地下水埋深对淮北平原冬小麦耗水量影响试验研究

研究地下水埋深对淮北平原冬小麦耗水量的影响,对浅埋区农业水管理具有重要意义。基于2017—2020年五道沟水文水资源实验站大型称重式蒸渗仪群,模拟不同地下水埋深下冬小麦蒸散发变化过程,以蒸散量表征小麦耗水的变化,识别影响小麦耗水的关键环境因子,探索不同情景小麦耗水特征。全生育期内各地下水埋深0.5,1.0,2.0,3.0 m下小麦蒸散量依次为510.50,499.33,567.88,727.88 mm,各埋深下表层10 cm处土壤含水率与蒸散量相关系数依次为−0.42,−0.69,−0.53,−0.43;依据太阳辐射量划分3类典型日,典型日内蒸散强度为：强辐射日约0.30 mm/h、弱辐射日约0.07 mm/h、微弱辐射日约0.03 mm/h;蒸散峰历时依次为：5:00—20:00、7:00—17:00和9:00—17:00;太阳辐射强时,地下水埋深对蒸散强度峰值出现的时间影响较小,而太阳辐射过弱时,地下水埋深大会阻滞能量传输,蒸散强度峰值滞后;表层土壤水是蒸散发的主要来源,尤其在1.0,2.0 m埋深下表层土壤水对蒸散发贡献率更高;太阳辐射、净辐射和土壤热通量正向驱动小麦耗水,表层土壤水分、平均气温和空气湿度反向驱动。     

Spatiotemporal variability in hydrochemistry of shallow groundwater in a small pre‐alpine catchment: The importance of landscape elements

Topography and landscape characteristics affect the storage and release of water and, thus, groundwater dynamics and chemistry. Quantification of catchment scale variability in groundwater chemistry and groundwater dynamics may therefore help to delineate different groundwater types and improve our understanding of which parts of the catchment contribute to streamflow. We sampled shallow groundwater from 34 to 47 wells and streamflow at seven locations in a 20‐ha steep mountainous catchment in the Swiss pre‐Alps, during nine baseflow snapshot campaigns. The spatial variability in electrical conductivity, stable water isotopic composition, and major and trace ion concentrations was large and for almost all parameters larger than the temporal variability. Concentrations of copper, zinc, and lead were highest at sites that were relatively dry, whereas concentrations of manganese and iron were highest at sites that had persistent shallow groundwater levels. The major cation and anion concentrations were only weakly correlated to individual topographic or hydrodynamic characteristics. However, we could distinguish four shallow groundwater types based on differences from the catchment average concentrations: riparian zone‐like groundwater, hillslopes and areas with small upslope contributing areas, deeper groundwater, and sites characterized by high magnesium and sulfate concentrations that likely reflect different bedrock material. Baseflow was not an equal mixture of the different groundwater types. For the majority of the campaigns, baseflow chemistry most strongly resembled riparian‐like groundwater for all but one subcatchment. However, the similarity to the hillslope‐type groundwater was larger shortly after snowmelt, reflecting differences in hydrologic connectivity. We expect that similar groundwater types can be found in other catchments with steep hillslopes and wet areas with shallow groundwater levels and recommend sampling of groundwater from all landscape elements to understand groundwater chemistry and groundwater contributions to streamflow.     

空间层次聚类显著性判别的重排检验方法

同时顾及空间邻近与专题属性相似的空间层次聚类是挖掘空间分布模式的一种有效手段。空间层次聚类方法虽然可以获得多层次的聚集结构,但聚类结果显著性的统计判别依然是一个尚未解决的难题。为此,本文提出了一种空间层次聚类结果显著性的统计判别方法,用于确定空间层次聚类的停止准则,减少聚类过程对参数设置的依赖。通过试验分析与比较发现,该方法能够有效判别空间层次聚类结果的显著性和确定层次聚类合并过程的停止条件,同时具有很好的抗噪性,避免随机结构的干扰。     

基于时空聚类的出租车载客热点区域挖掘研究

针对出租车运营过程缺少路径优化指导造成运营能力分布不均、空载率高的问题,本文以成都市安装有GPS设备的出租车所采集的轨迹数据为研究对象,以提高出租车效益为目标,采用了一种基于网格的出租车载客热点聚类算法,通过对出租车GPS轨迹数据进行处理和聚类分析,充分挖掘出租车载客热点区域,从而为出租车的运营者和管理者提供信息决策服务。     

模糊聚类定权法对SLR定轨精度的影响

针对卫星激光测距(satellite laser ranging,SLR)精密定轨过程中存在的测站观测数据合理定权问题,将一种改进的模糊聚类算法引入到SLR观测数据定权中。基于国际激光测距服务(International Laser Ranging Service,ILRS)提供的全球SLR测站性能报告,对测站进行近实时滑动分类定权,改变SLR数据处理中权重的经验或者随意性选取模式。经过LAGEOS1卫星2014年1月至2016年12月3年全球SLR实测数据处理的测试。结果表明,当考虑LAGEOS标准点总数、LAGEOS标准点RMS值以及LAGEOS标准点合格率这3项测站质量控制因素确定的测站权值能最大限度地提高卫星定轨精度和观测数据的使用效率,对参与计算的365个3d弧段数据,91.46%弧段精度得到提高,平均提高约3.7mm,且每个测站的定轨残差RMS也得到了降低。这对于正在迈向毫米级测量精度的SLR技术至关重要。     

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.     

A density-based approach for detecting network-constrained clusters in spatial point events

Existing spatial clustering methods primarily focus on points distributed in planar space. However, occurrence locations and background processes of most human mobility events within cities are constrained by the road network space. Here we describe a density-based clustering approach for objectively detecting clusters in network-constrained point events. First, the network-constrained Delaunay triangulation is constructed to facilitate the measurement of network distances between points. Then, a combination of network kernel density estimation and potential entropy is executed to determine the optimal neighbourhood size. Furthermore, all network-constrained events are tested under a null hypothesis to statistically identify core points with significantly high densities. Finally, spatial clusters can be formed by expanding from the identified core points. Experimental comparisons performed on the origin and destination points of taxis in Beijing demonstrate that the proposed method can ascertain network-constrained clusters precisely and significantly. The resulting time-dependent patterns of clusters will be informative for taxi route selections in the future.     

Two-stage permutation tests for determining homogeneity within a spatial cluster

The discovery of spatial clusters formed by proximal spatial units with similar non-spatial attribute values plays an important role in spatial data analysis. Although several spatial contiguity-constrained clustering methods are currently available, almost all of them discover clusters in a geographical dataset, even though the dataset has no natural clustering structure. Statistically evaluating the significance of the degree of homogeneity within a single spatial cluster is difficult. To overcome this limitation, this study develops a permutation test approach Specifically, the homogeneity of a spatial cluster is measured based on the local variance and cluster member permutation, and two-stage permutation tests are developed to determine the significance of the degree of homogeneity within each spatial cluster. The proposed permutation tests can be integrated into the existing spatial clustering algorithms to detect homogeneous spatial clusters. The proposed tests are compared with four existing tests (i.e., Park’s test, the contiguity-constrained nonparametric analysis of variance (COCOPAN) method, spatial scan statistic, and q-statistic) using two simulated and two meteorological datasets. The comparison shows that the proposed two-stage permutation tests are more effective to identify homogeneous spatial clusters and to determine homogeneous clustering structures in practical applications.     

基于自发地理信息的人行道路信息提取

人类的行为轨迹可快速提取到车辆难以通行的人行道路以及人行道路设施等信息,这些信息是行人LBS的关键性元素,它的完备性程度决定了行人LBS服务质量的高低。本文使用志愿者数据集与百度地图,研究了一整套基于VGI数据的人行道路信息提取方法。通过轨迹数据清洗、道路几何路网提取、人行道路设施的检测与识别3个主要板块实现了人行道路信息的提取。算法在完成道路几何路网信息提取的同时,实现了人行横道、过街天桥、地下通道等道路设施信息的获取。