农村劳动力转移就业的时空路径——以安徽省4个样本村为例

借鉴时间地理学理论与方法,提出农村劳动力转移就业时空路径概念。以安徽省4个样本村为例,使用ArcGIS、SPSS等软件进行数据分析,得出农村劳动力转移就业时空路径的基本类型与特征:① 农村劳动力依据时空路径特征可分为稳定型、逐步稳定型、漂泊不定型、回流型、逐步开拓型、断续型六种类型;② 4个样本村劳动力打工时空路径演化有明显的地域差异;③ 21世纪初期是农村劳动力全面接受打工就业方式的时期,就业行业主要集中在建筑业、制造业、服务业,“老家亲戚、朋友”是最重要的打工媒介;④ 农村劳动力在打工地和家乡间的流动节律有“春节型”、“节假日型”、“休息日型”、“每日型”四种类型;⑤ 农村劳动力转移就业具有明显的空间指向和粘性特征,家乡是重要的结点空间,社会经济地理位置是地域差异形成的重要原因。     

Primary investigation of statistical correlation between changes in ice volume and area of glaciers

This study makes an attempt to investigate through statistical analysis the correlation between changes in ice volume and area of glaciers. Using data from nine sample glaciers in the Tian Shan, the results show that a linear relation exists between changes in ice volume and area, with a correlation coefficient of 0.700. However, the accuracy estimation is difficult due to the limited number of samples. The correlation was not improved after adding eleven glacier samples in other mountains. Two reference glaciers are then analyzed in more detail. The linear correlation coefficient is higher than 0.800 when using the observed changes in ice volume and area during different periods on Urumqi Glacier No. 1, which suggests that the linear relation is valid for one glacier for different periods if its shape does not change noticeably and also for other glaciers of the same shape during the same period. The relation between changes in ice volume and area of Qingbingtan Glacier No. 72 is different during different periods due to change in the shape of the glacier tongue and the influence of the debris cover. Moreover, errors in glacier-change monitoring and-volume estimation have an important influence on the correlation results. Therefore, further study needs to focus not only on the distinction between glacier types and between different periods but also on the accuracy of volume estimation.     

湍流度随高度的变化及其对城市宏观地形的依赖

分别构建广州主建成区垂直比例尺为1﹕2 000、1﹕1 000和1﹕500的3个建筑物模型,利用大型边界层风洞,在西北和东南两风向下,基于中性流模拟分析了复杂城市地形下湍流度随高度的变化及其对宏观地形的依赖。结果表明：风廓线指数α与不同高度的湍流度之间的关系密切,利用现有模型,根据4类粗糙度边界层和不同垂直比例尺,可确定相应的湍流度随高度变化模型的主要系数,预测精度高。城市地形下最大湍流度面发育在0~0.2 h之间狭窄的范围内。用湍流度形态指数β来表征湍流度随高度的变化,无论城市屋脊还是平坦地形,随着风程区的延伸,廓线的指数α升高,湍流度形态指数β降低。表明同一高度湍流度值具有由迎风区、丘顶区向背风区增高,沿风程逐渐增大的规律,对地形部位和风程的依赖性强,与来流翻越简单地形时的特征一致。     

佛山市顺德区飞鹅山Ⅲ号滑坡形成机理与防治技术

采用工程地质钻探、物探、地质测绘及室内试验等技术方法探讨飞鹅山Ⅲ号滑坡形成机理与防治技术。结果表明：1）滑坡体主要岩性为泥质粉砂岩,飞鹅山滑坡属于新形成的深层中型牵引式滑坡,在平面上呈圈椅状。2）滑坡属于双层滑面滑坡,主滑面以中型深层滑坡为主,主滑体上部发育中型中厚层滑坡。3）滑坡产生的原因为：(1)泥质粉砂岩倾向与坡向基本一致,且岩层倾角为中等倾角;(2)人工开挖使坡脚形成高陡临空面,抗滑力大为降低;(3)雨水沿层面及节理裂隙入渗至坡体深部,大大增加岩土体容重,同时泥质粉砂岩遇水软化,抗剪强度显著降低。4）结合该滑坡区地质环境条件,采用坡面削坡+锚杆（索）+格构梁+双排预应力锚拉抗滑桩+三维网植草绿化+截排水+毛石挡墙的综合治理方法进行防治,监测结果显示该滑坡变形及位移已得到有效控制,整治效果良好。     

基于GWR模型的道路网络对森林碳密度干扰的地理变异

以闽江上游地区为例,在分析三明市2007—2016年森林碳密度时空动态的基础上,采用常规的以及改进后的道路网络测度指标,应用缓冲区分析方法和地理加权回归（Geographically Weighted Regression,GWR）模型,从线上和面上分别探讨道路网络对森林碳密度干扰的地理变异规律。结果表明：① 碳密度受到道路网络的较大影响,路网影响域内外碳密度的大小排序为：路网影响域内＜整个研究区＜路网影响域外;多条道路影响域重叠区的碳密度(26.330 Mg/hm²)明显低于单条道路影响域的碳密度(37.406 Mg/hm²);不同等级道路影响域的碳密度由大到小依次为县道＞高速＞省道＞其它道路＞国道＞乡道。道路网络对2007—2016年碳密度的降低也有明显影响。② GWR模型的分析结果表明,路网对碳密度的影响程度随着样点的变化而变化,具有“空间非平稳性”。碳密度随着路网密度的增加而降低,而随着离道路距离的增加而增加。③ 研究区西北部和中部,GWR的回归系数及相关系数均较大,表明这2个区域道路对碳密度影响大且解释力皆较强。     

东北地区农业现代化发展水平测度与时空演变分析

率先实现农业现代化是全面振兴、全方位振兴东北老工业基地的重大任务。根据中国农业现代化理论内涵和实践要求,从投入、产出、社会发展3个维度构建农业现代化评价指标体系,对2008年、2018年东北地区40个地级行政单元的农业现代化水平进行测度与阶段划分。结果表明：① 从空间格局看,东北地区农业现代化水平呈现出“沿东北-西南轴线地区较高,轴线东西两侧地区较低”的空间格局,三江平原、松嫩平原及环渤海地区为高值集聚区;② 从发展速度看,东北地区各地市农业现代化水平整体有所提高,北部地区发展速度整体大于南部;③ 从所处阶段看,2018年处在农业现代化“初步实现”的地市占比达86%,东北地区农业现代化水平总体处在由“初步实现”向“基本实现”的转变阶段;④ 农业现代化发展水平3个分维度指标在地理空间上也表现出一定的地域分异格局;⑤ 不同地区应针对发展优势及资源禀赋,走符合自身特点的农业现代化路径。     

中国交通CO2排放时空格局演变及其影响因素——基于2000~2012年30个省（市）面板数据的分析

通过构建交通CO₂排放模型对2000~2012年中国30个省（市）的交通CO₂排放时空演变特征进行了分析。并采取“由大到小”逐步回归的建模方式,在传统的固定效应模型（面板数据模型）基础上引入时间固定效应,构建了双向固定效应模型对中国交通CO₂排放的社会经济、城市形态、交通发展等方面的影响因素进行研究。结果表明：2000~2012年期间,中国交通CO₂排放总量和人均交通CO₂排放量分别以9.29%和8.69%的年均增速增长,前者的区域差异呈先增后减趋势,后者的区域差异则首先呈周期性波动,而后一直保持减少趋势。人均GDP和城镇居民家庭人均可支配收入对人均交通CO₂排放具有显著的正向效应,表明社会经济发展和居民收入水平提高是交通CO₂排放增长的主要驱动因素。城市人口密度对交通CO₂排放亦具有显著的正向效应,这意味着未来中国应加强对城市人口密度的规划控制,以避免因人口过度集聚而额外增加产生交通CO₂排放。公共交通发展水平对交通CO₂排放增长具有显著的负向效应,但小汽车拥有率对交通CO₂排放的影响并不显著。     

Atmospheric insight to climatic signals of δ~(18)O in a Laohugou ice core in the northeastern Tibetan Plateau during 1960–2006

δ~(18)O variations;;ice core;;outgoing longwave radiation;;meridional wind;;northeastern Tibetan Plateau     

Capacity of soil loss control in the Loess Plateau based on soil erosion control degree

The capacity of soil and water conservation measures, defined as the maximum quantity of suitable soil and water conservation measures contained in a region, were determined for the Loess Plateau based on zones suitable for establishing terraced fields, forestland and grassland with the support of geographic information system (GIS) software. The minimum possible soil erosion modulus and actual soil erosion modulus in 2010 were calculated using the revised universal soil loss equation (RUSLE), and the ratio of the minimum possible soil erosion modulus under the capacity of soil and water conservation measures to the actual soil erosion modulus was defined as the soil erosion control degree. The control potential of soil erosion and water loss in the Loess Plateau was studied using this concept. Results showed that the actual soil erosion modulus was 3355 t?km^-2?a^-1, the minimum possible soil erosion modulus was 1921 t?km^-2?a^-1, and the soil erosion control degree was 0.57 (medium level) in the Loess Plateau in 2010. In terms of zoning, the control degree was relatively high in the river valley-plain area, soil-rocky mountainous area, and windy-sandy area, but relatively low in the soil-rocky hilly-forested area, hilly-gully area and plateau-gully area. The rate of erosion areas with a soil erosion modulus of less than 1000 t?km^-2?a^-1 increased from 50.48% to 57.71%, forest and grass coverage rose from 56.74% to 69.15%, rate of terraced fields increased from 4.36% to 19.03%, and per capita grain available rose from 418 kg?a^-1 to 459 kg?a^-1 under the capacity of soil and water conservation measures compared with actual conditions. These research results are of some guiding significance for soil and water loss control in the Loess Plateau.