山岳型旅游区人文建筑环境后效与调控模型

许多山岳型旅游区内或其流域上游，都建有人文建筑，而且在急剧增多，导致自然环境日趋恶化，其中乱建疗养院和旅馆的影响最为严重。通过地监测并全面分析张家界环境演变趋势，发现住宿施对环境的影响，比其他游乐设施更为明显。张家界国家森林公园生态环境的脆弱因子是金鞭溪水质。金鞭溪水质恶化主要表现为蓝藻，绿藻迅速繁殖，感官质量下降。主要原因是磷污染较重，总磷年均值100%超标。本文提出了基于环境脆弱因子的动态阈值调控模型，通过计算得出：在不超出张家界景区最为脆弱的环境因子-金鞭溪水质标准：总磷≤0.02前提下，金鞭溪上游接待区住宿设施生态阈值的动态系列：春季临界床位数为1186，夏季为3057，冬季为545，秋季为333。目前的建筑规模已超过了金鞭溪上游接待区住宿设施生态阈值。     

MODIS数据在黄河凌汛监测中的应用

对MODIS数据的特性及其在黄河凌汛监测中的应用情况进行了探讨和总结。试验结果表明 ,MODIS数据在冰雪检测方面具有很大的潜力     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

An analytical approach to ascertain saturation‐excess versus infiltration‐excess overland flow in urban and reference landscapes

Uncontrolled overland flow drives flooding, erosion, and contaminant transport, with the severity of these outcomes often amplified in urban areas. In pervious media such as urban soils, overland flow is initiated via either infiltration‐excess (where precipitation rate exceeds infiltration capacity) or saturation‐excess (when precipitation volume exceeds soil profile storage) mechanisms. These processes call for different management strategies, making it important for municipalities to discern between them. In this study, we derived a generalized one‐dimensional model that distinguishes between infiltration‐excess overland flow (IEOF) and saturation‐excess overland flow (SEOF) using Green–Ampt infiltration concepts. Next, we applied this model to estimate overland flow generation from pervious areas in 11 U.S. cities. We used rainfall forcing that represented low‐ and high‐intensity events and compared responses among measured urban versus predevelopment reference soil hydraulic properties. The derivation showed that the propensity for IEOF versus SEOF is related to the equivalence between two nondimensional ratios: (a) precipitation rate to depth‐weighted hydraulic conductivity and (b) depth of soil profile restrictive layer to soil capillary potential. Across all cities, reference soil profiles were associated with greater IEOF for the high‐intensity set of storms, and urbanized soil profiles tended towards production of SEOF during the lower intensity set of storms. Urban soils produced more cumulative overland flow as a fraction of cumulative precipitation than did reference soils, particularly under conditions associated with SEOF. These results will assist cities in identifying the type and extent of interventions needed to manage storm water produced from pervious areas.     

重要性权值的驾车导航POI表达规则

在导航电子地图中,针对驾车任务的POI自适应表达是提高导航电子地图信息传输效率的关键。针对这一问题,提出了基于重要性权值的驾车导航POI表达规则。首先,分析了POI重要性权值的影响因素;其次,从影响因素出发,研究了基于权值的POI规则表达的各规则项;最后,设计了POI自适应表达规则库,并在嵌入了数据处理规则库的绘图软件上进行了技术实现。试验结果表明,利用基于权值的POI表达规则进行地图表达,可以提高地图内容的层次性与清晰性,优化驾车导航服务。     

多光谱遥感影像亮度空间相位一致性特征点检测

提出了一种基于亮度空间和相位一致性理论的多光谱遥感影像特征点检测算法。首先利用参数自适应的灰度变换函数建立影像亮度空间;然后结合相位一致性方法在影像亮度空间进行候选特征点检测,并将候选特征点映射到原始影像上进行非极大值抑制;最后在尺度空间计算特征点的特征尺度值。本文方法有效结合了亮度空间特征检测和相位一致性特征检测的优势,对多光谱遥感影像的辐射变化具有较强的稳健性。试验结果证明,与传统特征点检测算法相比,本文方法在特征重复率和重复特征数量方面都具有明显的优势。     

基于潜在语义信息的城市功能区识别————广州市浮动车GPS时空数据挖掘

随着中国城市化进程的不断推进和深入,城市内部空间结构正发生不断的变化.城市内部形成的不同功能区标识研究,对城市结构理论以及政策制定,资源配置等方面具有非常重要的意义.这些不同的功能区包括住宅区,工业区,教育区以及办公区等.本文以大数据为依托,重点研究城市功能区的特点和分布状态,选取广州市6个区为样本,以最新道路网络为分割依据把研究样本分为439个区域.对历时一周的海量浮动车(GPS)数据以及兴趣点数据采用时空语义挖掘方法,建立潜在的狄利克雷模型(LDA)以及狄利克雷多项式回归模型(DMR);通过OPTICS聚类方法对不同模型的结果进行聚类,进而利用POI类别密度,居民出行特征等方法进行分区结果识别.同时,参考百度地图的地理信息,将研究得到的广州市功能分区结果与广州市城镇用地现状图,居民日常出行特征进行对比验证分析.研究表明,该方法基本能识别出具明显特征的城市功能区,如成熟居住区,科教文化区,商业娱乐区,开发区等.识别出的广州市不同类型的功能区呈现了以居住区和商业区为主导,其他类型功能区围绕其展开的特点.研究证明,利用大规模,高质量的个体时空数据开展人们移动行为和日常活动组织及社会空间的研究,能从一个新的视角揭示城市功能区的形成及其机制.     

基于SEED波形文件的运行率统计

介绍了基于SEED波形文件运行率计算的技术和实现方法,介绍了SEED文件中标识时间的特殊掩码、时间片的具体格式和程序的实现,并给出了与其相关的部分源代码.     

布达拉宫旅游商业化的社区治理研究

以社区为出发点,综合旅游商业化、社区治理等相关理论,在布达拉宫及周边社区旅游商业化表征分类的基础上,梳理其社区旅游商业化的治理成效及治理困境。再运用静态博弈模型与决策树,分析布达拉宫及周边社区旅游商业化的治理中各利益主体博弈的过程,并探析治理困境的原因。研究发现,旅游商业化的社区治理受到各利益主体间权力大小和利益选择的影响。政府及相关部门处于强势地位,主导并采取措施治理旅游商业化。布达拉宫的各空间圈层在商业化治理过程和难度上都存在明显差异。引起治理困境的原因主要是“权”与“利”的纠葛、商业化控制的阈限不清晰、利益主体之间的沟通不畅。在主要利益相关者的博弈中,各治理主体共同重构一个相对均衡的“利益－权力”关系结构,以保证社区旅游商业化得以有效治理。     

基于自然区块的城市热环境空间分异性研究

通过有效解决建设用地子类划分,实现定量评价城市热环境的空间分异性,对改善城市生态环境、实现城市化的健康发展具有重要的意义和科学价值。论文以广州市为例,参考自然城市的概念,基于5类兴趣点(Point Of Interest,POI)开放数据,结合城市建设用地分类标准,构建5类自然区块;在Landsat 8遥感影像地表温度反演的基础上,计算分析自然区块下地表热场等级分布格局、热场平均值及热环境足迹范围,以对城市热环境空间分异性进行评价。研究表明：① 自然区块的构建,能准确地反映各类POI数据空间分布情况,能够实现对建设用地子类型的划分;② 5类自然区块内部地表热场等级均以高温像元为主,但等级分布具有显著差异。同时,自然区块的热场平均值由高到低的排序为：工业区块>商业服务业区块>交通与道路区块>居住区块>公共管理与服务区块;③ 自然区块形成的高温集聚区,存在热量扩散现象,实际影响范围大于其物理边界,5类自然区块的热环境足迹范围具有分异性。热环境足迹影响范围由大到小排序为：工业区块>商业服务业区块>居住区块>道路与交通区块>公共管理与服务区块。研究结果可为微观尺度上分析城市热环境、改善城市生态环境、实现城市化的健康发展提供科学依据。