Influences of environmental factors on the dissipation of green tides in the Yellow Sea, China.

Green tides attack the Yellow Sea every year since 2007 and have caused substantial financial loss. Based on Haiyang-1C/Coastal zone imager (HY-1C/CZI) and Terra/MODIS satellite images, the temporal and spatial distribution of green tides floating in the Yellow Sea during 2019 was extracted. The relationships between the growth rate of the green tides and the environmental factors including sea surface temperature (SST), photosynthetically active radiation (PAR), sea surface salinity (SSS), nitrate and phosphate during the green tides' dissipation phase has been detected.

Important role of precipitation in controlling a more uniform spring phenology in the Qinba Mountains, China.

Under global warming, the gradual pattern of spring phenology along elevation gradients (EG) has significantly changed. However, current knowledge on the phenomenon of a more uniform spring phenology is mainly focused on the effect of temperature and neglected precipitation. This study aimed to determine whether a more uniform spring phenology occurs along EG in the Qinba Mountains (QB) and explore the effect of precipitation on this pattern.

A high-precision aerosol retrieval algorithm for FY-3D MERSI-II images.

The Medium Resolution Spectral Imager-II (MERSI-II) onboard the recently launched Chinese Fengyun-3D (FY-3D) satellite has great capability in detecting global aerosols as it includes aerosol bands similar to Moderate Resolution Imaging Spectroradiometer (MODIS). However, to date, aerosol retrieval based on MERSI-II is still limited to dark target regions and there is no official aerosol products for the MERSI-II. This study focuses on developing a high-precision algorithm to retrieve aerosol optical depth (AOD) suitable for entire land areas (except snow/ice and inland waters) based on MERSI-II measurements.

Automatic counting of rapeseed inflorescences using deep learning method and UAV RGB imagery.

Flowering is a crucial developing stage for rapeseed ( L.) plants. Flowers develop on the main and branch inflorescences of rapeseed plants and then grow into siliques.

Exploring risk transfer of human brucellosis in the context of livestock agriculture transition: A case study in Shaanxi, China.

With the booming of worldwide agriculture intensification, brucellosis, one of the most neglected zoonotic diseases, has become an increasing challenge for global public health. Although the transmission patterns of human brucellosis (HB) have been studied in many regions, the dynamic transfer processes of risk and its driving factors remain poorly understood, especially in the context of agricultural intensification. This study attempted to explore the risk transfer of HB between the exact epidemic areas and the neighboring or distant low-risk areas to explain the impact of livestock agriculture intensification and foodborne infections on the transmission of HB in Shaanxi Province as a case study.

Simultaneous profiling of dust aerosol mass concentration and optical properties with polarized high-spectral-resolution lidar.

Dust particles originating from arid desert regions can be transported over long distances, presenting severe risks to climate, environment, social economics, and human health at the source and downwind regions. However, there has been a dearth of continuous diurnal observations of vertically resolved mass concentration and optical properties of dust aerosols, which hinders our understanding of aerosol mixing, stratification, aerosol-cloud interactions, and their impacts on the environment. To fill the gap of the insufficient observations, to the best of our knowledge, this work presents the first high-spectral-resolution lidar (HSRL) observation providing days of continuous profiles of the mass concentration, along with particle linear depolarization ratio (PLDR), backscattering coefficient, extinction coefficient and lidar ratio (LR), simultaneously.

Analysing the global and local spatial associations of medical resources across Wuhan city using POI data.

Background: There is a sharp contradiction between the supply and demand of medical resources in the provincial capitals of China. Understanding the spatial patterns of medical resources and identifying their spatial association and heterogeneity is a prerequisite to ensuring that limited resources are allocated fairly and optimally, which, along with improvements to urban residents' quality of life, is a key aim of healthy city planning. However, the existing studies on medical resources pattern mainly focus on their spatial distribution and evolution characteristics, and lack the analyses of the spatial co-location between medical resources from the global and local perspectives.

Evaluation and comparison of VIIRS dark target and deep blue aerosol products over land.

The dark target (DT) and deep blue (DB) algorithms have been applied to the VIIRS to construct a long-term climate data recording of atmospheric aerosols. This study provides the first evaluation and comparison of two updated VIIRS aerosol products over global land based on Version 3 Level 1.5 AERONET measurements.

Sulfur dioxide may predominate in the adverse effects of ambient air pollutants on semen quality among the general population in Hefei, China.

Previous studies have reported potential adverse effects of exposure to ambient air pollutants on semen quality in infertile men, but studies on the general population have been limited and inconsistent, and the pollutants that play a major role remain unclear. This study aimed to explore the potential association between exposure to six air pollutants (PM, PM, NO, SO, O and CO) during different sperm development periods and semen quality among the general population, and to explore the interaction between different air pollutant exposures. We included 1515 semen samples collected from the Human Sperm Bank.

Land cover change in global drylands: A review.

As a sensitive region, identifying land cover change in drylands is critical to understanding global environmental change. However, the current findings related to land cover change in drylands are not uniform due to differences in data and methods among studies. We compared and judged the spatial and temporal characteristics, driving forces, and ecological effects by identifying the main findings of land cover change in drylands at global and regional scales (especially in China) to strengthen the overall understanding of land cover change in drylands.

Spatiotemporal impact of non-pharmaceutical interventions against COVID-19 on the incidence of infectious diarrhea in Xi'an, China.

Background: Non-pharmaceutical interventions (NPIs) against COVID-19 may prevent the spread of other infectious diseases. Our purpose was to assess the effects of NPIs against COVID-19 on infectious diarrhea in Xi'an, China.

Methods: Based on the surveillance data of infectious diarrhea, and the different periods of emergence responses for COVID-19 in Xi'an from 2011 to 2021, we applied Bayesian structural time series model and interrupted time series model to evaluate the effects of NPIs against COVID-19 on the epidemiological characteristics and the causative pathogens of infectious diarrhea.

An interpretable approach for automatic aesthetic assessment of remote sensing images.

The increase of remote sensing images in recent decades has resulted in their use in non-scientific fields such as environmental protection, education, and art. In this situation, we need to focus on the aesthetic assessment of remote sensing, which has received little attention in research. While according to studies on human brain's attention mechanism, certain areas of an image can trigger visual stimuli during aesthetic evaluation.

Combing remote sensing information entropy and machine learning for ecological environment assessment of Hefei-Nanjing-Hangzhou region, China.

Urban ecological environment is the basis of citizens' survival and development. A rapid and objective urban ecological environment assessment (UEEA) plays an important role in the urban sustainable development and environment protection. This study established an improved urban ecological comfort index (UECI), which is based on our previous UECI and fully composed of four remote sensing indicators: normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), land surface temperature (LST), and aerosol optical depth (AOD), representing the greenness, dryness, heat, and atmospheric turbidity, respectively.

Population flow based spatial-temporal eigenvector filtering modeling for exploring effects of health risk factors on COVID-19.

The COVID-19 pandemic has had great impact on human health and social economy. Several studies examined spatial and temporal patterns of health risk factors associated with COVID-19, but population flow spillover effect has not been sufficiently considered. In this paper, a population flow-based spatial-temporal eigenvector filtering model (FLOW-ESTF) was developed to consider spatial-temporal patterns and population flow connectivity simultaneously.

A hybrid generative adversarial network for weakly-supervised cloud detection in multispectral images.

Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth observation. Clouds in optical remote sensing images seriously affect the visibility of the background and greatly reduce the usability of images for land applications. Traditional methods based on thresholding, multi-temporal or multi-spectral information are often specific to a particular satellite sensor.

Effects of green spaces on alleviating mortality attributable to PM in China.

Increasing research suggested that green spaces are associated with many health benefits, but evidence for the quantitative relationship between green spaces and mortality attributable to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM) is limited. We collected disease-specific mortality and PM data for a period of 4 years (2015-2018) along with green space data for an 8-year duration (2010-2017) in 31 provincial-level administrative regions of China.

Clustering by measuring local direction centrality for data with heterogeneous density and weak connectivity.

Clustering is a powerful machine learning method for discovering similar patterns according to the proximity of elements in feature space. It is widely used in computer science, bioscience, geoscience, and economics. Although the state-of-the-art partition-based and connectivity-based clustering methods have been developed, weak connectivity and heterogeneous density in data impede their effectiveness.

Decoupling relationship analysis between urbanization and carbon emissions in 33 African countries.

Global warming is a serious environmental problem facing the world in the 21st century. Carbon dioxide, an important greenhouse gas, is the driver of global warming. Rapid urbanization has not only improved the quality of life, but has also led to radical increases in carbon emissions.

Assessing the impact of drought-land cover change on global vegetation greenness and productivity.

Drought-land cover change (D-LCC) is considered to be an important stress factor that affects vegetation greenness and productivity (VG&P) in global terrestrial ecosystems. Understanding the effects of D-LCC on VG&P benefits the development of terrestrial ecosystem models and the prediction of ecosystem evolution. However, till today, the mechanism remains underexploited.

Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes.

As a promising method, unmanned aerial vehicle (UAV) multispectral remote sensing (RS) has been extensively studied in precision agriculture. However, there are numerous problems to be solved in the data acquisition and processing, which limit its application. In this study, the Micro-MCA12 camera was used to obtain images at different altitudes.

Spatio-temporal association mining of intercity PM pollution: Hubei Province in China as an example.

The complex interaction between emissions, meteorology, and atmospheric chemistry makes accurate predictions of particulate pollution difficult. Advanced data mining techniques can reveal potential laws, providing new possibilities for understanding the evolution and causes of air pollution. Based on the Granger method and block modeling analysis, this paper explored the intercity spillover effects of hourly PM in Hubei Province, China, to determine the specific role (i.

ULMR: An Unsupervised Learning Framework for Mismatch Removal.

Due to radiometric and geometric distortions between images, mismatches are inevitable. Thus, a mismatch removal process is required for improving matching accuracy. Although deep learning methods have been proved to outperform handcraft methods in specific scenarios, including image identification and point cloud classification, most learning methods are supervised and are susceptible to incorrect labeling, and labeling data is a time-consuming task.

Combining spectral and wavelet texture features for unmanned aerial vehicles remote estimation of rice leaf area index.

Estimating the crop leaf area index (LAI) accurately is very critical in agricultural remote sensing, especially in monitoring crop growth and yield prediction. The development of unmanned aerial vehicles (UAVs) has been significant in recent years and has been extensively applied in agricultural remote sensing (RS). The vegetation index (VI), which reflects spectral information, is a commonly used RS method for estimating LAI.