空间功能视角下的公共服务对房价的影响——以成都市为例

房价的快速上涨和城市内部房价的巨大差异引起社会广泛关注,调控房价,防止局部区域房价过热势在必行。本文从城市空间功能的视角出发,以成都市2016年房价为例,基于地理探测器分析公共服务对房价的影响。结果表明：成都平均房价为8480元/m²,并从市中心沿交通环线和放射状干线同时向郊区递减,形成圈层加放射格局,总体上呈现西高东低、南高北低的特点。公共服务(主要包括医疗、金融和教育服务)对房价的影响以第三圈层和西南方最为显著,且高于城市层面上整体的影响。公共服务对房价的影响显著受不同区域的空间功能差异的影响,公共服务和空间功能差异会加剧房价的分异格局,并推动局部房价过热。因此,显著地受到在房价调控中,不仅要有传统的金融、经济政策,还要注重空间功能和公共服务的优化。     

The almost constant-speed two-body problem with resistance

The almost constant-speed motion of a mass acted upon by a Newtonian attraction and a resisting force is treated. The equation of orbit is derived for a specific type of resistance which covers the familiar case of Danby's drag(=r ^–2) whilst the vector invariants are obtained by direct operation on the vector form of the equation of motion.     

基于TIC的多时相遥感影像相对辐射归化处理

采用不变点群法(temporally invariant cluster,TIC),由两时相影像的NDVI点密度图确定两个TIC中心并建立辐射归化处理方程,对影像的NDVI进行相对辐射归化处理。与其它辐射归化处理方法相比,该方法简单、有效且精度高,对轻微的植被物候变化敏感且影像不变特征点较少时也能进行辐射归化处理,可有效应用于土地利用/覆盖、植被物候及景观等变化监测。     

K-means算法复杂度的能量分析方法

传统的算法复杂度分析方法重点对算法的内在流程进行分析,而且对于数据挖掘时具有很大不确定性,执行时间不能准确确定.用物理学原理从能量的角度对数据挖掘中的经典聚类算法K-means进行分析,并从算法的本质上推导出其复杂度下限,推导出该算法能优化到的极限值.     

A study on the early-warning technique concerning debris flow disasters

According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN)real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system′s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.     

基于自定义RDD的海量遥感图像并行镶嵌方法

图像镶嵌是遥感图像处理中的重要内容,在跨区域遥感图像分析中发挥重要作用。为了解决传统遥感图像并行算法中存在的计算节点利用率低、频繁数据I/O等问题,本文根据Spark分布式内存计算框架,充分利用Spark利于迭代数据处理的优势,提出了一种基于Spark自定义RDD（弹性分布式数据集）的并行镶嵌方法。该方法首先在集群的多个节点上通过相位相关法执行图像重叠区域估计操作,从而提高了图像重叠区域估计的多节点并行计算;然后,通过重写Spark中RDD的compute和getPartitions方法,自定义针对遥感图像处理的RDD,并将图像镶嵌中的重叠区域估计、图像配准和图像融合3个关键步骤作为自定义RDD的Transformation类型的操作算子;最后,通过隐式转换创建自定义RDD,并调用自定义RDD的操作算子实现图像镶嵌的并行处理。实验结果表明,与传统基于MPI的并行镶嵌算法相比,该方法在保证图像镶嵌效果的基础上,能够有效提高大数据量的图像镶嵌效率。     

区域GPS网实时计算可降水量的若干问题

目前地基GPS气象学测得的可降水量 (PWV )精度好于 2mm ,但在利用区域GPS网实时计算每个测站上空的PWV时 ,要涉及到很多常规GPS资料处理时所忽略的问题 ,如需考虑数据处理软件和计算方式的选择、站坐标的确定和约束、轨道的使用方法、网外辅助站最佳数量的确定、海潮对实时计算PWV的影响以及实时应用于气象服务时的端部效应等问题。利用上海GPS综合应用网获取的 2 0 0 2年 6、7月份长江三角洲地区入梅前后的数据 ,分析了利用区域性的GPS网实时计算高精度的PWV时要解决的各种问题 ,探讨了其数据处理方案     

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A Reconnaissance Method for Delineation of Tracts for Regional-Scale Mineral-Resource Assessment Based on Geologic-Map Data

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible.     

卫星图像中不同水体类型识别研究

在具有高空间分辨率特性的图像上,城市中大型建筑物、道路、河流、湖泊和其他人工地物形状特征和纹理特征清晰可辨。针对高分辨率卫星图像的特点,文章以水体类型识别为例,从卫星数字图像目标地物波谱特征抽取入手,通过图像分类,将水体从背景中分离并予以识别,同时实现像素重组。在区域分割与边界跟踪基础上,对卫星图像进行水体形状特征的抽取与描述,实现不同水体类型的识别。