面状地质要素智能综合算法与应用研究

地质图智能综合具有可重复、效率高等优点。面状地质要素是地质图中的主要要素,通过算法研究实现面状地质要素的智能综合,在地质图缩编过程中是十分必要的。本文根据地质图缩编技术的行业经验、计算机软件开发规范,以及年代—地质体关系、地质体接触关系和面状地质要素拓扑规则等面状地质要素综合的理论基础,设计智能综合算法的逻辑流程,并基于ArcEngine和C#开发环境,设计实现地质图综合过程中面状地质要素智能化综合算法。首先根据由新到老的顺序依次对面状地质要素边界点集进行抽稀,然后对抽稀后的边界点集进行边界圆滑,并对综合面状地质要素的结果进行自动拓扑检查,最后得到最终的综合结果。以郑州、洛阳及周边区域的4幅1:25万地质图缩编至1:50万地质图为例进行面状地质要素综合,缩编后地质图（1:50万）中面状地质要素综合效果经过地质专家评估并得到认可。综合结果符合地质要素的压盖关系和拓扑规则,同时可以高效、批量、准确地实现地质要素智能综合,综合效率大大提高,可节省80%以上的工作量。地质图缩编过程中面状地质要素智能综合算法具有实际应用价值,实现了理论与技术的生产转化,改善传统编图综合的工作模式,促进了缩编制图效率的提高,推动了行业技术的进步,可以投入到大规模的地质图缩编工作中。     

单机倾斜摄影方式的无人机航线设计

针对传统的无人机航线设计大都只考虑垂直摄影的情形,没有考虑倾斜摄影的问题,该文结合滑坡地区的具体地形,对倾斜摄影的倾角以及主光轴方位角等相关参数进行了讨论与设定,并对倾斜摄影方式下的图像重叠率进行分析与对比,从而在确定重叠率后对无人机航线设计规划进行了研究,最终通过对比同一摄区垂直摄影与倾斜摄影的拍摄结果并分析。实验结果表明,对于单位摄区面积内,垂直摄影的密度为237.15张/km2,倾斜摄影的密度为206.69张/km2,同时可以明显发现单相机倾斜摄影的方式更有利于滑坡监测。     

基于D-InSAR三轨法的北京平原区地表形变监测

首先阐述了D-InSAR三轨法提取地表形变的基本原理,以北京平原区为实验区域,利用2009年9月到2010年4月间时隔210 d的三景Envisat ASAR数据进行解算,获取了该时间段内北京市城区范围内的整体地表形变,并将其与常规水准测量结果进行比较。结果表明,实验区监测结果范围与传统测量方法累计沉降量等值线吻合较好,D-InSAR三轨法能很好地反映实验区域的地面沉降情况。     

中国贫困村致贫因素分析及贫困类型划分（英文）

Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error(LSE) model and spatial econometric analysis model to identify the villages' poverty types and poverty difference. The case study shows that:(1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang.(2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions.(3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type.(4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of pov-erty alleviation at all levels to mobilize all kinds of anti-poverty resources.     

基于三维GIS的地震灾情实时动态标绘技术

面向地震应急救援的分析与处置,研究基于三维灾场环境的地震灾情实时动态标绘技术。将标绘体系的层次结构设计为几何层、单元层和语义表现层,重点研究几何层和语义表现层的设计与实现方法,探讨如何将各类标绘方法与语义表现形式转化为地震应急灾情信息、救援信息的集成显示与可视化分析的有效手段。并通过实际应急演练,验证将实时动态标绘技术应用于地震应急救援分析与处置的可行性和有效性。     

Driving forces analysis of reservoir wetland evolution in Beijing during 1984–2010

The reservoir wetland, which is the largest artificial wetland in Beijing, constitutes one of the important urban ecological infrastructures. Considering two elements of natural environment and socio-economy, this paper established the driving factor indexing system of Beijing reservoir wetland evolution. Natural environment driving factors include precipitation, temperature, entry water and groundwater depth; social economic driving factors include resident population, urbanization rate and per capita GDP. Using multi-temporal Landsat TM images from 1984 to 2010 in Beijing, the spatial extent and the distribution of Beijing reservoir wetlands were extracted, and the change of the wetland area about the three decade years were analyzed. Logistic regression model was used to explore for each of the three periods： from 1984 to 1998, from 1998 to 2004 and from 2004 to 2010. The results showed that the leading driving factors and their influences on reservoir wetland evolution were different for each period. During 1984-1998, two natural environment indices： average annual precipitation and entry water index were the major factors driving the increase in wetland area with the contribution rate of Logistic regression being 5.78 and 3.50, respectively, and caused the wetland growth from total area of 104.93 km 2 to 219.96 km 2 . From 1998 to 2004, as the impact of human activities intensified the main driving factors were the number of residents, groundwater depth and urbanization rate with the contribution rate of Logistic regression 9.41, 9.18, and 7.77, respectively, and caused the wetland shrinkage rapidly from the total area of 219.96 km 2 to 95.71 km 2 . During 2004-2010, reservoir wetland evolution was impacted by both natural and socio-economic factors, and the dominant driving factors were urbanization rate and precipitation with the contribution rate of 6.62 and 4.22, respectively, and caused the wetland total area growth slightly to 109.73 km 2 .     

面向地震灾害场景建模的三维地形交互改造技术

在虚拟地震灾害场景基础上,提出一种细节可控的三维地形实时改造算法,用于模拟因地震造成灾区地表形态的变化情况。该方法将地形改造的主要任务交由GPU（图形处理器）的pixel shader（像素着色器）完成,在pixel shader中将原始地形高度图的高程数据读取出来,通过设计算法对数据进行改造后输出至一张新的高度图,并用新的高度图替换原始高度图重新绘制一遍场景,以完成地形的实时改造;使用“乒乓”算法和批处理方式对地形改造效率进一步优化;引入Perlin（柏林）噪声增加了地形改造结果的随机扰动性,使改造结果更加逼真和接近实际情况。实验结果表明：该方法能够在地震灾害场景仿真平台中得到很好的应用,运算效率高,能够满足地形实时改造和交互编辑的实际需求。     

北京市细颗粒物时空分布及与呼吸系统疾病相关分析

细颗粒物(PM2.5)即粒径小于2.5μm的可吸入颗粒物[1],是当今中国城市大气污染的首要污染物。本研究以北京市为例,选取北京市2010年至2012年三年内采暖期与非采暖期两个不同时期的细颗粒物(PM0.3,PM0.5,PM1)实测数据,及同时期北京市患呼吸系统疾病人数数据,运用地统计的空间分析方法,对获取数据进行空间化及插值研究。通过偏相关分析法对北京市细颗粒物浓度与患呼吸系统疾病人数数据进行相关分析。得出以下主要结论:①细颗粒物的空间变化明显,2010年、2011年及2012年细颗粒物浓度整体呈上升趋势,2012年三种粒径细颗粒物浓度整体高于2010年与2011年。②不同粒径的细颗粒物,对呼吸疾病的影响程度不同:在0.3μm,0.5μm与1μm三种粒径的细颗粒物中,PM1对呼吸系统疾病影响最大,偏相关系数达到0.785。     

再生水补水条件下土壤全氮空间分布特征

土壤中的氮素是植物生长发育的基础,由于城市湿地土壤受特殊水文条件影响,土壤全氮(TN)的分布规律和影响机制较为复杂,因此研究土壤TN的空间分布特征具有重大的生态意义。本文以再生水为主要补给水源的北京门城湖湿地公园为研究区,运用ArcGIS和地统计学对该区土壤TN的空间分布特征进行研究。结果表明:研究区土壤TN质量分数较高,差值明显,变异系数达47.35%;比较不同的植物群落区可知,香蒲群落区土壤TN质量分数最高。对影响研究区土壤TN分布的因素分析得出:土壤TN、全磷(TP)质量分数呈极显著正相关关系(r=0.81,P0.01);TN、土壤有机质(SOM)质量分数呈显著正相关关系(r=0.62,P0.05);气候因子中,湿度和温度对TN分布同样影响显著。水质参数中,再生水出水口处测得的土壤TN的指标数值更高,随出水口距离的增加,参数值总体呈下降趋势且逐步趋于稳定,说明植被对湿地土壤中氮素空间分布的调整具有重要作用。     

无人机模糊图像自动检测方法

图像模糊程度是图像评价的一个关键指标参数,它影响着图像的质量和信息。特别对于无人机拍摄的图像,如果利用模糊的图像参与计算,会造成很大的误差甚至出现颠覆性的结果。因此对于图像模糊的检测显得至关重要。传统的图像模糊检测方法大都基于人工检测、且有合格的参考图像参与评价过程,方法耗时、费力,无法用于大量无人机拍摄图像的分析。因此本文基于Sobel边缘检测原理,利用4个方向的Sobel算子,寻找图像中每个Sobel边缘点的模糊邻域,并构建模糊邻域宽度值的计算准则,由此来计算出整幅图像的平均模糊邻域宽度值,并将这个计算结果作为检测模糊的直接依据。同时考虑到无人机拍摄图像的特点,将其按照拍摄时间顺序排列,依次将相邻图像互为参考,通过对比互为参考图像的模糊邻域宽度值的变化情况,将宽度值突变的图像确定为模糊图像。据此对无人机拍摄的所有图像进行模糊检测。最终通过7组2322张 图像进行自动检测发现151张图像模糊,通过人工检测发现158张图像模糊,平均检测率95.57%。该检测方法具有较强的 适用性。