新型移动三维激光扫描技术在盾构管片椭圆度检测中的应用

铁运营阶段对隧道结构的变形监测保证了地铁运行的安全,而椭圆度检测是地铁隧道结构检测的重要工作。本文简单介绍了传统椭圆度检测的基本方法,分析了新型移动三维激光扫描检测系统基本原理及隧道椭圆度检测的方法和处理流程。通过工程案例实际应用以及对检测结果的综合分析,证明了移动三维激光扫描技术在盾构管片椭圆度检测中的优势。     

城市局部气候分区对地表温度的影响 ——以大连市区为例

以大连市区建筑数据、SPOT 5和Landsat 8遥感数据为基础,运用局部气候带分类、地表温度反演方法,研究大连市局部气候带分区类型和特征,进而分析不同局部气候带对城市地表温度的影响。研究结果表明：①大连市建筑类型高度主要为低层建筑、多层建筑和中高层建筑,建筑密度为中密度和较高密度,甘井子区分布大量森林绿地,中山区具有丰富的公园绿地;②地表温度整体偏高,空间上呈现东高西低的趋势,其中半数以上地区地表温度达到28℃~31℃,并且有超过1%的地区地表温度大于38℃,该区域出现极端高温;③同一建筑高度上,密度越大的建筑区域,地表温度越高;同一建筑密度,多层建筑高度覆盖区地表温度较高。森林绿地地表温度最低,公园绿地和社区绿地地表温度几乎一致,附属绿地地表温度最高。     

基于DEM的山地地理可照时数空间分布估算统计模型——以重庆为例

为了建立合理、准确且便于估算和应用的山地地理可照时数空间分布模型,本文以重庆为例,首先利用分布式模型估算了30 a平均年和各月可照时数,并利用基于气象行业标准得到的理论值进行了验证;其次,以栅格单元为统计样本,建立了基于地形尺度的可照时数估算的统计模型。结果表明:(1)基于分布式模型的模拟结果具有较高可信度,除10月外,其他各月和年的相对误差均小于10%,且东北和东南部的相对误差较中西部高。(2)西部方山丘陵区的可照时数高,中部平行岭谷区次之,东北和东南部低。冬季可照时数的空间异质性最大,夏季次之,春秋季接近,均较小。(3)各月和年可照时数与主要地理和地形因子之间的相关关系均表现为极显著性,各月复相关系数在0.7929~0.8277,年复相关系数为0.8522。(4)重庆可照时数估算统计模型在一定程度上简化了分布式模型的计算步骤和计算量,便于其应用,并可为其他地区估算可照时数提供方法参考。     

格尔木河水质现状及生态风险评估

为了解经济迅速发展背景下格尔木河流域水体中痕量元素分布、水环境质量现状和生态风险,对格尔木河9个采样点水样21种痕量元素的分布及相关性进行了分析,以Cu、Zn、Hg、Cd、Cr和Pb为目标重金属,评估了格尔木河水质现状及生态风险。结果表明:重金属Pb浓度在所有水样中均低于检出限,其它痕量元素浓度在0.001(Cd)～6297.013(Sr)μg·L~(-1)范围变化。根据相关性分析,推测格尔木河水体中Li、Sc、Ti、V、Cu、Ge、Rb、Sr、Mo、Cd来源可能相同。采样点水样6种重金属浓度均达到地表水环境质量I类的标准。采用5种方法评价了格尔木河水质现状,研究区水质处于无污染的理想状态。格尔木河重金属引发的潜在生态风险处于低风险水平(生态风险指数变化范围为0.35～0.68)。     

The effect of terrain factors on rice production: A case study in Hunan Province

Journal of Geographical Sciences - Rice (Oryza sativa L.) is the most important staple crop of China, and its production is related to both natural condition and human activities. It is fundamental...     

Developing a comprehensive evaluation method for Interconnected River System Network assessment: A case study in Tangxun Lake group

Journal of Geographical Sciences - The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It...     

Multiscale geographically and temporally weighted regression: exploring the spatiotemporal determinants of housing prices

Understanding scale effects is important and indispensable for geography studies. However, spatial and spatiotemporal statistical tools for measuring the operational scales of different processes are rather limited. This article extends the popular geographically and temporally weighted regression (GTWR) model to consider operational scale effects by proposing multiscale GTWR (MGTWR), which offers a flexible and scalable framework for identifying and analysing multiscale processes by specifying flexible bandwidths for various covariates. Then, MGTWR is employed to explore spatiotemporal variations and how influential factors are associated with housing prices in Shenzhen. This article attempts to extend GTWR to MGTWR in consideration of scale effects, thereby highlighting the importance of different levels of spatiotemporal heterogeneity. Furthermore, the empirical results of this study can provide valuable policy implications for real estate development in areas where urban planning should address multiscale effects in both temporal and spatial dimensions.     

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.     

Numerical Study on Tidal Mixing in the Bohai Sea

The spatial and temporal variability of tidal mixing in Bohai Sea is studied using a numerical approach. In calculating tidal mixing, accurate barotropic tidal current is obtained via a harmonic analysis package utilizing the simulated current output from a high-resolution regional ocean model. And a “small-scale” roughness map is adopted to describe the detailed topographic features of Bohai Sea. It is shown that the tidal mixing estimated in Bohai Sea is much higher than the level of global background, and fluctuates considerably at some regions within a single day. In Liaodong Bay, Bohai Bay and Bohai Strait, the mixing varies greatly, with the peak value of O (10^?2) m² s^?1. The order of magnitude of mixing in Laizhou Bay is about O (10^?5～10^?3) m² s^?1. Mixing with background level of O (10^?5) m² s^?1 only appears in central area. Result also shows that rough topography plays relatively a more important role than tidal current in enhancing diapycnal mixing in Bohai Sea. The distributions of tidal mixing in selected sections reveal that the vertical stratification in Bohai Sea is not obvious, generally renders a barotropic structure.     

透明胞外聚合颗粒物碳输运新途径

目前大家普遍认为,透明胞外聚合颗粒物(Transparent Exopolymer Particles,TEP)因其独特的凝聚效应导致碳通量向海底输出。但是,近几年的研究表明TEP不仅影响了碳沉降途径,其本身能够悬浮甚至向海水表层迁移,导致其在海洋微表层(Surface Micro-layer, SML)积累,最终显著影响海洋表层碳通量。TEP和其他颗粒物聚集形成凝聚物后,其运动趋势则由凝聚物中TEP的含量占比,即最终颗粒物密度所决定。一个新的值得注意的现象是,密度低的TEP通过与其他微粒聚合形成表面活性物质(Surface-active Substances, SAS),会在海洋–大气界面形成薄膜,显著影响海–气CO₂交换通量,甚至对全球气候变化造成影响。