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1.
The study examines a water exploration and poverty alleviation project in Guyuan county. The study analyzes correlations between aquifers and multiple induced polarization (IP) parameters, including resistivity, polarizability, deviation, half decay time, water-bearing factors, and Kc, a new parameter refined in this study. Based on the study, the well was placed accurately, and its maximum water inflow reached 30 m3/h. Kc value highlights the rate of change at early stages of IP secondary field. Kc value served as a quick indicator in this groundwater prospecting and is validated in practice. Progress has been made in finding new parameters in exploring water with IP method. Thanks to the project, local people have access to water and poverty alleviation has scored some achievements.  相似文献   
2.
Machine learning has achieved great success in many areas today. The lifting algorithm has a strong ability to adapt to various scenarios with a high accuracy, and has played a great role in many fields. But in astronomy, the application of lifting algorithms is still rare. In response to the low classification accuracy of the dark star/galaxy source set in the Sloan Digital Sky Survey (SDSS), a new research result of machine learning, eXtreme Gradient Boosting (XGBoost), has been introduced. The complete photometric data set is obtained from the SDSS-DR7, and divided into a bright source set and a dark source set according to the star magnitude. Firstly, the ten-fold cross-validation method is used for the bright source set and the dark source set respectively, and the XGBoost algorithm is used to establish the star/galaxy classification model. Then, the grid search and other methods are used to adjust the XGBoost parameters. Finally, based on the galaxy classification accuracy and other indicators, the classification results are analyzed, by comparing with the models of function tree (FT), Adaptive boosting (Adaboost), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Stacked Denoising AutoEncoders (SDAE), and Deep Belief Nets (DBN). The experimental results show that, the XGBoost improves the classification accuracy of galaxies in the dark source classification by nearly 10% as compared to the function tree algorithm, and improves the classification accuracy of sources with the darkest magnitudes in the dark source set by nearly 5% as compared to the function tree algorithm. Compared with other traditional machine learning algorithms and deep neural networks, the XGBoost also has different degrees of improvement.  相似文献   
3.
Evapotranspiration (ET) is an important parameter in hydrologic processes and modelling. In agricultural watersheds with competing uses of fresh water including irrigated agriculture, estimating crop evapotranspiration (ETc) accurately is critical for improving irrigation system and basin water management. The use of remote sensing-based basal crop coefficients is becoming a common method for estimating crop evapotranspiration for multiple crops over large areas. The Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI), based on reflectance in the red and near-infrared bands, are commonly used for this purpose. In this paper, we examine the effects of row crop orientation and soil background darkening due to shading and soil surface wetness on these two vegetation indices through modelling, coupled with a field experiment where canopy reflectance of a cotton crop at different solar zenith angles, was measured with a portable radiometer. The results show that the NDVI is significantly more affected than the SAVI by background shading and soil surface wetness, especially in north–south oriented rows at higher latitudes and could lead to a potential overestimation of crop evapotranspiration and irrigation water demand if used for basal crop coefficient estimation. Relationships between the analysed vegetation indices and canopy biophysical parameters such as crop height, fraction of cover and leaf area index also were developed for both indices.  相似文献   
4.
Wetlands represent one of the world's most biodiverse and threatened ecosystem types and were diminished globally by about two‐thirds in the 20th century. There is continuing decline in wetland quantity and function due to infilling and other human activities. In addition, with climate change, warmer temperatures and changes in precipitation and evapotranspiration are reducing wetland surface and groundwater supplies, further altering wetland hydrology and vegetation. There is a need to automate inventory and monitoring of wetlands, and as a study system, we investigated the Shepard Slough wetlands complex, which includes numerous wetlands in urban, suburban, and agricultural zones in the prairie pothole region of southern Alberta, Canada. Here, wetlands are generally confined to depressions in the undulating terrain, challenging wetlands inventory and monitoring. This study applied threshold and frequency analysis routines for high‐resolution, single‐polarization (HH) RADARSAT‐2, synthetic aperture radar mapping. This enabled a growing season surface water extent hyroperiod‐based wetland classification, which can support water and wetland resource monitoring. This 3‐year study demonstrated synthetic aperture radar‐derived multitemporal open‐water masks provided an effective index of wetland permanence class, with overall accuracies of 89% to 95% compared with optical validation data, and RMSE between 0.2 and 0.7 m between model and field validation data. This allowed for characterizing the distribution and dynamics of 4 marsh wetlands hydroperiod classes, temporary, seasonal, semipermanent, and permanent, and mapping of the sequential vegetation bands that included emergent, obligate wetland, facultative wetland, and upland plant communities. Hydroperiod variation and surface water extent were found to be influenced by short‐term rainfall events in both wet and dry years. Seasonal hydroperiods in wetlands were particularly variable if there was a decrease in the temporary or semipermanent hydroperiod classes. In years with extreme rain events, the temporary wetlands especially increased relative to longer lasting wetlands (84% in 2015 with significant rainfall events, compared with 42% otherwise).  相似文献   
5.
White dwarfs are the evolutionary endpoint of the low-and-medium mass stars. In the studies of white dwarfs, the mass of white dwarf is an important physical parameter. In this paper, we give an analysis about the velocity distribution of DA white dwarfs in the Sloan Digital Sky Survey (SDSS), and hope to find the relation between mass and velocity distribution of white dwarfs. We get the radial velocity and tangential velocity of every DA white dwarf according to their proper motion and spectral shift. Through analyzing the velocity distribution of DA white dwarfs, we find that the small-mass white dwarfs, which are produced from the single-star evolution channel, have a relatively large velocity dispersion.  相似文献   
6.
PS测井技术是地震勘探方法之一,也是一种简便、快速、准确的原位测试技术。该文介绍了单孔法PS测井的原理及其在铁路工程勘察中的应用,主要包括根据等效剪切波,进行建筑抗震场地类别划分,铁路工程抗震场地类别划分。根据岩土动力学参数,达到评价岩体质量和划分围岩类别目的,利用剪切波速法估算岩土的承载力基本值。通过青岛机场隧道场地的工程实例说明了PS测井技术在岩土工程勘察设计中的应用情况及应用效果。  相似文献   
7.
8.
滑坡是发生在我国山区的主要地质灾害类型,金沙江地区由于地势较高、地形复杂、多云多雨的特点,给传统的滑坡监测增加了难度。合成孔径雷达差分干涉测量技术(Differential interferometry synthetic aperture radar,D-InSAR)已在滑坡地面沉降监测中得到了广泛应用。本文选取金沙江上游沿岸作为研究区域,基于2018年8月11日与9月28日的Sentinel-1A影像及SRTM1数据,利用GAMMA软件及D-InSAR技术监测到金沙江地区的地表形变,成功识别出金沙江右岸的一处滑坡灾害。研究结果显示,在此滑坡的坡顶部分出现了约2.5 cm的沉降,而在坡底部分由于崩塌物的累积,地面出现了约3 cm的抬升。从实验结果可以得出,InSAR技术是一种有效的滑坡变形监测手段,利用Sentinel-1A卫星的SAR数据对滑坡区域进行形变监测,可以得到较好的干涉结果。  相似文献   
9.
This paper analyzes the backscatter of the microwave signal in a boreal forest environment based on a Ku -band airborne Frequency-Modulated Continuous Waveform (FMCW) profiling radar—Tomoradar. We selected a half-managed boreal forest in the southern part of Finland for a field test. By decomposing the waveform collected by the Tomoradar, the vertical canopy structure was achieved. Based on the amplitude of the waveform, the Backscattered Energy Ratio of Canopy-to-Total (BERCT) was calculated. Meanwhile, the canopy fraction was derived from the corresponding point cloud recorded by a Velodyne VLP-16 LiDAR mounted on the same platform. Lidar-derived canopy fraction was obtained by counting the number of the first/ the strongest returns versus the total amount of returns. Qualitative and quantitative analysis of radar-derived BERCT on lidar-derived canopy fraction and canopy height are investigated. A fitted model is derived to describe the Ku-band microwave backscatter in the boreal forest to numerically analyze the proportion contributed by four factors: lidar-derived canopy fraction, radar-derived canopy height, the radar-derived distance between trees and radar sensor and other factors, from co-polarization Tomoradar measurements. The Root Mean Squared Error (RMSE) of the proposed model was 0.0958, and the coefficient of determination R2 was 0.912. The fitted model reveals that the correlation coefficient between radar-derived BERCT and lidar-derived canopy fraction is 0.84, which illustrates that lidar surface reflection explains the majority of the profiling /waveform radar response. Thus, vertical canopy structure derived from lidar can be used for the benefit of radar analysis.  相似文献   
10.
为了更全面地分析筋土界面相互作用特性,改制了一台可视加筋土界面特性宏细观分析的试验仪器,可开展不同土工合成材料与填料的直剪和拉拔试验;该仪器改进了试验箱的尺寸,可方便两种试验的对比分析,增加了图像摄录系统,可进行试验过程的细观分析。使用新研制仪器分别进行了土工合成材料(土工格栅和土工布)加筋尾矿砂的直剪和拉拔试验,试验结果表明:两种试验条件下,土工格栅与尾矿的界面参数(似黏聚力和似摩擦角)及似摩擦系数均比土工布与尾矿的界面参数和似摩擦系数大;直剪试验下筋材网孔的有无对筋-尾矿界面参数均有较大影响,拉拔试验下筋材网孔有无对筋-尾矿界面参数似黏聚力的影响较为显著,对似摩擦角的影响较小。随着宏观变量法向应力的增加,细观参数孔隙率减小,平均接触数增加,反映在宏观上的现象就是填料颗粒被压密,筋材需要克服的阻力增大。该试验仪器能够较好地分析筋土界面宏细观特性,获得关键技术指标以用于加筋结构的设计。   相似文献   
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