Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data

The accurate mapping of urban housing prices at a fine scale is essential to policymaking and urban studies, such as adjusting economic factors and determining reasonable levels of residential subsidies. Previous studies focus mainly on housing price analysis at a macro scale, without fine‐scale study due to a lack of available data and effective models. By integrating a convolutional neural network for united mining (UMCNN) and random forest (RF), this study proposes an effective deep‐learning‐based framework for fusing multi‐source geospatial data, including high spatial resolution (HSR) remotely sensed imagery and several types of social media data, and maps urban housing prices at a very fine scale. With the collected housing price data from China's biggest online real estate market, we produced the spatial distribution of housing prices at a spatial resolution of 5 m in Shenzhen, China. By comparing with eight other multi‐source data mining techniques, the UMCNN obtained the highest housing price simulation accuracy (Pearson R = 0.922, OA = 85.82%). The results also demonstrated a complex spatial heterogeneity inside Shenzhen's housing price distribution. In future studies, we will work continuously on housing price policymaking and residential issues by including additional sources of spatial data.     

地理国情普查成果在土地资源监测中的应用初探

以江西省某县地理国情普查数据为基础,研究其与土地变更调查数据的相似性与差异性,结合土地资源监测的热点,初步探究地理国情普查成果在土地资源监测中应用,为地理国情普查成果应用提供思路与方向。     

Spillover or crowding out? The effects of environmental regulation on residents’ willingness to pay for environmental protection

Natural Hazards - Existing researches about environment regulation mainly focus on its effect on enterprises’ production decision-making behavior but neglects the effect on the individual and...     

Effects of different soil and water conservation measures on hydrological extremes and flood processes in the Yanhe River,Loess Plateau,China

The runoff and sediment load of the Loess Plateau have changed significantly due to the implementation of soil and water conservation measures since the 1970s. However, the effects of soil and water conservation measures on hydrological extremes have rarely been considered. In this study, we investigated the variations in hydrological extremes and flood processes during different periods in the Yanhe River Basin (a tributary of the Loess Plateau) based on the daily mean runoff and 117 flood event data from 1956 to 2013. The study periods were divided into reference period (1956–1969), engineering measures period (1970–1995), and biological control measures period (1996–2013) according to the change points of the annual streamflow and the actual human activity in the basin. The results of the hydrological high extremes (HF1_max, HF3_max, HF7_max) exhibit a decreasing trend (P?<?0.01), whereas the hydrological low extremes (HBF1_min, HBF3_min, HBF7_min) show an increasing trend during 1956–2013. Compared with the hydrological extremes during the reference period, the hydrological high extremes increased during the engineering measures period at low (<?15%) and high frequency (>?80%), whereas decreased during the biological control measures period at almost all frequencies. The hydrological low extremes generally increased during both the engineering measures and biological control measures periods, particularly during the latter period. At the flood event scale, most flood event indices in connection with the runoff and sediment during the engineering measures period were significantly higher than those during the biological control measures period. The above results indicate that the ability to withstand hydrological extremes for the biological control measures was greater than that for the engineering measures in the studied basin. This work reveals the effects of different soil and water conservation measures on hydrological extremes in a typical basin of the Loess Plateau and hence can provide a useful reference for regional soil erosion control and disaster prevention policy-making.

     

藏南泽当地区大反向逆冲断层变形研究——以磁组构与EBSD组构分析为例

仁布-泽当逆冲断层是喜马拉雅大反向逆冲断层（GCT）在藏南地区的重要延伸部分,也是喜马拉雅造山带北部边界新生代最为活动的构造单元之一。新生代以来特提斯喜马拉雅的构造变形组构特征的研究对于深入理解碰撞造山带演化与高原隆升具有重要构造意义。本文综合GCT泽当-琼结段断层的宏观与微观变形特征,对断裂带石英脉、围岩中石英和云母矿物的电子背散射（EBSD）组构及断层两侧岩石磁组构（AMS）特征进行对比分析。结果表明对AMS主要贡献来自顺磁性云母、绿泥石等,磁化率各向异性椭球体以压扁状为主,磁面理与构造面理（劈理、断层面）基本重合,显示较强的构造变形磁组构特征;磁线理优选方向近南北向,且与观测北向逆冲断层方向一致,揭示剪切作用在变形过程中的持续作用。研究发现泽当地区GCT附近石英微观结构从围岩至断层区,石英至少呈现3种不同类型的微观变形机制：围岩区溶解蠕变、断裂带石英以膨凸重结晶和亚颗粒旋转重结晶作用为主。断裂带石英的c轴EBSD组构指示变形为低温（300~400℃）环境,其中黑云母的结晶学优选（CPO）与磁组构主轴优选方向存在高度的一致性,进一步证实了顺磁性矿物黑云母对AMS的主要贡献。综合研究表明泽当地区GCT的韧性变形是断层处在中上地壳韧性带的活动阶段变形的结果,也代表了特提斯喜马拉雅在碰撞、高原隆升期的变形主要特征。     

滇东南都龙超大型锡锌多金属矿床黄铁矿LA-ICPMS微量元素组成研究

滇东南马关都龙是一个以锡锌为主,共-伴生铟、铜、铅、钨、铁、银等多种元素的锡锌多金属超大型矿床。虽然前人从矿物学、矿床地球化学、年代学等不同角度开展了较多的研究,该矿床锡锌多金属矿化为燕山晚期岩浆热液活动的产物已是不争的事实,但关于该矿床是否存在热水沉积作用及其与锡锌多金属成矿作用的关系依然存在较大争议。本文选取都龙矿区广泛存在的黄铁矿作为主要研究对象,在矿相学基础上利用LA-ICPMS对不同阶段黄铁矿的微量元素组成开展了系统的研究。野外及显微鉴定结果表明,矿区存在四种类型(期次)的黄铁矿,即:鲕状黄铁矿Py1;穿切或交代Py1的细脉状黄铁矿Py2;与闪锌矿等硫化物共生的自形黄铁矿Py3;包裹早期黄铁矿或闪锌矿等硫化物的他形黄铁矿Py4。LA-ICPMS分析结果表明,该矿床黄铁矿中富集多种微量元素,其中Co、Ni、As、Ge等元素以类质同象的形式存在黄铁矿晶格中,而其余元素多以显微矿物包体形式赋存于黄铁矿中。上述四期黄铁矿微量元素组成存在较大差别,Py1相对富集Zn和As,而其余微量元素含量较低,Co与Ni含量较低,Co/Ni比值远低于1.00,其微量元素组成与典型沉积作用形成黄铁矿基本一致; Py2与Py1具有相似的微量元素组成特征,其Co/Ni比值接近Py1变化范围; Py3和Py4除富集Zn、As外,Mn、Co、Ni、Cu、Sb、Pb、Bi元素含量也相对较高,其Co/Ni比值相对较高,多大于1,与典型岩浆热液型黄铁矿微量元素组成相似,而与沉积型黄铁矿差异明显。结合各阶段黄铁矿产出地质特征,对比不同类型黄铁矿微量元素组成,本研究认为:Py1鲕状黄铁矿为热水沉积作用形成; Py2为Py1变质改造形成的细脉状黄铁矿,其微量元素继承了Py1; Py3为岩浆热液活动形成的自形黄铁矿; Py4为岩浆热液活动晚期形成的他形黄铁矿,Ag和Bi组成作为区分不同成因类型黄铁矿的化学指标的潜力。矿区早期沉积作用形成鲕状黄铁矿过程可能为后期成矿作用提供了部分硫源及少量Zn等成矿物质,海西-印支期区域变质改造作用对矿区成矿作用影响不大,而燕山晚期岩浆热液活动才是矿区锡多金属大规模成矿作用的主导因素。     

江南钨矿带桂林郑钼钨矿床钼的赋存状态、时空分布及其研究意义

安徽桂林郑钼钨矿床位于江南钨矿带北部,是目前区内唯一钼储量达到大型的钼钨矿床。本文在对该矿床地质特征和已有成果总结基础上,详细观察了各代表性矿化蚀变样品的岩相学特征,提出该矿床具镁质矽卡岩矿床特征,是桂林郑花岗斑岩熔体与奥陶系白云质灰岩地层交代的产物。矿石类型可分为靠近岩体(100m)浸染状矿石和远离岩体( 100m)的条带状矿石,分别赋存在接触交代矽卡岩和层控矽卡岩中。桂林郑矿床的矿石矿物为富钼白钨矿(钼钙矿-白钨矿系列),可分为三个世代,分别形成于无水矽卡岩阶段(Sch-Ⅰ)和含水矽卡岩-氧化物阶段(Sch-Ⅱ和Sch-Ⅲ),辉钼矿仅在浸染状矿石富钼白钨矿(Sch-Ⅲ)边部少量发育。不同矿石类型、不同世代富钼白钨矿的电子探针成分分析显示,富钼白钨矿的钼含量(MoO_3%)在5.75%～71.02%之间,均值为46.00%(n=224),总体具有超常富钼的特点;从无水矽卡岩阶段到含水矽卡岩-氧化物阶段(早→晚)、从浅部的条带状矿石到深部的浸染状矿石(浅→深),富钼白钨矿MoO_3含量有降低趋势。桂林郑钼钨矿床是首个以富钼白钨矿为主要矿石矿物的钼-多金属矿床,这一特殊钼钨矿床的发现深化了矽卡岩钼钨矿床的成因认识,同时对江南钨矿带内区域成矿规律与找矿勘探工作的推进提供了依据。     

粤中从化地区佛冈岩基白垩纪花岗岩LA-ICP-MS锆石U-Pb年代学及地球化学特征

LA-ICP-MS锆石U-Pb定年结果表明,粤中从化地区发育一套白垩纪花岗岩,其形成时代为～145 Ma,属佛冈岩基的一部分.地球化学研究表明,花岗岩的SiO2含量为71.9％～77.72％(平均74.89％),Al2O3含量为12.17％～14.42％(平均13.24％),A/CNK为1.31～1.49(平均1.4),ALK全碱指数7.92～9.15(平均8.5),为过铝质高钾钙碱性系列花岗岩.它们的稀土元素总量(ΣREE)为(128.8～393.8)×10-6,Eu具负异常,δEu值为0.1～0.4,LREE/HREEE值为2.2～13.3;具有富集Rb、U、La、Nd、Sm和Lu,强列亏损Ba、Nb、Sr、P和Ti等元素特点.元素地球化学特征显示其为高分异I型花岗岩,可能是在高温条件下幔源物质诱导下地壳部分熔融后引发古老地壳杂砂-泥质源岩部分熔融而形成.综合区域地质资料分析,从化地区白垩纪花岗岩可能形成于古太平洋板块向欧亚板块俯冲的陆缘弧构造环境.     

Numerical investigation of the hydrodynamic response of an impermeable sea-wall subjected to artificial submarine landslide-induced tsunamis

Landslides - Landslide-induced tsunamis are common natural hazards that potentially affect the safety and stability of waterfront structures. A numerical tank was constructed using FLOW-3D to...     

四川盆地开江地区WT1井震旦系陡山沱组物源分析及构造背景判断*

为厘清四川盆地开江地区WT1井震旦系陡山沱组地层发育的构造背景,重塑其原型沉积盆地,为重建古地理及油气进一步勘探部署工作提供科学依据,利用岩石学、岩石地球化学及碎屑锆石U-Pb年代学手段对该井陡山沱组物源进行了分析。岩石地化结果表明WT1井陡山沱组沉积物源岩为中基性火山岩类且经历了中等程度化学风化作用;碎屑锆石U-Pb年龄主要记录了915~850Ma、794~714.5Ma以及622~700Ma 3个阶段的构造岩浆活动,与扬子克拉通北缘及邻区Rodinia超大陆的裂解演化过程有关,该构造活动背景下的中基性火山岩是WT1井陡山沱组沉积的主要物质来源。结果表明四川盆地开江地区的陡山沱组发育于拉张伸展构造背景,属克拉通内裂陷盆地沉积,有利于烃源岩层的发育;同时为Rodinia超大陆的裂解演化过程提供了重要的年代学演化证据。该成果对深入认识四川盆地的地质结构、沉积-构造演化以及油气勘探的战略部署等具有极为重要的科学意义。