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Study on Soil Salinization Information in Arid Region Using Remote Sensing Technique

Agricultural Sciences in china 2011年第3期10卷 404-411页

作者： Tashpolat Tiyip Key Laboratory of Oasis Ecology Ministry of Education/College of Resources and Environmental Science Xinjiang University

Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, china, which was studied using a Landsat Enhanced Thematic Mapper Plus （ETM＋） image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data. Principal component analysis （PCA） is a popular data reduction technique used to help build a decision tree; it reduces complexity and can help the classification precision of a decision tree to be improved. A decision tree approach was used to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area. According to the research, the third principal component （PC3） is an effective variable in the decision tree classification for salinized soil information extraction. The research demonstrated that the PC3 was the best band to identify areas of severely salinized soil; the blue spectral band from the ETM＋ sensor （TM1） was the best band to identify salinized soil with the salt-tolerant vegetation of tamarisk （Tamarix chinensis Lour）; and areas comprising mixed water bodies and vegetation can be identified using the spectral indices MNDWI （modified normalized difference water index） and NDVI （normalized difference vegetation index）. Based upon this analysis, a decision tree classifier was applied to classify landcover types with different levels of soil saline. The results were checked using a statistical accuracy assessment. The overall accuracy of the classification was 94.80%, which suggested that the decision tree model is a simple and effective method with relatively high precision.

关键词： soil salinization information arid region remote sensing

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An optimal hydropower contract load determination method considering both human and riverine ecosystem needs

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Frontiers of Earth Science 2015年第3期9卷 546-554页

作者： Xin'an YIN Zhifeng YANG Cailing LIU Yanwei ZHAO State Key Laboratory of Water Environment Simulation School of Environment Beijing Normal University Beijing 100875 China

In this research, a new method is developed to determine the optimal contract load for a hydropower reservoir, which is achieved by incorporating environ- mental flows into the determination process to increase hydropower revenues, while mitigating the negative impacts ofhydropower generation on riverine ecosystems. In this method, the degree of na^ral flow regime alteration is adopted as a constraint of hydropower generation to protect riverine ecosystems, and the maximization of mean annual revenue is set as the optimization objective. The contract load in each month and the associated reservoir operating parameters were simultaneously optimized by a genetic algorithm. The proposed method was applied to china＇s Wangkuai Reservoir to test its effectiveness. The new method offers two advantages over traditional studies. First, it takes into account both the economic benefits and the ecological needs of riverine systems, rather than only the economic benefits, as in previous methods. Second, although many measures have been established to mitigate the negative ecological impacts ofhydropower generation, few have been applied to the hydropower planning stage. Thus, since the contract load is an important planning parameter for hydropower generation, influencing both economic benefits and riverine ecosystem protection, this new method could provide guidelines for the establishment of river protection measures at the hydropower planning stage.

关键词： hydropower electricity supply load reservoiroperation river protection

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Numerical simulation of intelligent compaction for subgrade construction

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Journal of Central South University 2020年第7期27卷 2173-2184页

作者： MA Yuan LUAN Ying-cheng ZHANG Wei-guang ZHANG Yu-qing School of Transportation Southeast UniversityNanjing 210096China National Engineering Laboratory of Highway Maintenance Technology Changsha University of Science&TechnologyChangsha 410114China Aston Institute of Materials Research Engineering Systems&Management GroupAston UniversityBirminghamB47ETUK

During the compaction of a road subgrade, the mechanical parameters of the soil mass change in real time, but current research assumes that these parameters remain unchanged. In order to address this discrepancy, this paper establishes a relationship between the degree of compaction K and strain ε. The relationship between the compaction degree K and the shear strength of soil(cohesion c and frictional angle φ) was clearly established through indoor experiments. The subroutine UMAT in ABAQUS finite element numerical software was developed to realize an accurate calculation of the subgrade soil compaction quality. This value was compared and analyzed against the assumed compaction value of the model, thereby verifying the accuracy of the intelligent compaction calculation results for subgrade soil. On this basis, orthogonal tests of the influential factors(frequency, amplitude, and quality) for the degree of compaction and sensitivity analysis were carried out. Finally, the ‘acceleration intelligent compaction value’, which is based on the acceleration signal, is proposed for a compaction meter value that indicates poor accuracy. The research results can provide guidance and basis for further research into the accurate control of compaction quality for roadbeds and pavements.

关键词： intelligent compaction numerical simulation dynamic change control indicators orthogonal experiment

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