The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s...The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes.展开更多
Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing da...Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.展开更多
基于无人机未来融入国家空域系统的发展趋势,针对无人机数量增多导致与有人机之间碰撞风险增大的问题,根据ADS-B IN的优势和特点,提出了一种融合空域下,无人机利用ADS B IN进行冲突探测和解脱的模型。模型中依据飞行器的具体参数划设了...基于无人机未来融入国家空域系统的发展趋势,针对无人机数量增多导致与有人机之间碰撞风险增大的问题,根据ADS-B IN的优势和特点,提出了一种融合空域下,无人机利用ADS B IN进行冲突探测和解脱的模型。模型中依据飞行器的具体参数划设了有人机的安全区和保护区,并利用几何法设置潜在碰撞风险判定标准和解脱完成标准,根据最小机动和最快解脱原则,无人机在空域内进行实时探测并对可能产生冲突的有人机主动避让,在避让过程中分别考虑了速度解脱、航向解脱、速度和航向混合解脱三种解脱策略。在实际运行场景中,同时考虑了风对航空器速度和航向的影响,进行了风速修正。设置三种运行场景进行了仿真试验,仿真结果满足最低安全间隔的要求。为进一步验证模型的优势,另与传统的人工势场方法进行了仿真对比。以上两种结果均证实了模型的可靠性和优越性,未来可用于降低管制员工作负荷,提高空域整体安全性。展开更多
文摘The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes.
基金Under the auspices of National Key Research and Development Project of China(No.2021YFD1500103)Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28100500)+2 种基金National Natural Science Foundation of China(No.4197132)Science and Technology Development Plan Project of Jilin Province(No.20210201044GX)Land Observation Satellite Supporting Platform of National Civil Space Infrastructure Project(No.CASPLOS-CCSI)。
文摘Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.
文摘基于无人机未来融入国家空域系统的发展趋势,针对无人机数量增多导致与有人机之间碰撞风险增大的问题,根据ADS-B IN的优势和特点,提出了一种融合空域下,无人机利用ADS B IN进行冲突探测和解脱的模型。模型中依据飞行器的具体参数划设了有人机的安全区和保护区,并利用几何法设置潜在碰撞风险判定标准和解脱完成标准,根据最小机动和最快解脱原则,无人机在空域内进行实时探测并对可能产生冲突的有人机主动避让,在避让过程中分别考虑了速度解脱、航向解脱、速度和航向混合解脱三种解脱策略。在实际运行场景中,同时考虑了风对航空器速度和航向的影响,进行了风速修正。设置三种运行场景进行了仿真试验,仿真结果满足最低安全间隔的要求。为进一步验证模型的优势,另与传统的人工势场方法进行了仿真对比。以上两种结果均证实了模型的可靠性和优越性,未来可用于降低管制员工作负荷,提高空域整体安全性。
