 0.83.DiscussionExperimental data suggested that combining spatial fusion and semantic segmentation effectively inverts three-dimensional spectral information for forest stands. The model could meet the accuracy requirements of local spectral inversion, and the NIR values of stands in different regions were correlated with the vertical height of the canopy and the distance from the tree apex in the region. These findings improve our understanding of the precise three-dimensional spectral distribution of forests, providing a basis for near-earth remote sensing of forests and the estimation of forest stand health

Preparation of Super-Flexible Silica Aerogel and Its Application in Oil–Water Separation

Using silica as the precursor, and methyltrimethoxysilane and dimethyldimethoxysilane as the silicon sources, a super-flexible hydrophobic lipophilic gel solid was prepared via hydrolysis, drying, solvent replacement, and atmospheric-pressure drying. The characterization test showed that the sample had good flexibility, hydrophobicity, an amorphous structure, and a hydrophobic contact angle of 137°. Through the adsorption separation experiment, it was concluded that the adsorption separation rate of aerogel to oil substances is related to the viscosity of the oil substances. The hydrophobic and oleophilic properties of flexible silicon aerogel materials can be applied to many aspects, such as crude oil leakage and kitchen waste oil recovery, with broad future development prospects and great research significance

Disruptions in thermohaline staircases caused by subsurface mesoscale eddies in the eastern Caribbean Sea

Abstract Thermohaline staircases and mesoscale eddies play crucial roles in the transport of heat, salt, and nutrients in the ocean, yet their complex relationship remains unclear due to the limitations in observational resolution and lateral range. Here, utilizing high spatial resolution seismic images with a total length of 2518 km, we show the widespread occurrence of thermohaline staircases in the eastern Caribbean Sea and demonstrate their three-dimensional distribution. These staircases occupy about 70% of the total length of the seismic lines, with the remaining 30% occupied by six subsurface mesoscale eddies. These staircases are disrupted and interrupted due to the enhanced turbulent diffusivity driven by the vertical shear of these eddies. The numerous high-resolution seismic observations presented herein enhance our comprehension of the interplay between staircases and multiscale oceanic dynamical processes

Spatio-Temporal Multi-Scale Analysis of Landscape Ecological Risk in Minjiang River Basin Based on Adaptive Cycle

Landscape ecological security is an environmental requirement for social and economic development. Understanding the dynamic mechanisms of landscape change and the associated ecological risks in regional socioecological systems is necessary for promoting regional sustainable development. Using the Minjiang River Basin as the research area, the Google Earth Engine platform, random forest (RF) model, and FLUS model were employed for land use classification and future multi-scenario prediction. Multisource remote sensing data were used to establish a three-dimensional evaluation index system for an adaptive cycle. Additionally, the “potential-connection-resilience” framework was adopted to explore the spatial and temporal variations in landscape ecological risk in the basin from 2001 to 2035 under different administrative scales and development scenarios. The results showed that from 2001 to 2020, the building and forest areas increased significantly, whereas grassland and plowland areas decreased significantly. Moreover, the spatial fragmentation of the watershed improved significantly with the transformation of large amounts of grassland into forests. The construction area continued to expand in 2035 under different scenarios. Under the economic development scenario, the grassland and plowland areas decreased considerably, but the forest area increased slowly. Under the ecological protection scenario, the expansion of land use was restrained, and the reduction rate of grassland and cultivated land was moderated. From 2001 to 2020, the overall ecological risk was at a medium-low level and showed a decreasing trend, and the fragmentation degree of the forest had a significant impact on ecological risk. By 2035, landscape ecological risks increased under different development scenarios, and construction land expansion had become the dominant factor affecting the risk level. By evaluating the distribution and development trend of ecologically high-risk areas in the Minjiang River Basin, the results of this study provide basic support for the rational planning of land resources in the basin and decision making for future sustainable development efforts

Unraveling the Light‐Absorbing Properties of Brown Carbon at a Molecular Level

Abstract Brown carbon (BrC) exhibits a highly complex chemical composition with diverse light‐absorbing properties, which complicates our understanding of its climate impacts. This study examined the impact of molecular characteristics (including molecular mass, unsaturation, oxidation state, and polarity) and heteroatoms on the light‐absorbing properties (absorptivity and wavelength dependence) of BrC from a molecular perspective, based on the ultraviolet‐visible spectra of over 40,000 light‐absorbing substances in aerosol from different sources and ambience. Our findings reveal that the light‐absorptivity of BrC molecules increases with decreasing polarity and O/C ratio, while it rises with higher molecular mass and unsaturation. We developed predictive models for molecular absorptivity based on its double bond equivalent and O/C ratio. In addition, we observed an inverse correlation between absorptivity and wavelength dependence at the molecular level, as determined through mathematical analysis. This molecular‐level understanding provides valuable insights into BrC absorbing mechanisms, facilitating more accurate characterization in atmospheric models

Prescribing Patterns in Outpatient Clinics of Township Hospitals in China: A Comparative Study before and after the 2009 Health System Reform

Objective: China introduced a series of health reforms in 2009, including a national essential medicines policy and a medical insurance system for primary care institutions. This study aimed to determine the changing prescribing patterns associated with those reforms in township hospitals. Methods: A multi-stage stratified random cluster sampling method was adopted to identify 29 township hospitals from six counties in three provinces. A total of 2899 prescriptions were collected from the participating township hospitals using a systematic random sampling strategy. Seven prescribing indicators were calculated and compared between 2008 and 2013, assessing use of medicines (antibiotics and adrenal corticosteroids) and polypharmacy, administration route of medicines (injections), and affordability of medicines. Results: Significant changes in prescribing patterns were found. The average number of medicines and costs per-prescription dropped by about 50%. The percentage of prescriptions requiring antibiotics declined from 54% to 38%. The percentage of prescriptions requiring adrenal corticosteroid declined from 14% to 4%. The percentage of prescriptions requiring injections declined from 54% to 25%. Despite similar changing patterns, significant regional differences were observed. Conclusions: Significant changes in prescribing patterns are evident in township hospitals in China. Overprescription of antibiotics, injections and adrenal corticosteroids has been reduced. However, salient regional disparities still exist. Further studies are needed to determine potential shifts in the risk of the inappropriate use of medicines from primary care settings to metropolitan hospitals

Resolving Ultraviolet–Visible Spectra for Complex Dissolved Mixtures of Multitudinous Organic Matters in Aerosols

Light-absorbing organic aerosols, referred to as brown carbon (BrC), play a vital role in the global climate and air quality. Due to the complexity of BrC chromophores, the identified absorbing substances in the ambient atmosphere are very limited. However, without comprehensive knowledge of the complex absorbing compounds in BrC, our understanding of its sources, formation, and evolution mechanisms remains superficial, leading to great uncertainty in climatic and atmospheric models. To address this gap, we developed a constrained non-negative matrix factorization (NMF) model to resolve the individual ultraviolet–visible spectrum for each substance in dissolved organic aerosols, with the power of ultrahigh-performance liquid chromatography-diode array detector-ultrahigh-resolution mass spectrometry (UHPLC-DAD-UHRMS). The resolved spectra were validated by selected standard substances and validation samples. Approximately 40,000 light-absorbing substances were recognized at the MS1 level. It turns out that BrC is composed of a vast number of substances rather than a few prominent chromophores in the urban atmosphere. Previous understanding of the absorbing feature of BrC based on a few identified compounds could be biased. Weak-absorbing substances missed previously play an important role in BrC absorption when they are integrated due to their overwhelming number. This model brings the property exploration of complex dissolved organic mixtures to a molecular level, laying a foundation for identifying potentially significant compositions and obtaining a comprehensive chemical picture