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Radiation anomalies in optical remote sensing images frequently occur due to electronic issues within the image sensor or data transmission errors. These radiation anomalies can be categorized into several types, including CCD, StripeNoise, RandomCode1, RandomCode2, ImageMissing, and Tap. To ensure the retention of image data with minimal radiation issues as much as possible, this paper adopts a self-made radiation dataset and proposes a FlexVisionNet-YOLO network to detect radiation anomalies more accurately. Firstly, RepViT is used as the backbone network with a vision transformer architecture to better capture global and local features. Its multiscale feature fusion mechanism efficiently handles targets of different sizes and shapes, enhancing the detection ability for radiation anomalies. Secondly, a feature depth fusion network is proposed in the Feature Fusion part, which significantly improves the flexibility and accuracy of feature fusion and thus enhances the detection and classification performance of complex remote sensing images. Finally, Inner-CIoU is used in the Head part for edge regression, which significantly improves the localization accuracy by finely adjusting the target edges; Slide-Loss is used for classification loss, which enhances the classification robustness by dynamically adjusting the category probabilities and markedly improves the classification accuracy, especially in the sample imbalance dataset. Experimental results show that, compared to YOLOv8, the proposed FlexVisionNet-YOLO method improves precision, recall, mAP0.5, and mAP0.5:0.9 by 3.5%, 7.1%, 4.4%, and 13.6%, respectively. Its effectiveness in detecting radiation anomalies surpasses that of other models. [ABSTRACT FROM AUTHOR]

Coccidiosis, a parasitic disease caused by single or multiple Eimeria species, leads to significant economic losses in the poultry industry. The Eimeria life cycle includes schizogony, gametogony, and sporogony. To investigate the dynamics of gene expression and regulatory networks during the development of Eimeria acervulina, we employed time-course transcriptomics to rigorously compare the gene expression patterns between a precocious line (PL) and the wild type (WT) of E. acervulina. The results revealed that the PL enters into gametogony 12 h earlier than the WT, and both the PL and WT exhibited distinct clustering patterns during the development phase. A weighted gene co-expression network analysis (WGCNA) identified genes specifically expressed at four distinct developmental stages, schizogony, gametogony, sporulated oocysts, and unsporulated oocysts, clarifying the key biological processes at each stage. This study used global transcriptome profiling to elucidate molecular variations throughout the E. acervulina life cycle, providing critical insights into molecular characterization and valuable resources for investigating other apicomplexan parasites of public health importance. [ABSTRACT FROM AUTHOR]

Rabbit coccidiosis is caused by infection with one or, more commonly, several Eimeria species that parasitize the hepatobiliary ducts or intestinal epithelium of rabbits. Currently, there are eleven internationally recognized species of rabbit coccidia, with the complete mitochondrial (mt) genomes of six species commonly infecting rabbits having been sequenced and annotated. Eimeria kongi was initially discovered in 2011 and prompted a preliminary study on this species. Through traditional morphological analysis, E. kongi was identified as a novel species of rabbit coccidia. To further validate this classification, we sequenced and annotated its mitochondrial genome. The complete mt genome of E. kongi spans 6258 bp and comprises three cytochrome genes (cytb, cox1, cox3), fourteen gene fragments for the large subunit (LSU) rRNA, and nine gene fragments for the small subunit (SSU) rRNA, lacking transfer RNA (tRNA) genes. Moreover, phylogenetic analysis of the mitochondrial genome sequence of E. kongi revealed its clustering with six other species of rabbit coccidia into a monophyletic group. Additionally, E. irresidua and E. flavescens were grouped within the lineage lacking oocyst residuum, consistent with their morphological characteristics. Consistent with multiple molecular phylogenies, in this investigation, E. kongi was further confirmed as a new species of rabbit coccidia. Our research findings are of great significance for the classification of coccidia and for coccidiosis prevention and control in rabbits. [ABSTRACT FROM AUTHOR]

As an important means of improving positioning accuracy, block adjustment has been used in the improvement and assessment of accuracy for the Chinese Gaofen-7 (GF-7) satellite. However, there is little research on what factors affect accuracy without ground control points (GCPs). The correlation between accuracy and the images participating in the adjustment is not clear. This paper proposes the correlation coefficients and canonical correlation analysis between five accuracy indicators and three sets of ten adjustment factors, including topographic factors, participating image factors, and tie points (TPs) factors, to quantify the influence of adjustment factors on accuracy. Block adjustment without GCPs for GF-7 stereo imagery is verified in three study areas to evaluate the relationship between accuracy and adjustment factors. The results show that block adjustment without GCPs can improve direct positioning accuracy with an average improvement of 1.27 m in the planar direction and 0.13 m in the elevation direction. Moreover, plane accuracy is more easily affected by three sets of factors, while the influence on elevation accuracy is more balanced. The set of TP factors has the greatest influence on accuracy, and the image overlap is more critical than the image coverage area, number, and time periods. Topographic factors also play an important role, and the influence of the elevation factor with the highest canonical correlation coefficient (−0.71) is more significant than the other two factors, roughness, and slope. The results provide a reference for the improvement of adjustment accuracy without GCPs, the reasonable selection of adjustment images, the optimization of TPs, and the strategy of the partition processing of large-area block adjustment for GF-7 stereo imagery. [ABSTRACT FROM AUTHOR]

At present, some mapping satellites, such as GaoFen-7 and ZiYuan3-03, are equipped with both optical stereo cameras and laser altimeters that can synchronously obtain stereo images and sparse ground laser altimetry points (LAPs). To effectively improve the geometric accuracy of these satellite stereo images, this study proposed an integrated processing method for LAPs and stereo images derived from the same satellite. This method makes full use of the advantages of synchronously obtaining stereo images and LAPs, and designs measurement technology for accurate pixel coordinates of LAPs in stereo images, which works toward solving a technical difficulty that has restricted their integration to achieve higher accuracy. The method also constructs a combined block adjustment model of LAPs and stereo images. We selected 70 GaoFen-7 stereo images and 463 GaoFen-7 LAPs from Hebei Province, China, and 12 ZiYuan3-03 stereo images and 81 ZiYuan3-03 LAPs from Heilongjiang Province, China, to conduct integrated processing experiments. The vertical accuracy of the GaoFen-7 images in all types of terrain were improved substantially and reached the accuracy requirements of 1:10,000 (even 1:5000) scale mapping in China. The vertical accuracy of the ZiYuan3-03 images in various terrain areas were also improved markedly, satisfying the accuracy requirement of 1:50,000 scale mapping. These experimental results indicate that the working mode of synchronously obtaining LAPs and stereo images using the same satellite is advanced, and the proposed method is correct and effective. [ABSTRACT FROM AUTHOR]

Slope failures, subsidence, earthworks, consolidation of waste dumps, and erosion are typical active deformation processes that pose a significant hazard in current and abandoned mining areas, given their considerable potential to produce damage and affect the population at large. This work proves the potential of exploiting space-borne InSAR and airborne LiDAR techniques, combined with data inferred through a simple slope stability geotechnical model, to obtain and update inventory maps of active deformations in mining areas. The proposed approach is illustrated by analyzing the region of Sierra de Cartagena-La Union (Murcia), a mountainous mining area in southeast Spain. Firstly, we processed Sentinel-1 InSAR imagery acquired both in ascending and descending orbits covering the period from October 2016 to November 2021. The obtained ascending and descending deformation velocities were then separately post-processed to semi-automatically generate two active deformation areas (ADA) maps by using ADATool. Subsequently, the PS-InSAR LOS displacements of the ascending and descending tracks were decomposed into vertical and east-west components. Complementarily, open-access, and non-customized LiDAR point clouds were used to analyze surface changes and movements. Furthermore, a slope stability safety factor (SF) map was obtained over the study area adopting a simple infinite slope stability model. Finally, the InSAR-derived maps, the LiDAR-derived map, and the SF map were integrated to update a previously published landslides' inventory map and to perform a preliminary classification of the different active deformation areas with the support of optical images and a geological map. Complementarily, a level of activity index is defined to state the reliability of the detected ADA. A total of 28, 19, 5, and 12 ADAs were identified through ascending, descending, horizontal, and vertical InSAR datasets, respectively, and 58 ADAs from the LiDAR change detection map. The subsequent preliminary classification of the ADA enabled the identification of eight areas of consolidation of waste dumps, 11 zones in which earthworks were performed, three areas affected by erosion processes, 17 landslides, two mining subsidence zone, seven areas affected by compound processes, and 23 possible false positive ADAs. The results highlight the effectiveness of these two remote sensing techniques (i.e., InSAR and LiDAR) in conjunction with simple geotechnical models and with the support of orthophotos and geological information to update inventory maps of active deformation areas in mining zones. [ABSTRACT FROM AUTHOR]

To meet the demands of natural resource monitoring, land development supervision, and other applications for high-precision and high-frequency information extraction from constructed land change, this paper focused on automatic feature extraction and data processing optimization methods for newly constructed bare land based on remote sensing images. A generalized deep convolutional neural network change detection model framework integrating multi-scale information was developed for the automatic extraction of change information. To resolve the problems in the automatic extraction of new bare land parcels, such as mis-extractions and parcel fragmentation, a proximity evaluation model that integrates the confidence-based semantic distance and spatial distance between parcels and their overlapping area is proposed to perform parcel aggregation. Additionally, we propose a complete set of optimized processing techniques from pixel pre-processing to vector post-processing. The results demonstrated that the aggregation method developed in this study is more targeted and effective than ArcGIS for the automatically extracted land change parcels. Additionally, compared with the initial parcels, the total number of optimized parcels decreased by more than 50% and the false detection rate decreased by approximately 30%. These results indicate that this method can markedly reduce the overall data volume and false detection rate of automatically extracted parcels through post-processing under certain conditions of the model and samples and provide technical support for applying the results of automatic feature extraction in engineering practices. [ABSTRACT FROM AUTHOR]

GaoFen 7 (GF-7) is China's first submeter high-resolution stereo mapping satellite with dual-linear-array cameras and a laser altimeter system onboard for high-precision mapping. To further take advantage of the very high elevation accuracy of laser altimetry data and the high relative accuracy with stereo images, an innovative combined adjustment method for GF-7 stereo images with laser altimetry data is presented in this paper. In this method, two flexible and effective schemes were proposed to extract the elevation control point according to the registration of footprint images and stereo images and then utilized as vertical control in the block adjustment to improve the elevation accuracy without ground control points (GCPs). The validation experiments were conducted in Shandong, China, with different terrains. The results demonstrated that, after using the laser altimetry data, the root mean square error (RMSE) of elevation was dramatically improved from the original 2.15 m to 0.75 m, while the maximum elevation error was less than 1.6 m. Moreover, by integrating a few horizontal control points, the planar and elevation accuracy can be simultaneously improved. The results show that the method will be useful for reducing the need for field survey work and improving mapping efficiency. [ABSTRACT FROM AUTHOR]

Intensive and large-scale underground coal mining has caused geological disasters such as local ground subsidence, cracks and collapse in the Datong coalfield, China, inducing serious threats to local residents. Interferometric synthetic aperture radar (InSAR) has the capability of surface deformation detection with high precision in vast mountainous areas. DInSAR, stacking-InSAR and SBAS-InSAR are commonly used InSAR-related deformation analysis methods. They can provide effective support for mine ecological security monitoring and prevent disasters. We use the three methods to conduct the deformation observation experiments in the Datong coalfield. Sentinel-1A data from November 2020 to October 2021 are used. As a result, a total of 256 deformations in the Datong coalfield were successfully detected by the three methods, of which 218 are mining deformations, accounting for 85% of the total deformations. By comparing the results of the three methods, we found that DInSAR, stacking-InSAR, and SBAS-InSAR detected 130, 256, and 226 deformations in the Datong coalfield, respectively, while the deformations caused by coal mining were 128, 218, and 190. DInSAR results with long spatiotemporal baselines are seriously incoherent. SBAS-InSAR results of displacement rate are more precise than stacking-InSAR, and the mean standard deviation is 1.0 mm/a. However, for areas with lush vegetation or low coherence, SBAS-InSAR has poor performance. The detection deformation area results of DInSAR and SBAS-InSAR are subsets of stacking-InSAR. The displacement rates obtained by stacking-InSAR and SBAS-InSAR are consistent; the mean difference in the displacement rate between the two methods is 2.7 mm/a, and the standard deviation is 5.1 mm/a. The mining deformation locations and their shapes in the study area can be identified with high efficiency and power by stacking-InSAR. Therefore, with a comprehensive understanding of the advantages and limitations of the three methods, stacking-InSAR can be an effective and fast method to identify the level, location and range of mining deformation in lush mountainous areas. [ABSTRACT FROM AUTHOR]

The GF-7 satellite is China's first civil sub-meter resolution stereo mapping satellite, aiming at 1:10,000-scale mapping. To achieve this goal, apart from the stereo optical cameras that reach sub-meter resolution, the GF-7 satellite is equipped with a laser altimetry system capable of obtaining three-dimensional laser points (LPs) with high elevation accuracy. However, the combination of laser altimetry data and optical stereo images has not been thoroughly studied. In this paper, we exploit the images recorded by the highly integrated laser footprint cameras and propose a hierarchical phase correlation method based on a geographic pyramid for the registration of laser altimetry data and high-resolution optical stereo images, which lays a solid foundation for the following combined adjustment. Experiments show that the proposed registration method can automatically locate the LPs on high-resolution stereo images and meet the requirements of bundle adjustment. A series of bundle adjustment experiments were carried out, showing that laser altimetry data can significantly enhance the vertical accuracy of optical image stereo mapping and that elevation accuracy can reach roughly 1.0 m (RSME) without ground control points. Therefore, this study could be a good guide for global high-precision DSM acquisition with the GF-7 satellite. [ABSTRACT FROM AUTHOR]

The Gaofen-7 (GF-7) satellite uses a two-beam laser altimetry system in which each beam is equipped with a laser footprint camera (LFC) to provide geometric processing of the laser footprint images that assist in optical image stereo mapping. Because of the violent vibrations during launch and the difference in the environment before and after entering orbit, the key parameters for geometric processing of the laser footprint images may change, which will cause large geolocation errors. Therefore, it is essential to carry out on-orbit calibration and validation for the laser footprint cameras. This study first constructs a rigorous geometric positioning model for the LFC of the GF-7 satellite and analyses various error sources that affect the geometric positioning accuracy of laser footprint images. Then, a comprehensive calibration method, which effectively eliminates the distortion of the LFC optical system, and the positioning error caused by the long-period jitter of the satellite platform, is proposed based on the multi-scene images combined with image simulation. The proposed method can effectively eliminate various errors that affect the geometric positioning accuracy of the GF-7 laser footprint image. The internal geometric positioning accuracy of the calibrated LFC is better than 0.7 pixels, and the absolute geometric positioning accuracy is within 6.0 m after using precise post-processing orbital and attitude data. Our study will contribute to the processing and application of laser altimetry data from the GF-7 satellite. [ABSTRACT FROM AUTHOR]

The increasing frequency of human activities has accelerated changes in land use types and consequently affected the atmospheric environment. In this manuscript, we analyze the relationships between the particulate matter concentration and land use changes in the Beijing–Tianjin–Hebei (BTH) region, China, from 2015 to 2018. The experimental results indicate that (1) an improved sine function model can suitably fit the periodic changes in the particulate matter concentration, with the average R2 value increasing to 0.65 from the traditional model value of 0.49, while each model coefficient effectively estimates the change characteristics of each stage. (2) Among all land use types, the particulate matter concentrations in construction land and farmland are high, with a large annual difference between high and low values. The concentration decreases slowly in spring and summer but increases rapidly in autumn and winter. The concentrations in forestland and grassland are the lowest; the difference between high and low values is small for these land use types, and the concentration fluctuation pattern is relatively uniform. Natural sources greatly influence the concentration fluctuations, among which frequent dusty weather conditions in spring impose a greater influence on forestland and grassland than on the other land use types. (3) The landscape pattern of land use exerts a significant influence on the particulate matter concentration. Generally, the lower the aggregation degree of patches is, the higher the fragmentation degree is, the more complex the shape is, the higher the landscape abundance is, and the lower the particulate matter concentration is. The higher the construction land concentration is, the more easily emission sources can be aggregated to increase the particulate matter concentration. However, when forestland areas are suitably connected, this land use type can play a notable role in inhibiting particulate matter concentration aggravation. This conclusion is of great relevance to urban land use planning and sustainable development. [ABSTRACT FROM AUTHOR]

Featured Application: This paper proposed a novel TSPA-based Bayesian filtering multi-baseline phase unwrapping (MBPU) framework. This framework can provide a theoretical basis for future MBPU studies. The proposed framework can provide an effective theoretical basis for high-precision DEM acquisition. Phase unwrapping (PU) has been a key step in the processing of interferometric synthetic aperture radar (InSAR) data, and its processing accuracy will directly affect the reconstruction results of digital elevation models (DEMs). The traditional single-baseline (SB) PU must be calculated under continuity assumptions. However, multi-baseline (MB) PU can get rid of the limitation of continuity assumption, so reasonable results can be obtained in regions with large gradient changes. However, the poor noise robustness of MBPU has always been a key problem. To address this issue, we transplant three Bayesian filtering methods with a two-stage programming approach (TSPA), and propose corresponding MBPU models. First, we propose a gradient-estimation method based on the first step of TSPA, and then the corresponding PU model is determined according to different Bayesian filtering. Finally, the wrapped phase can be obtained by unwrapping, one by one, using an effective quality map based on heapsort. These methods can improve the robustness of the MBPU methods. More significantly, this paper establishes a novel TSPA-based Bayesian filtering MBPU framework for the first time. This is of great significance for broadening the research of MBPU. The proposed methods experiments on simulated and real MB InSAR datasets. From the results, we can see that the TSPA-based Bayesian filtering MBPU framework can significantly improve the robustness of the MBPU method. [ABSTRACT FROM AUTHOR]

Remote sensing data plays an important role in classifying land use/land cover (LULC) information from various sensors having different spectral, spatial and temporal resolutions. The fusion of an optical image and a synthetic aperture radar (SAR) image is significant for the study of LULC change and simulation in cloudy mountain areas. This paper proposes a novel feature-level fusion framework, in which the Landsat operational land imager (OLI) images with different cloud covers, and a fully polarized Advanced Land Observing Satellite-2 (ALOS-2) image are selected to conduct LULC classification experiments. We take the karst mountain in Chongqing as a study area, following which the features of the spectrum, texture, and space of the optical and SAR images are extracted, respectively, supplemented by the normalized difference vegetation index (NDVI), elevation, slope and other relevant information. Furthermore, the fused feature image is subjected to object-oriented multi-scale segmentation, subsequently, an improved support vector machine (SVM) model is used to conduct the experiment. The results showed that the proposed framework has the advantages of multi-source data feature fusion, high classification performance and can be applied in mountain areas. The overall accuracy (OA) was more than 85%, with the Kappa coefficient values of 0.845. In terms of forest, gardenland, water, and artificial surfaces, the precision of fusion image was higher compared to single data source. In addition, ALOS-2 data have a comparative advantage in the extraction of shrubland, water, and artificial surfaces. This work aims to provide a reference for selecting the suitable data and methods for LULC classification in cloudy mountain areas. When in cloudy mountain areas, the fusion features of images should be preferred, during the period of low cloudiness, the Landsat OLI data should be selected, when no optical remote sensing data are available, and the fully polarized ALOS-2 data are an appropriate substitute. [ABSTRACT FROM AUTHOR]

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. [ABSTRACT FROM AUTHOR]

The Ziyuan3-01 (ZY3-01) satellite is China's first civilian stereo surveying and mapping satellite to meet the 1:50,000 scale mapping requirements, and has been operated in orbit for 10 years. The boresight misalignment of the three-line camera (TLC) is an essential factor affecting the geolocation accuracy, which is a principal concern for stereo mapping satellites. However, the relative relationships of TLC are often regarded as fixed for the same ground scene in most traditional geometric calibrations, without considering the on-orbit long-periodic changes. In this paper, we propose a long-periodic method to analyze and estimate the boresight misalignments between three cameras, with the attitude estimation of a nadir (NAD) camera as the benchmark. Offsets and drifts of the three cameras were calculated and calibrated with different compensation models using scale invariant feature transform (SIFT) points as the ground control. Ten simultaneous NAD–Forward (FWD)–Backward (BWD) imagery of the ZY3-01 satellite acquired from 2012 to 2020 were selected to verify the long-periodic changes in TLC boresight misalignments. The results indicate that the boresight alignment angles of ZY3-01 TLC are dynamic during the long-periodic flight, but the structure of TLC is stable for the misalignments of both FWD and BWD within only 7 arc seconds, which can provide a positive reference for subsequent satellite design and long-periodic on-orbit geometric calibration. [ABSTRACT FROM AUTHOR]

Atmospheric particulate matter (PM) is a major air pollutant. PM2.5 and PM10 pose particularly serious threats to the ecological environment and human health. Vegetation plays an important role in reducing the concentration of particles. Based on a long time series of air quality, meteorological, and vegetation coverage data in the Beijing–Tianjin–Hebei (BTH) region, the present paper evaluated the influence at the overall and built-up area scales and quantified the process involved in the dry settlement of particles on vegetation based on a mathematical model. The experimental results showed that (1) the total amounts of PM10 reduced by vegetation in the BTH area were 505,200 t, 465,500 t, 477,200 t and 396,500 t in 2015, 2016, 2017 and 2018, respectively, and the total amount of PM2.5 was reduced by 19,400 t, 19,200 t, 16,400 t and 12,700 t, respectively. The annual reduction in PM10 and PM2.5 from 2015 to 2018 by vegetation in the BTH region showed a downwards trend, and the annual reduction was mainly caused by the significant decrease in PM concentration. (2) More than 80% of the reduction in annual yield was concentrated in May–September, and a large leaf area was the main reason for the largest yield reduction in the growing season. The efficiency of PM reduction in forestland was approximately five–seven times that in grassland, and the deciduous broad-leaved forest was the main driver of this reduction in each forest. (3) The reduction in PM10 by vegetation was approximately 30 times that of PM2.5. However, the reduction in PM2.5 by vegetation should not be ignored because PM2.5 has a stronger correlation with human production and living activities. Increasing the area and density of green space via afforestation, returning farmland to forest and giving full play to the self-purification function of green spaces are very important to reducing and controlling the concentration of PM. [ABSTRACT FROM AUTHOR]

This study described the on-orbit vicarious radiometric calibration of Chinese civilian high-resolution stereo mapping satellite ZY3-02 multispectral imager (MUX). The calibration was based on gray-scale permanent artificial targets, and multiple radiometric calibration tarpaulins (tarps) using a reflectance-based approach between July and September 2016 at Baotou calibration site in China was described. The calibration results reveal a good linear relationship between DN and TOA radiances of ZY3-02 MUX. The uncertainty of this radiometric calibration was 4.33%, indicating that radiometric coefficients of ZY3-02 MUX are reliable. A detailed discussion on the validation analysis of the comparison results between the different radiometric calibration coefficients is presented in this paper. To further validate the reliability of the three coefficients, the calibrated ZY3-02 MUX was compared with Landsat-8 Operational Land Imager (OLI). The results also indicate that radiometric characteristics of ZY3-02 MUX imagery are reliable and highly accurate for quantitative applications. [ABSTRACT FROM AUTHOR]

The GaoFen-7(GF-7) satellite is equipped with China's first laser altimeter for Earth observation; it has the capability of full waveform recording, which can obtain global high-precision three-dimensional coordinates over a wide range. The laser is inevitably affected by platform tremors, random errors in the laser pointing angle, laser state, and other factors, which further affect the measurement accuracy of the laser footprint. Therefore, evaluation of the satellite laser launch state is an important process. This study contributes to laser emission state evaluations based on the laser footprint image in terms of two main two aspects: (1) Monitoring changes in the laser pointing angle—laser pointing is closely related to positioning accuracy, which mainly results from monitoring the change in the laser spot centroid. We propose a threshold constraint algorithm that extracts the centroid of an ellipse-fitting spot. (2) Analysis of the energy distribution state—directly obtaining the parameters used in the traditional evaluation method is a challenge for the satellite. Therefore, an index suitable for evaluating the laser emissions state of the GF-7 satellite was constructed according to the data characteristics. Based on these methods, long time-series data were evaluated and analyzed. The experimental results show that the proposed method can effectively evaluate the emissions state of the laser altimeter, during which the laser pointing angle changes monthly by 0.434″. During each continuous operation of the laser, the energy state decreased gradually, with a small variation range; however, both were generally in a stable state. [ABSTRACT FROM AUTHOR]

China's first civilian, sub-meter, high-resolution stereo mapping satellite, GF-7, launched on 3 November 2019. Radiometric characterization of GF-7 multispectral imagery has been performed in this study. A relative radiometric accuracy evaluation of the GF-7 multispectral imagery was performed using several large uniform scenes, and the results showed that the accuracy is better than 2%. The absolute radiometric evaluation of the GF-7 satellite sensor was conducted at the Baotou and Dunhuang calibration sites, using the reflectance-based vicarious approach. The synchronous measurements of surface reflectance and atmospheric parameters were collected as the input for the radiative transfer model. The official radiometrically calibrated coefficient of the GF-7 multispectral imagery was evaluated with the predicted top-of-atmosphere (TOA) radiance from the radiative transfer model. The results indicated that the absolute radiometric accuracy of GF-7 multispectral imagery is better than 5%. In order to monitor the radiometric stability of the GF-7 satellite multispectral sensor, a relative and absolute radiometric accuracy assessment campaign should be performed several times a year. [ABSTRACT FROM AUTHOR]

Satellite laser altimetry can obtain sub-meter or even centimeter-scale surface elevation data over large areas, but it is inevitably affected by scattering caused by clouds, aerosols, and other atmospheric particles. This laser ranging error caused by scattering cannot be ignored. In this study, we systematically combined existing atmospheric scattering identification technology used in satellite laser altimetry and observed that the traditional algorithm cannot effectively estimate the laser multiple scattering of the GaoFen-7 (GF-7) satellite. To solve this problem, we used data from the GF-7 satellite to analyze the importance of atmospheric scattering and propose an identification scheme for atmospheric scattering data over land and water areas. We also used a look-up table and a multi-layer perceptron (MLP) model to identify and correct atmospheric scattering, for which the availability of land and water data reached 16.67% and 26.09%, respectively. After correction using the MLP model, the availability of land and water data increased to 21% and 30%, respectively. These corrections mitigated the low identification accuracy due to atmospheric scattering, which is significant for facilitating satellite laser altimetry data processing. [ABSTRACT FROM AUTHOR]

Based on measurement data from air quality monitoring stations, the spatio-temporal characteristics of the concentrations of particles with aerodynamic equivalent diameters smaller than 2.5 and 10 μm (PM2.5 and PM10, respectively) in the Beijing–Tianjin–Hebei (BTH) region from 2015 to 2018 were analysed at yearly, seasonal, monthly, daily and hourly scales. The results indicated that (1) from 2015 to 2018, the annual average values of PM2.5 and PM10 concentrations and the PM2.5/PM10 ratio in the study area decreased each year; (2) the particulate matter (PM) concentration in winter was significantly higher than that in summer, and the PM2.5/PM10 ratio was highest in winter and lowest in spring; (3) the PM2.5 and PM10 concentrations exhibited a pattern of double peaks and valleys throughout the day, reaching peak values at night and in the morning and valleys in the morning and afternoon; and (4) with the use of an improved sine function to simulate the change trend of the monthly mean PM concentration, the fitting R2 values for PM2.5 and PM10 in the whole study area were 0.74 and 0.58, respectively. Moreover, the high-value duration was shorter, the low-value duration was longer, and the concentration decrease rate was slower than the increase rate. [ABSTRACT FROM AUTHOR]

Digital Surface Model (DSM) derived from high resolution satellite imagery is important for various applications. GFDM is China's first civil optical remote sensing satellite with multiple agile imaging modes and sub-meter resolution. Its panchromatic resolution is 0.5 m and 1.68 m for multi-spectral images. Compared with the onboard stereo viewing instruments (0.8 m for forward image, 0.65 m for back image, and 2.6 m for back multi-spectrum images) of GF-7, a mapping satellite of China in the same period, their accuracy is very similar. However, the accuracy of GFDM DSM has not yet been verified or fully characterized, and the detailed difference between the two has not yet been assessed either. This paper evaluates the DSM accuracy generated by GFDM and GF-7 satellite imagery using high-precision reference DSM and the observations of Ground Control Points (GCPs) as the reference data. A method to evaluate the DSM accuracy based on regional DSM errors and GCPs errors is proposed. Through the analysis of DSM subtraction, profile lines, strips detection and residuals coupling differences, the differences of DSM overall accuracy, vertical accuracy, horizontal accuracy and the strips errors between GFDM DSM and GF-7 DSM are evaluated. The results show that the overall accuracy of both is close while the vertical accuracy is slightly different. When regional DSM is used as the benchmark, the GFDM DSM has a slight advantage in elevation accuracy, but there are some regular fluctuation strips with small amplitude. When GCPs are used as the reference, the elevation Root Mean Square Error (RMSE) of GFDM DSM is about 0.94 m, and that of GF-7 is 0.67 m. GF-7 DSM is more accurate, but both of the errors are within 1 m. The DSM image residuals of the GF-7 are within 0.5 pixel, while the residuals of GFDM are relatively large, reaching 0.8 pixel. [ABSTRACT FROM AUTHOR]

GF-6 is the first optical remote sensing satellite for precision agriculture observations in China. Accurate identification of the cloud in GF-6 helps improve data availability. However, due to the narrow band range contained in GF-6, Fmask version 3.2 for Landsat is not suitable for GF-6. Hence, this paper proposes an improved Fmask based on the spectral-contextual information to solve the inapplicability of Fmask version 3.2 in GF-6. The improvements are divided into the following six aspects. The shortwave infrared (SWIR) in the "Basic Test" is replaced by blue band. The threshold in the original "HOT Test" is modified based on the comprehensive consideration of fog and thin clouds. The bare soil and rock are detected by the relationship between green and near infrared (NIR) bands. The bright buildings are detected by the relationship between the upper and lower quartiles of blue and red bands. The stratus with high humidity and fog_W (fog over water) are distinguished by the ratio of blue and red edge position 1 bands. Temperature probability for land is replaced by the HOT-based cloud probability (LHOT), and SWIR in brightness probability is replaced by NIR. The average cloud pixels accuracy (TPR) of the improved Fmask is 95.51%. [ABSTRACT FROM AUTHOR]

The potential of Eimeria parasites as live vaccine vectors has been reported with successful genetic manipulation on several species like E. tenella, E. mitis and E. necatrix. Among seven Eimeria species infecting chickens, E. acervulina is a highly prevalent, moderately pathogenic species. Thus, it is valuable for the study of transfection and for use as a potential as vaccine vector. In this study, a plasmid containing expression cassette with enhanced yellow fluorescent protein (EYFP), red fluorescent protein (RFP) and 12 copies of extracellular domain of H9N2 avian influenza virus M2 (M2e) protein was used for the transfection. Nucleofected sporozoites were inoculated into birds through wing vein. Recombinant E. acervulina oocysts with 0.1% EYFP+ and RFP+ populations were collected from the feces of the inoculated birds. The fluorescent rate of transgenic parasites reached over 95% after nine successive propagations with a pyrimethamine selection in vivo and fluorescent-activated cell sorting (FACS) of progeny oocysts. The expression of M2e in the transgenic parasites (EaM2e) was confirmed by Western blot and its cytoplasm localization in sporozoites was displayed by an indirect immunofluorescent assay (IFA). Meanwhile, we found that the fecundity of EaM2e was equivalent to that of wild type E. acervulina (EaWT). Taken together, the stable transfection of E. acervulina was successfully established. Future studies will focus on whether transgenic E. acervulina can serve as a live vaccine vector. [ABSTRACT FROM AUTHOR]

Simple Summary: The excessive or improper use of antibiotics in chicken feed has led to the emergence of antibiotic-resistant bacteria, drug residues in the tissue, and other relevant issues, and this situation is severe in China. From 31 December 2020, antibiotics were banned for use as supplemental growth promoters in animal feed in China; therefore, antibiotic substitutes are urgently needed in China. People are searching for ideal antibiotic alternatives, and probiotics have proven their potential use for this. Our current trial aims to evaluate the effects of the Bacillus subtilis (B. subtilis) YW1 strain on laying hens, including the effects on performance, morphology, cecal microbiota, and intestinal barrier function. Our study showed that orally administering laying hens with probiotic B. subtilis cannot significantly improve their overall egg production, can induce a healthier microbiota composition characterized by a higher ratio of beneficial bacteria, and strengthens the physical barrier function of the intestine by inducing a higher expression of the tight junction protein. This makes it a valid probiotic alternative to antibiotics, and also a reference strain for clinical application in the poultry industry. We investigated the efficacy of a single bacterium strain, Bacillus subtilis (B. subtilis) YW1, on the performance, morphology, cecal microbiota, and intestinal barrier function of laying hens. A total of 216 28-week-old Hy-line Brown laying hens were divided into three dietary treatment groups, with six replicates of 12 birds each for 4 weeks. The control group (Ctr) was fed a basal diet and the treatment groups, T1 and T2, were fed a basal diet supplemented with B. subtilis at a dose rate of 5 × 108 CFU/kg and 2.5 × 109 CFU/kg, respectively. Dietary supplementation with B. subtilis did not significantly affect overall egg production in both groups, with no obvious changes in average egg weight and intestine morphology. B. subtilis administration also improved the physical barrier function of the intestine by inducing significantly greater expression levels of the tight junction protein occludin in T1 (p = 0.07) and T2 (p < 0.05). Further, supplementation with B. subtilis effectively modulated the cecal microbiota, increasing the relative level of beneficial bacteria at the genus level (e.g., Bifidobacterium p < 0.05, Lactobacillus p = 0.298, Bacillus p = 0.550) and decreasing the level of potential pathogens (e.g., Fusobacterium p < 0.05, Staphylococcus p < 0.05, Campylobacter p = 0.298). Overall, B. subtilis YW1 supplementation cannot significantly improve the egg production; however, it modulated the cecal microbiota towards a healthier pattern and promoted the mRNA expression of the tight junction protein occludin in laying hens, making B. subtilis YW1 a good probiotic candidate for application in the poultry industry, and further expanding the resources of strains of animal probiotics. [ABSTRACT FROM AUTHOR]

The GF-7 satellite is China's first high-resolution stereo mapping satellite that reaches sub-meter resolution, equipped with new-type payloads, such as an area array footprint camera that can achieve synchronization acquisition of laser spots. When the satellite is in space, the variation of camera parameters may occur due to launch vibration and environmental changes, and on-orbit geometric calibration thereby must be made. Coupled with the data from the GF-7 satellite, this paper constructs a geometric imaging model of the area array footprint camera based on the two-dimensional direction angle, and proposes a coarse-to-fine "LPM-SIFT + Phase correlation" matching strategy for the automatic extraction of calibration control points. The single-image calibration experiment shows that the on-orbit geometric calibration model of the footprint camera constructed in this paper is correct and effective. The matching method proposed is used to register the footprint images with the DOM (Digital Orthophoto Map) reference data to obtain dense control points. Compared with the calibration result using a small number of manually collected control points, the root mean square error (RMSE) of the residual of the control points is improved from half a pixel to 1/3, and the RMSE of the same orbit checkpoints in the image space is improved from 1 pixel to 0.7. It can be concluded that using the coarse-to-fine image matching method proposed in this paper to extract control points can significantly improve the on-orbit calibration accuracy of the footprint camera on the GF-7 satellite. [ABSTRACT FROM AUTHOR]

Slope and roughness are basic geophysical properties of terrain surface, and also sources of error in satellite laser altimetry systems. The full-waveform satellite laser altimeter records the complete echo waveform backscattered from the target surface worldwide, so it may be used for both range measurement and inversion analysis of geometric parameters of the target surface. This paper proposes a new method for inversion of slope and roughness of the bare or near-bare terrain within laser footprint using full-waveform satellite laser altimeter data, Shuttle Radar Topographic Mission (SRTM) and topographic prior knowledge. To solve the non-uniqueness of the solution to the inversion problem, this paper used the SRTM and airborne Light Detection and Ranging (LiDAR) data in North Rhine-Westphalia, Germany, to establish a priori hypothesis about real information of topographic parameters. Then, under the constraints of prior hypothesis, the theoretical formulas and rules for slope and roughness inversion using the pulse-width broadening knowledge of satellite laser altimeter echo full-waveform were developed. Finally, based on the full-waveform data from the Geoscience Laser Altimeter System (GLAS) that was borne on ICE, Cloud, and Land Elevation Satellite (ICESat) and SRTM in the West Valley City, Utah and Jackson City, Wyoming, United States of America, the inversion was carried out. The experiment compares the results of proposed method with those of existing ones and evaluates the inversion results using high precision terrain slope and roughness information, which indicates that our proposed method is superior to the state-of-the-art methods, and the inversion accuracy for slope is 0.667 ° (Mean Absolute Error, MAE) and 1.054 ° (Root Mean Square Error, RMSE), the inversion accuracy for roughness is 0.171 m (MAE) and 0.250 m (RMSE). [ABSTRACT FROM AUTHOR]

Satellite platform microvibration is a common phenomenon in earth observation satellite orbits that directly affects the imaging quality and accuracy of surveying and mapping. With the continuous improvement in the spatial resolution, the influence of satellite platform microvibration on image geometric accuracy is becoming increasingly significant. High-precision microvibration detection and compensation are key technologies for eliminating image distortion and location deviation caused by satellite platform microvibration. In this paper, the microvibration detection methods of different satellite platforms are summarized, and the verification and analysis are performed on the data downloaded from the Resource-3 satellite (ZY-3) platform, to provide technical support for subsequent refined processing of satellite attitude. [ABSTRACT FROM AUTHOR]

Trajectory big data have significant applications in many areas, such as traffic management, urban planning and military reconnaissance. Traditional visualization methods, which are represented by contour maps, shading maps and hypsometric maps, are mainly based on the spatiotemporal information of trajectories, which can macroscopically study the spatiotemporal conditions of the entire trajectory set and microscopically analyze the individual movement of each trajectory; such methods are widely used in screen display and flat mapping. With the improvement of trajectory data quality, these data can generally describe information in the spatial and temporal dimensions and involve many other attributes (e.g., speed, orientation, and elevation) with large data amounts and high dimensions. Additionally, these data have relatively complicated internal relationships and regularities, whose analysis could cause many troubles; the traditional approaches can no longer fully meet the requirements of visualizing trajectory data and mining hidden information. Therefore, diverse visualization methods that present the value of massive trajectory information are currently a hot research topic. This paper summarizes the research status of trajectory data-visualization techniques in recent years and extracts common contemporary trajectory data-visualization methods to comprehensively cognize and understand the fundamental characteristics and diverse achievements of trajectory-data visualization. [ABSTRACT FROM AUTHOR]

Vivid main structure and rich texture detail are important factors with which to determine the quality of high-resolution images after super-resolution (SR) reconstruction. Owing to the loss of high-frequency information in the process of SR reconstruction and the limitation of the accurate estimation of the unknown information in the inversion process, a gap still exists between the high-resolution image and the real image. The main structure can better preserve the edge structure of the image, and detail boosting can compensate for the missing high-frequency information in the reconstruction process. Therefore, a novel single remote-sensing image SR reconstruction method based on multilevel main structure and detail boosting (MMSDB-SR) is put forward in this paper. First, the multilevel main structure was obtained based on the decomposition of the remote-sensing image through use of the relative total variation model. Subsequently, multilevel texture detail information was obtained by a difference process. Second, the multilevel main structure and texture detail were reconstructed separately. The detail-boosting function was used to compensate for the missing high-frequency details in the reconstruction process. Finally, the high-resolution remote-sensing image with clear edge and rich texture detail can be obtained by fusing the multilevel main structure and texture-detail information. The experimental results show that the reconstructed high-resolution image has high clarity, high fidelity, and multi-detail visual effects, and the objective evaluation index exhibits significant improvement. Actual results show an average gain in entropy of up to 0.34 dB for an up-scaling of 2. Real results show an average gain in enhancement measure evaluation of up to 2.42 for an up-scaling of 2. The robustness and universality of the proposed SR method are verified. [ABSTRACT FROM AUTHOR]

Successfully launched on 30 May 2016, ZY3-02 is the first Chinese surveying and mapping satellite equipped with a lightweight laser altimeter. Calibration is necessary before the laser altimeter becomes operational. Laser footprint location prediction is the first step in calibration that is based on ground infrared detectors, and it is difficult because the sample frequency of the ZY3-02 laser altimeter is 2 Hz, and the distance between two adjacent laser footprints is about 3.5 km. In this paper, we build an on-orbit rigorous geometric prediction model referenced to the rigorous geometric model of optical remote sensing satellites. The model includes three kinds of data that must be predicted: pointing angle, orbit parameters, and attitude angles. The proposed method is verified by a ZY3-02 laser altimeter on-orbit geometric calibration test. Five laser footprint prediction experiments are conducted based on the model, and the laser footprint prediction accuracy is better than 150 m on the ground. The effectiveness and accuracy of the on-orbit rigorous geometric prediction model are confirmed by the test results. The geolocation is predicted precisely by the proposed method, and this will give a reference to the geolocation prediction of future land laser detectors in other laser altimeter calibration test., Competing Interests: The authors declare no conflict of interest.