序列无人机影像拼接方法研究

无人机影像具有数量多、畸变大、POS数据不准确等特点,导致其在拼接过程中会产生大量的累积误差,要快速地获得大范围准确的全景图有一定的困难。基于此,提出一种既精确又高效的无人机序列影像拼接方法。首先计算大致的影像匹配区域,减少特征搜索和匹配的时间,同时记录匹配区域中心位置的特征点坐标,引入平差理论,区分平地、丘陵、山区等不同区域加权纠正匹配特征点的坐标位置。同时针对航带间重叠率小、姿态差异大等特点,采用"先航带间再航带内、旁边航带向中间航带靠拢"的拼接方式,减少整体区域的累积误差产生,最终完成全局影像的拼接。     

多特征加权融合的高分SAR影像建筑区提取方法

机载SAR影像分辨率的不断提高使得图像纹理信息更加丰富,对地物分类和提取具有重要意义。针对建筑区的纹理特点,该文提出了一种综合统计和结构多特征加权融合的建筑区提取方法。分别采用经典的灰度共生矩阵方法提取统计纹理特征和采用变差函数方法提取结构纹理特征,并考虑方向信息;然后利用提出的巴士距离特征权值计算方法,将所选特征进行加权融合;利用K均值聚类算法对融合后的特征图像进行非监督分类,对分类图像进行后处理并提取外部轮廓。以国产机载P波段全极化SAR影像为数据源进行了实验,并对结果进行了定量分析,表明该方法能够高精度地有效提取高分辨率机载SAR影像中的建筑区。     

稳健加权总体最小二乘的点云数据平面拟合

针对观测向量和系数矩阵均含有误差以及点云数据存在异常点的问题,该文提出一种稳健加权总体最小二乘法。该方法在加权总体最小二乘的基础上,通过设置一定的准则,剔除点云数据中存在的异常点,以获取更为精确的平面拟合参数解。仿真模拟算例和实际点云数据实验结果表明,该方法与传统的方法相比,能够消除异常点带来的影响,获得更精确的参数解,平面拟合精度更高。     

Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city,China

Land price plays an important role in guiding land resource allocation for urban planning and development, particularly in big cities of fast developing countries where infrastructures and populations change frequently. Therefore, detecting spatially implicit information in the spatial pattern of relationships between land price and related impact factors is critical. Geographically weighted regression (GWR) analysis was conducted in this study for the purpose in Wuhan, China, by using a 10-year panel data set of residential land price. Based on twelve factors in three aspects (land attributes, location factors and neighborhood attributes), an evaluation index system of resident land price was established. The spatial distributions of estimated coefficients and pseudo t-values of three major explanatory variables (floor area ratio, distance to nearest center business district (CBD) and distance to nearest lake), obtained from GWR analysis, indicated that their relationships of the impact factors with land price are spatially non-stationary. The positive impact of floor area ratio on land price is more significant in highly developed areas than in less developed areas. Conversely, the negative impact of distance to nearest CBD on land price is larger in highly developed areas than in less developed areas. Moreover, wealthier dwellers may be willing to pay a higher price for a good lake view (especially views of small lakes), but infrastructure barriers (near some large lakes) cause negative effect. The outputs of this study, which provide detailed information on the relationships between land price and impact factors in local areas, are promising for urban planners to scientifically evaluate land price and make area-specific strategies.     

Modelling of geographic cancer risk factor disparities in US counties

The goal of this research is to create a theoretical framework for the identification of cancer risk factor disparities and address the recognition of geographic patterns in these factors. 34 secondary variables covering the entire US at the county level in 2010 were analyzed, both individually and grouped (theoretically and statistically), in relation to the mortality to incidence ratio (MIR) for all cancer sites. An a priori assessment and a principal components analysis (PCA) were used to group variables to test societal constructs. OLS and geographically weighted regressions (GWRs) were used to assess influence of both individual and grouped variables against the MIR. The theoretical grouping of variables showed little change in predictive capability of OLS models. In GWR model, there was marked improvement over the OLS. Maps produced using local R2 showed clear regional patterns of influence between the indicators and the MIR. Both the theoretical model and the justification for a spatial approach to cancer risk factor disparities were shown to be effective in this paper. The link between this suite of indicators and the health outcomes is clear, and supports the idea that a full representation of the SES landscape should be used to both predict health outcomes and to assess policy options for improving these outcomes. With the presence of definitive regional patterns and clear connections between the MIR and societal groupings, the findings from this research suggest a need to shift to a more comprehensive and spatial approach to cancer disparities research.     

1960-2014年中国绿洲严寒期的时空变化特征与成因分析

基于中国绿洲74个地面气象站的逐日平均气温观测资料,计算候平均温度≤ 0 ℃的严寒期起止候及候数,运用线性趋势法、M-K突变检验、Morlet小波分析法、相关分析等方法,分析中国绿洲严寒期的起止候及候数的时空变化特征与成因。结果表明：近55年来,中国绿洲严寒期起始候推后、终止候提前、候数缩短,变化倾向率分别为0.3 p/10a、-0.27 p/10a和-0.58 p/10a;且空间差异显著,其中,柴达木盆地绿洲严寒期来的最早、结束的最晚,严寒期变化趋势最显著。严寒期起止候及候数分别在1990年、1998年、1994年发生突变。严寒期起始候与候数表现出与大气环流和厄尔尼诺有关的显著周期,终止候表现出与太阳活动有关的显著周期,可以证实严寒期起始候和候数的变化与大气环流和厄尔尼诺密切相关,而终止候的变化则与太阳活动有关。青藏高原指数、亚洲区极涡面积指数和二氧化碳排放量是影响研究区严寒期的主要因子,而南亚夏季风指数则对柴达木盆地绿洲影响最显著。研究区严寒期随着经纬度和海拔高度的增加,起始候提前、终止候推后、候数延长,并以纬度的变化最显著。严寒期起止候及候数对区域增暖具有极好的响应,但区域增暖对起止候及候数的影响各不相同。     

全球城市知识流动网络的结构特征与影响因素

在科技全球化时代,城市之间的知识流动日益频繁,成为当代知识生产的重要特征。然而,鲜有从知识流动的视角开展全球城市体系的研究。基于2017年的高被引论文合作数据,采用社会网络分析方法和空间计量模型系统地刻画了全球城际科研合作网络的拓扑结构和空间格局及其影响因素。研究发现：① 拓扑结构呈现出以北美、欧洲和亚太城市的三极格局,轴辐式和分布式结构特征并存。② 世界城市科研合作网络形成以北美、西欧、东亚和澳大利亚为顶点的四边形格局。③ 多核心-边缘结构显现,纽约、伦敦和北京等8个城市为全球核心,芝加哥等41个城市为区域核心。④ 全球城市科研合作网络的等级层次特征显著,纽约、北京和吉达分别是三大子网的主导型城市。⑤ 空间相互作用模型表明地理距离阻碍了城市间的科研合作,城市的科研规模、人口规模、世界一流大学数量、制度邻近性和社会邻近性促进了城际联系。     

京津冀文化艺术产业空间格局演变及其影响因素

基于2007—2017年文化艺术企业数据,采用核密度估计和空间自相关检验分析京津冀县域尺度的文化艺术产业的空间格局演变,并运用岭回归和地理加权回归对其影响因素效应及空间分异性进行探索,最后讨论其影响机制。研究发现：① 京津冀文化艺术产业空间集聚范围不断扩大,河北与京津的断崖式差距正在逐步缩减,“两核一轴带”格局逐渐形成;② 京津冀文化艺术产业具有显著的空间依赖性,全局依赖性有所减弱但局部依赖性逐渐增强;H-H型集聚主要在京津分布蔓延,京津之间的廊坊市显现出L-H型集聚;L-L型集聚主要位于河北各地市的边缘地带,个别区县呈现H-L型孤岛集聚形态;③ 市场需求、关联产业及人才技术是影响当前京津冀文化艺术产业发展的主要因素,文化资源影响稳定而政策环境效应空间分异性大,未来应结合地区发展空间关联性和影响因素空间分异性针对性地实现京津冀文化艺术产业协同发展。     

Application of geographically weighted regression model in the estimation of surface air temperature lapse rate

The surface air temperature lapse rate(SATLR)plays a key role in the hydrological,glacial and ecological modeling,the regional downscaling,and the reconstruction of high-resolution surface air temperature.However,how to accurately estimate the SATLR in the regions with complex terrain and climatic condition has been a great challenge for re-searchers.The geographically weighted regression(GWR)model was applied in this paper to estimate the SATLR in China's mainland,and then the assessment and validation for the GWR model were made.The spatial pattern of regression residuals which was identified by Moran's Index indicated that the GWR model was broadly reasonable for the estimation of SATLR.The small mean absolute error(MAE)in all months indicated that the GWR model had a strong predictive ability for the surface air temperature.The comparison with previous studies for the seasonal mean SATLR further evidenced the accuracy of the estimation.Therefore,the GWR method has potential application for estimating the SATLR in a large region with complex terrain and climatic condition.     

一种由叠加速度转换为平均速度的方法

根据地震勘探原理,以二层楔型模型和近似叠加速度求值公式为基础,提出了一种由速度谱求取平均速度或层速度的具体方法,并以二层楔形及五层楔形模型为例,计算其层速度、平均速度与正常时差速度的误差,结果表明其误差较小,完全可以满足地震资料解释的要求。通过实际应用以及与钻孔标定的平均速度的对比验证,表明该方法对于煤田地震勘探是适用的,特别是该方法可以直接求出沿界面法线方向的平均速度,提高时深转换的精度。