The Research And Application Of Remote Sensing Monitoring Method Of Actual Irrigated Area

The value of actual irrigated area is an important indicator of irrigation water management, but due to wide space range of irrigated district, ground manual monitoring is very difficult to achieve. Remote sensing methods have a wide rapid coverage, high efficiency, real-time, objective and other advantages, which can be used to solve the difficulties in monitoring irrigated area. In this paper, a remote sensing monitoring method of irrigated area based on modified perpendicular drought index (MPDI) is researched and the differential thresholds for distinguishing irrigation are analyzed and proposed. The method was applied to 5 rounds of actual irrigated area monitoring in Hetao irrigated district, inner Monglia, China., using the satellite images of HJ1A/1B CCD, China, and verified by ground tests. The results show that the method is of high precision, and can provide help for enhancing the management level of irrigated districts

Negative effects of abamectin on soil microbial communities in the short term

With the widespread use of abamectin in agriculture, there is increasing urgency to assess the effects of abamectin on soil microorganisms. Here, we treated plant–soil microcosms with abamectin at concentrations of 0.1 and 1.0 mg/kg and quantified the impacts of abamectin on bulk and rhizosphere soil microbial communities by shotgun metagenomics after 7 and 21 days of exposure. Although abamectin was reported to be easily degradable, it altered the composition of the soil microbial communities, disrupted microbial interactions, and decreased community complexity and stability after 7 days of exposure. After treatment with abamectin at a concentration of 1.0 mg/kg, some opportunistic human diseases, and soil-borne pathogens like Ralstonia were enriched in the soil. However, most ecological functions in soil, particularly the metabolic capacities of microorganisms, recovered within 21 days after abamectin treatment. The horizontal and vertical gene transfer under abamectin treatments increased the levels of antibiotic resistance genes dissemination. Overall, our findings demonstrated the negative effects of abamectin on soil ecosystems in the short-term and highlight a possible long-term risk to public and soil ecosystem health associated with antibiotic resistance genes dissemination

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Aim: The detection and segmentation of cerebral microbleeds (CMBs) images are the focus of clinical diagnosis and treatment. However, segmentation is difficult in clinical practice, and missed diagnosis may occur. Few related studies on the automated segmentation of CMB images have been performed, and we provide the most effective CMB segmentation to date using an automated segmentation system.Materials and Methods: From a research perspective, we focused on the automated segmentation of CMB targets in susceptibility weighted imaging (SWI) for the first time and then constructed a deep learning network focused on the segmentation of micro-objects. We collected and marked clinical datasets and proposed a new medical micro-object cascade network (MMOC-Net). In the first stage, U-Net was utilized to select the region of interest (ROI). In the second stage, we utilized a full-resolution network (FRN) to complete fine segmentation. We also incorporated residual atrous spatial pyramid pooling (R-ASPP) and a new joint loss function.Results: The most suitable segmentation result was achieved with a ROI size of 32 × 32. To verify the validity of each part of the method, ablation studies were performed, which showed that the best segmentation results were obtained when FRN, R-ASPP and the combined loss function were used simultaneously. Under these conditions, the obtained Dice similarity coefficient (DSC) value was 87.93% and the F2-score (F2) value was 90.69%. We also innovatively developed a visual clinical diagnosis system that can provide effective support for clinical diagnosis and treatment decisions.Conclusions: We created the MMOC-Net method to perform the automated segmentation task of CMBs in an SWI and obtained better segmentation performance; hence, this pioneering method has research significance

Daily Evapotranspiration Estimation at the Field Scale: Using the Modified SEBS Model and HJ-1 Data in a Desert-Oasis Area, Northwestern China

Accurate continuous daily evapotranspiration (ET) at the field scale is crucial for allocating and managing water resources in irrigation areas, particularly in arid and semi-arid regions. The authors integrated the modified perpendicular drought index (MPDI) as an indicator of water stress into surface energy balance system (SEBS) to improve ET estimation under water-limited conditions. The new approach fed with Chinese satellite HJ-1 (environmental and disaster monitoring and forecasting with a small satellite constellation) images was used to map daily ET on the desert-oasis irrigation fields in the middle of the Heihe River Basin. The outputs, including instantaneous sensible heat flux (H) and daily ET from the MPDI-integrated SEBS and the original SEBS model, were compared with the eddy covariance observations. The results indicate that the MPDI-integrated SEBS significantly improved the surface turbulent fluxes in water-limited regions, especially for sparsely vegetated areas. The new approach only uses one optical satellite data and meteorological data as inputs, providing a considerable operational improvement for ET mapping. Moreover, HJ-1 high-resolution data promised continuous daily ET at the field scale, which helps in understanding the corresponding relationships among field, crop, and water consumption. Such detailed ET information can greatly serve water resources management in the study area as well as other arid and semi-arid regions

Continuous Daily Evapotranspiration Estimation at the Field-Scale over Heterogeneous Agricultural Areas by Fusing ASTER and MODIS Data

Continuous daily evapotranspiration (ET) monitoring at the field-scale is crucial for water resource management in irrigated agricultural areas in arid regions. Here, an integrated framework for daily ET, with the required spatiotemporal resolution, is described. Multi-scale surface energy balance algorithm evaluations and a data fusion algorithm are combined to optimally exploit the spatial and temporal characteristics of image datasets, collected by the advanced space-borne thermal emission reflectance radiometer (ASTER) and the moderate resolution imaging spectroradiometer (MODIS). Through combination with a linear unmixing-based method, the spatial and temporal adaptive reflectance fusion model (STARFM) is modified to generate high-resolution ET estimates for heterogeneous areas. The performance of this methodology was evaluated for irrigated agricultural fields in arid and semiarid areas of Northwest China. Compared with the original STARFM, a significant improvement in daily ET estimation accuracy was obtained by the modified STARFM (overall mean absolute percentage error (MAP): 12.9% vs. 17.2%; root mean square error (RMSE): 0.7 mm d−1 vs. 1.2 mm d−1). The modified STARFM additionally preserved more spatial details than the original STARFM for heterogeneous agricultural fields, and provided field-to-field variability in water use. Improvements were further evident in the continuous daily ET, where the day-to-day dynamics of ET estimates were captured. ET data fusion provides a unique means of monitoring continuous daily crop ET values at the field-scale in agricultural areas, and may have value in supporting operational water management decisions

Familiarity Bias and Economic Decisions: Evidence from A Survey Experiment

International audienceThis paper provides experimental evidence that people in China have strong familiarity bias identified by hometown and education locations when making merger and acquisition decisions. Emotions and genders could affect the role of familiarity bias in merger and acquisition decisions

Daily Evapotranspiration Estimation Using HJ-1 Data for Irrigation Water Management in a Desert-Oasis Irrigation District, Northwest China

Irrigation of agricultural land is the main water consumer in the arid and semiarid regions. The accurate time series of daily evapotranspiration (ET) at the field scale is crucial for irrigation water management. Here, we presented an integrated approach to field-scale ET mapping by combing METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) with trapezoidal framework of vegetation fraction and land surface temperature (fv-Trad). This approach fed with Chinese satellite HJ-1 (environmental and disaster monitoring and forecasting with a small satellite constellation) images was used to map daily ET over the desert-oasis irrigation fields in the middle of the Heihe River Basin, Northwest China. The results showed that time series of daily ET derived from HJ-1 were well consistent with the in situ measurements (coefficient of determination (R2) of 0.95, root mean square error (RMSE) of 0.31 mmd–1, mean absolute percentage error (MAPE) of 12.0% at Daman station; R2 of 0.89, RMSE of 0.16 mmd–1, and MAPE of 13.2% at Huazhaizi station). The rapid variation of ET could be precisely captured by HJ-1, especially when rainfall or irrigation events occurred between successive acquisitions of satellite data. Meanwhile, the spatiotemporal variation of monthly ET is closely related to crop growth. Daily ET at field scale will support a variety of local interests in water use and irrigation management for both planning and regulatory purposes

Daily Evapotranspiration Estimation Using HJ-1 Data for Irrigation Water Management in a Desert-Oasis Irrigation District, Northwest China

Irrigation of agricultural land is the main water consumer in the arid and semiarid regions. The accurate time series of daily evapotranspiration (ET) at the field scale is crucial for irrigation water management. Here, we presented an integrated approach to field-scale ET mapping by combing METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) with trapezoidal framework of vegetation fraction and land surface temperature (fv-Trad). This approach fed with Chinese satellite HJ-1 (environmental and disaster monitoring and forecasting with a small satellite constellation) images was used to map daily ET over the desert-oasis irrigation fields in the middle of the Heihe River Basin, Northwest China. The results showed that time series of daily ET derived from HJ-1 were well consistent with the in situ measurements (coefficient of determination (R2) of 0.95, root mean square error (RMSE) of 0.31 mmd–1, mean absolute percentage error (MAPE) of 12.0% at Daman station; R2 of 0.89, RMSE of 0.16 mmd–1, and MAPE of 13.2% at Huazhaizi station). The rapid variation of ET could be precisely captured by HJ-1, especially when rainfall or irrigation events occurred between successive acquisitions of satellite data. Meanwhile, the spatiotemporal variation of monthly ET is closely related to crop growth. Daily ET at field scale will support a variety of local interests in water use and irrigation management for both planning and regulatory purposes