新疆呼图壁地下储气库的InSAR形变监测与模拟

利用TerraSAR-X卫星2013-08~2014-08的17景雷达影像,采用小基线集（small baseline subset,SBAS）InSAR技术获取呼图壁(HTB)地下储气库（underground gas storage,UGS）运行期间的地表形变序列,并结合UGS注（采）气井口的压力数据,采用多点源Mogi模型,对HTB UGS的形变场进行模拟。结果表明,整个UGS区域的形变特征为非连续分布,形变与注（采）气压力变化具有较好的相关性;注（采）气期间沿卫星视线向(LOS)的形变峰值分别为10 mm和-8 mm;采用自适应前向搜索法,基于多点源Mogi模型初步模拟注（采）气期间的形变过程,当UGS的注（采）气平均气压为18 MPa和15 MPa时,LOS的形变可达7 mm和-4 mm,地表形变的大小与注（采）气井口密度有关;UGS的储气分布呈非均匀状态,即地下气库结构复杂多变。     

BDS多路径效应特征及其对静态基线解精度的影响

为研究BDS载波相位多路径效应的特征,在强多路径环境下进行连续多天短基线静态数据采集,并计算双差观测值残差序列,分GEO、IGSO、MEO 3类卫星分析BDS多路径重复性,在此基础上研究多路径效应对BDS静态基线解精度的影响。结果表明,BDS多路径误差具有较强的重复性,其中GEO及IGSO卫星的多路径误差重复周期为1 d,MEO卫星的多路径误差重复周期为7 d;GEO卫星的多路径误差具有系统性偏移,但不是一个常数,而是随时间发生缓慢变化,因此长时间的静态观测并不能平滑该误差,从而导致在较强多路径环境下,BDS多路径误差对其静态解的影响可达cm级。     

大城市有利于小城市的经济增长吗?——来自长三角城市群的证据

厘清大城市是否有利于小城市经济增长这一问题,对于贯彻大中小城市和小城镇协调发展的国家新型城镇化战略具有重要意义。以长三角108个小城市为例,在传统经济增长模型中加入到大城市的地理距离、行政边界、市场潜能等因素,估计不同等级的大城市对小城市经济增长的空间影响及其异质性。研究发现：临近大城市有助于促进小城市的经济增长,并未发现存在集聚阴影效应的直接证据;空间相互作用的方向更多体现为高等级城市对低等级城市的影响,来自副省级城市的增长溢出最为显著,同层级小城市之间的空间关联效应相对微弱;城市间存在一定程度的市场分割,行政边界的存在阻碍了空间溢出效应的发挥。最后从强化中心城市的辐射带动功能、促进不同规模城市空间溢出效应的全域性释放、破除行政区经济的束缚等方面提出了促进大中小城市和小城镇协调发展的政策启示。     

环境损害鉴定评估的土壤基线确定方法

近年来,国内环境污染事故频繁发生,由此引发的环境损害问题日益严重。环境损害鉴定评估是中国推行的一项应对环境污染损害的重要环保举措,而基线则是确定损害的关键。基线确定作为损害评估与修复的重要组成部分,是科学评估的关键技术环节和重要前提,也是中国开展环境损害鉴定评估亟待解决的问题。总结国际上常用的4种基线确定方法：即历史数据法、参考点位法、环境标准法和模型推算法的优缺点及应用情况,探讨不同基线确定方法的具体工作步骤,并结合中国土壤环境研究工作积累与进展,提出中国土壤基线确定基本原则和推荐“4步法”工作程序,对中国开展土壤环境损害鉴定评估工作具有重要的理论意义和科学指导作用。     

小口径钢管桩与固结灌浆技术联合应用于岩溶地基处理

以工程实践为例,简述复杂岩溶地基处理中小口径钢管桩与固结灌浆技术联合应用的设计、施工工艺及应用效果。     

小口径割管器的设计与应用

某盐井施工时,在245．00—270．00m孔段有25m钻具被水泥固结,进行透孔作业时,扫至孔深250．60m时,扫孔用岩心管被扫落的钻杆接头碎块卡住拧断,透孔时发现孔内遗留3．2m断岩心管、钻头等物。根据钻孔结构与遗留钻具的特点．自行设计一种主要由活塞柱、割刀片和复位弹簧组成的小口径割管器,将水泥固结钻具割断,并将钻具和多种残留管材打捞出孔。从割断后打捞上来的钻杆分析,钻杆切割面光滑、平整,钻杆被完全切透,说明此种割管器设计合理,各部件动作有效。     

基于凸壳构造技术的领海基点选取问题研究

领海基点的选取数量及其空间点位分布的不同,对海域划界结果有着重要的影响.在传统的领海基点选取工作中缺乏一种有效的用于检验选取方案优劣的数学模型,因而这一工作中存在着不确定性因素.为了解决这个问题,提出了利用最小凸包(凸壳)构造技术实现领海基点最优选取的思路和方法,并在此基础上对某群岛的领海基点选取方案作了实例分析.     

Boundaries Make a Difference: The Effects of Spatial and Temporal Parameters on Conservation Planning*

Conservation planning and resulting ecological target identification require selection of both a planning area boundary and temporal baseline or reference condition. We examined the effects that these selections can have on resulting amount and location of identified conservation targets. A gap analysis for California was conducted using five different sets of ecoregion boundaries to identify and compare existing conservation shortfalls in major land cover type representation in protected areas using a threshold of 30 percent per ecoregion per type as the minimum required for future ecological viability. Another gap analysis was run for a single ecoregion using two temporal baselines (current and pre-1900) for the land cover followed by a comparison of identified conservation needs. We found that the boundaries of different ecoregional schemes affected both the total area needed to meet the per ecoregion land cover conservation goals and the spatial location of underprotected land cover types. Choice of temporal baseline also had a significant effect on the establishment of conservation targets for the highly human-impacted Central Valley ecoregion. To meet the given conservation threshold using a historic rather than contemporary baseline, a substantial amount of restoration is required. The results can help identify areas of both conservation needs consensus and those that vary widely based on the chosen planning boundary, as well as aid in the selection of appropriate restoration targets in degraded ecosystems. Because all landscapes are continuous in nature and planning area boundaries are discrete, similar results are likely to be found in analyses conducted in other regions.     

Stochastic model-based methods for handling uncertainty in areal interpolation

Handling of uncertainty in the estimation of values from source areas to target areas poses a challenge in areal interpolation research. Stochastic model-based methods offer a basis for incorporating such uncertainty, but to date they have not been widely adopted by the GIS community. In this article, we propose one use of such methods based in the problem of interpolating count data from a source set of zones (parishes) to a more widely used target zone geography (postcode sectors). The model developed also uses ancillary statistical count data for a third set of areas nested within both source and target zones. The interpolation procedure was implemented within a Bayesian statistical framework using Markov chain Monte Carlo methods, enabling us to take account of all sources of uncertainty included in the model. Distributions of estimated values at the target zone level are presented using both summary statistics and as individual realisations selected to illustrate the degree of uncertainty in the interpolation results. We aim to describe the use of such stochastic approaches in an accessible way and to highlight the need for quantifying estimation uncertainty arising in areal interpolation, especially given the implications arising when interpolated values are used in subsequent analyses of relationships.