Simultaneous extracting area and quantity of agricultural greenhouses in large scale with deep learning method and high-resolution remote sensing images.

Greenhouses are an important part of modern facility-based agriculture. While creating well-being for human society, greenhouses also bring negative impacts such as air pollution, soil pollution, and water pollution. Therefore, it is of great significance to obtain information such as the area and quantity of greenhouses. It is still a challenging task to find a low-cost, high-efficiency, and easy-to-use method for the dual extraction of greenhouse area and quantity on a large scale. In this study, relatively easy-to-obtain high-resolution Google Earth remote sensing images are used as the experimental data source, and an area and quantity simultaneous extraction framework (AQSEF) is constructed to extract both the area and quantity of greenhouses. The AQSEF uses UNet and YOLO v5 series networks as core operators to complete model training and prediction, and main components such as SWP, OSW&NMS and GCA complete data postprocessing. To evaluate the feasibility of our method, we take Beijing, China, as the research area and select multiple accuracy evaluation indicators in the two branches for accuracy verification. The results show that the mIoU, OA, Kappa, Recall and Precision with the best performance model in the area extraction branch can reach 0.931, 0.987, 0.867, 0.91 and 0.914, respectively. Additionally, the Recall, Precision, AP@0.5 and mAP@0.5: 0.95 values of the best performance model are 0.781, 0.891, 0.812 and 0.509, respectively, in the extraction of the quantity of greenhouses. Finally, in Beijing, the area covered by greenhouses is approximately 85.443 km2, and the quantity of greenhouses is approximately 155,464. With the proposed method, the time consumed for area extraction and quantity extraction is 6.73 h and 12.97 h, respectively. The experimental results show that AQSEF helps to overcome the spatiotemporal diversity of greenhouses and quickly and accurately map a high-spatial-resolution greenhouse distribution product within the research area.

Spatiotemporal analysis and potential impact factors of vegetation variation in the karst region of Southwest China.

The karst region of Southwest China is one of the largest in the world. Due to the effects of human activities and climate change, rocky desertification has become the primary ecological disaster which has significantly hindered the economic growth in Southwest China. In recent decades, the Chinese government has carried out a number of ecological restoration projects in Southwest China. This study aims to analyze the changes in vegetation coverage and its main driving factors in the Southwest China and the karst region of Southwest China from 2001 to 2015 through trend analysis, Hurst index correlation analysis, correlation analysis, and residual analysis. The results showed that (1) both Southwest China and the karst region of Southwest China experienced significant increasing trends in annual fractional vegetation cover, at a rate of 0.0028 year-1 and 0.0029 year-1, respectively; (2) the NDVI of the Southwest China and the karst region of Southwest China was stable, and the vegetation coverage areas showed low to medium fluctuations, accounting for 97.17% and 98.32% respectively; (3) the NDVI of the Southwest China and the karst region of Southwest China had strong sustainability, and the sustainable and improved regions account for 74.79% and 75.77% respectively; and (4) climate change had little influence on vegetation restoration, and human activities had a great influence on vegetation restoration. The relative contribution rates of human activities and climate change to vegetation NDVI changes in the Southwest China were 86% and 14%, respectively, and 90% and 10% in karst regions of Southwest China. Our findings contribute to a better understanding of the mechanisms of vegetation change in karst region and may provide scientific support for local vegetation restoration and conservation policies.

Microbiome diversity of cotton aphids (Aphis gossypii) is associated with host alternation.

Aphids are infected by a series of bacteria that can help them survive on specific host plants. However, the associations between aphids and these bacteria are not clear, and the bacterial communities in many aphid species are poorly characterized. Here, we investigated the bacterial communities of cotton aphids (Aphis gossypii) on 2 representative winter host plants and transferred to 3 summer host plants by 16S rDNA sequencing using the Illumina MiSeq platform. Our results revealed that the bacterial communities varied among cotton aphids on hibiscus, cotton aphids on pomegranate, cotton aphids on cotton transferred from hibiscus, cotton aphids on muskmelon transferred from hibiscus, cotton aphids on cucumber transferred from hibiscus,. The diversity and richness of the bacterial communities were significantly higher in aphids on muskmelon and aphids on cucumber than in the other treatments. There were two main factors influencing the distribution of internal bacterial OTUs revealed by principal component analysis, including the differences among Punicaceae, Malvaceae and Cucurbitaceae. There were 28 bacterial communities with significant differences between two arbitrary treatments, which could be grouped into 6 main clusters depending on relative abundance. Moreover, our results indicated that in addition to the obligate endosymbiont Buchnera, with a dominant position (> 52%), A. gossypii also harbored 3 facultative endosymbiotic bacteria (Serratia, Arsenophonus, and Wolbachia) and 3 possibly symbiotic bacteria (Acinetobacter, Pantoea, and Flavobacterium). There were several correspondences between the symbiotic bacteria in cotton aphids and the specific host plants of the aphids. This study provides a better understanding of the interactions among symbiotic bacteria, aphids and host plants, suggesting that the selection pressure on aphid bacterial communities is likely to be exerted by the species of host plants.

Exploring the long-term vegetation dynamics of different ecological zones in the farming-pastoral ecotone in northern China.

The vegetation in the farming-pastoral ecotone in northern China is influenced by both natural and anthropogenic factors and has undergone drastic changes in the past decades. The farming-pastoral ecotone is the transition zone from agriculture to animal husbandry. The ecological environment of this ecotone is complex and fragile. Most researches have primarily focused on the entire farming-pastoral ecotone, seldomly considering the differences between different ecological zones characterized by soil, climate, and biome conditions. Based on the long time series of leaf area index (LAI) data, meteorological data, and land-use dataset, this study analyzed LAI variation trends, the correlations between LAI and climate factors, and the impact of land-use type change on vegetation in the farming-pastoral ecotone in northern China. Moreover, this paper makes a full study of the changes of the whole study area from the perspective of the differences between different ecological zones. The results showed that over 36 years, areas with vegetation improvements were considerably larger than those with degradations. However, there were still 49.56% of the total area showing no significant vegetation change. There are differences in vegetation change and response to climate between the forest ecological zones and the grassland ecological zones. The vegetation improvement trends of the forest ecological zones were larger and more sensitive to temperature, while the vegetation improvements of the grassland ecological zones were relatively small, and were more sensitive to precipitation. Human activities promote LAI changes in areas close to the forest ecological zones. The change of land use indicates that the decrease of the overall natural vegetation area has not resulted in decreasing LAI. And there is a growing trend of woodland area in the grassland ecological zones. The study provides a theoretical basis for the management of the environment and vegetation in the farming-pastoral ecotone in northern China.

A novel way to calculate shortwave black carbon direct radiative effect.

Black carbon (BC) aerosol has a strong radiative forcing effect and significantly affects human beings and the environment. Therefore, it is important to quantitatively calculate its direct radiative effect (BC DRE) at the surface (SFC) and the top of the atmosphere (TOA). Current studies mainly use empirical formula methods or broadband methods to calculate BC DRE. However, these two methods do not consider the differences of sky diffuse light ratios in different wavelength bands. To overcome this problem, a new scheme named the multiband synthetic method is proposed to calculate blue sky albedo at MODIS narrow bands, and then, the blue sky albedo at the whole shortwave band is synthesized with these separate narrowband blue sky albedos. Based on BC concentration measured in Xuzhou over two years (from May 2014 to July 2016), aerosol optical depth (AOD) and microphysical parameters provided by AERONET, and the black sky albedo (BSA) and white sky albedo (WSA) provided by Google Earth Engine (GEE) products, shortwave BC DRE was calculated numerically with the use of the 6S radiative transfer model. The range of BC DRE computed by the multiband synthetic method at the TOA and SFC are 0.84 ± 0.08 to 3.27 ± 1.01W/m2 and -14.57 ± 4.53 to -4.31 ± 0.36W/m2. The shortwave BC DRE calculated by the multiband synthetic method was higher than that calculated with the broadband method and empirical formula method by 0.11% to 0.36% (at the SFC), 0.14% to 1.4% (at the SFC) and 3.4% to 10.1% (at the TOA), 5.5% to 15.8% (at the TOA), respectively. The BC DREs calculated by these three methods have small differences at the SFC. However, the difference was large at the TOA. The results of this study suggest that it is important to consider the differences between different narrow bands when calculating the broadband shortwave blue sky albedo.

Multichannel characteristics of absorbing aerosols in Xuzhou and implication of black carbon.

Black carbon (BC) is an important component of atmospheric aerosols; BC aerosols are produced mainly by the incomplete combustion of carbon-containing substances, and they have important effects on climate change, the atmospheric environment, and public health. Most of the existing research has focused on the single-band measurement results of BC aerosols. However, each band offers different information regarding the optical absorption properties of aerosols, such as enhanced light absorption by brown carbon in the 370 nm band. To bridge this research gap, the present study used BC concentration data measured by an AE42 aethalometer to analyze the multiband pollution characteristics of BC aerosols in Xuzhou city in China. An aethalometer model was established to quantitatively describe the concentrations of BC produced by solid and liquid fuels, and a concentration-weighted trajectory analysis was used to analyze the potential sources of BC aerosols in Xuzhou and their contributions to the total BC. The following results were obtained. (1) The BC concentration was high in spring and winter and low in summer and autumn, and the diurnal variation showed bimodal characteristics. (2) The difference among the aerosol concentrations in the seven bands was larger in autumn and winter than in spring and summer, and the contribution of brown carbon in autumn and winter was greater than that in spring and summer. (3) In winter, the solid source (coal and biomass combustion) of BC accounted for a large proportion of the total BC. (4) A source analysis of BC pollution days and BC clean days indicated different sources of BC pollution in different seasons. The results of this study provide a theoretical basis and realistic guide for the prevention and control of atmospheric pollution in Xuzhou and are anticipated to be of great significance for improving the regional and global atmospheric environment.

Williams-Campbell syndrome complicated with pulmonary hypertension and Type 2 respiratory failure: An adult case report.

Williams-Campbell syndrome, is a rare disorder characterized by a deficiency of cartilage in subsegmental bronchi, leading to distal airway collapse and bronchiectasis, which typically affects the fourth- to sixth-order bronchi. This article reported a 31-year-old female patient who was diagnosed with Williams-Campbell syndrome with pulmonary hypertension and Type 2 respiratory failure due to extensive cystic bronchiectasis. CT of the thorax showed the affected bronchi had characteristic ballooning on inspiration and collapse on expiration.

[Investigation of Multi-Angle Polarization Properties of Vegetation Based on RSP].

Polarization detection provides us with novel information to reflect the target attribute. Compared with traditional remote sensing methods, multi-angle polarization has relatively stable correlation and regularity. RSP(research scanning polarimeter)is an airborne prototype for the APS(aerosol polarimetery sensor) developed by the USA, which can provide with us the polarization detection information of 9 channels. We can get optical properties and physical characteristics of vegetation by analyzing stable multi-angle and multi-band polarization detection information from preprocessing scanning polarization data of flight test. In this paper, after making registration based on flight attitude information, a comparative analysis is made between characteristics of reflectance and polarization reflectance with visible light and near infrared band of the view zenith angles between--30 degree and 65 degree, based on dense area and sparse area(close to bare field) of vegetation. The results show that both dense area and sparse area demonstrate regular characteristics of polarization degree. The area close to hot spot area has highest reflectance energy. In contrast,. it has relatively least energy of polarization degree, which can prevent strong reflectance energy from influencing the stability of detector. Because the degree of polarization in dense area of vegetation is higher than that in sparse area at visible light band while that in concentration area of vegetation is lower than sparse area at near infrared light band, it shows that the visible light band information of dense area of vegetation that the sensor received is dominated by single scattering while the near infrared light band information of dense area of vegetation is dominated by multiple scattering.

Airborne validation of ground-object detection from polarized neutral-point atmosphere.

Based on the object's polarization effects, polarization is a newly emerging method in the field of remote sensing. Both objects and atmosphere have polarization effects, however, the atmosphere's polarization effects are much stronger than that of objects'. Consequently, atmosphere polarization effects will interfere or even cover objects' when observing with sensors. How to maximally eliminate the polarized effects generated by the atmosphere is a crucial problem in polarization remote sensing. Atmospheric neutral point is an area where the degree of atmosphere polarization is near to zero; therefore, if sensors are set up in this area, atmosphere polarization would be greatly eliminated, which is the main content of separating the effects between objects and atmosphere by its neutral point method. In this paper, after processing and analyzing the experimental data got from the first polarization remote sensing flight experiment with atmosphere neutral point, the degree of polarization images captured in neutral and non-neutral point area were obtained, and it can be seen that the main value of polarized degree of images got in neutral point area was obviously smaller than that in non-neutral point area. The results showed that the theory mentioned above was logical and practical. An innovation in our study is that the requirements needed in polarization remote sensing flight with neutral point were clarified. In the meantime, a qualitative conclusion was drawn that observing with longer wavelength is more applicable to polarization remote sensing.