精准扶贫视角下中国东北农村贫困地域性特征及成因

基于结构性问卷,采用入户访谈及问卷调查的方法,解析中国东北地区农村贫困空间格局与地域性特征,并对区域内部典型农村贫困区贫困问题的形成机制进行探讨与解构。研究认为： 东北地区农村贫困人口与贫困县集中分布在大兴安岭南麓和黑、吉、辽三省与内蒙古东部交界地区以及中俄、中朝边境地区,形成东、西两大片区,西部片区呈带状自北向南延伸,东部片区内存在两个团块状贫困人口集聚区,整体表现出“大集聚,小分散”的空间分布特征。② 区域内部存在5个农村贫困高发区,分别为中俄北部边境贫困高发区、中俄东部边境贫困高发区、松嫩平原贫困高发区、西部贫困高发区、中朝边境贫困高发区;农村贫困发生率“北高南低,西低东高”的特征明显。③ 农村贫困群体以中老年人为主,文化水平整体较低,吃穿与医疗保障问题突出;罹患疾病以及耕地不足、耕地利用率低是导致东北地区农村贫困的主因,发展现代农业和外出务工是消除贫困的重要途径。 ④ 区域内部存在西部农牧交错区、东部边境山地朝鲜族聚居区、东部平原与丘陵过渡区三大典型农村贫困区,西部农牧交错区农村贫困问题的产生主要受农业生产结构单一、农产品市场价格下行、农户自身思想认识落后、基础设施建设滞后、区域自然生态条件不利等多种因素的协同影响;东部边境山地朝鲜族聚居区农村贫困问题主要由劳动年龄人口的持续性外流所引发的系列效应导致;东部平原与丘陵过渡区农村贫困问题的出现主要受地理位置偏远、地形复杂导致自然灾害多发、耕地资源不足的影响。     

图们江下游圈河流域河岸沙丘动态变化

以图们江下游跨国界地区圈河流域河岸沙丘为研究对象,运用遥感与GIS技术,结合遥感影像、地形图等资料,分析该区1984~2015年河岸沙丘空间分布与格局演变,计算河岸沙丘分维值与稳定性指数。结果表明：该区河岸沙丘主要分布在弯曲型河道东岸,呈WNW-ESE向带状展布,面积15.71 km²。近31 a沙丘面积总体呈减少态势,净减少0.09 km²,其中,较少有人类活动的A区,沙丘面积呈减少趋势,减少幅度为8.21%;而受人类活动影响较大的B区,沙丘面积持续增加,尤其近5 a增幅达32%。河岸沙丘分维值虽总体高于内陆沙漠沙丘,但变化不显著,说明河岸沙丘处于相对稳定的发育演化过程中。该研究为图们江下游跨国界地区生态环境可续持发展提供科学依据。     

地理学研究进展与前沿领域

现代地理学涵盖自然地理学、人文地理学和地理信息科学，其发展趋势是：相邻学科的交叉、渗透与融合，加强地理学内部的综合研究，地理过程的微观研究进一步深化，结合实践拓宽应用研究领域，实验与研究手段的现代化，理论思维模式的转变。地理学应在陆地表层过程与格局、全球环境变化及其区域响应、自然资源保障与生态环境建设、区域可持续发展及人地系统的机理与调控、地理信息科学和数字地球战略等前沿领域开拓创新，为促进地球系统科学的发展、协调人地关系等做出积极的贡献。     

科尔沁沙地风沙与湖泊景观演变及影响因素分析

以科尔沁沙地为研究区,基于1975~2015年中等分辨率卫星影像,采用景观格局指数计算及数理统计分析方法,研究该区近40 a来沙地与湖泊景观格局的变化过程,并对其影响因素进行分析。结果表明,近40 a科尔沁沙地风沙地貌覆盖面积呈减少趋势,年均变化率-0.31%,而灌草丛沙丘地、抛物线形沙丘等固定半固定型沙丘面积增加,沙地逆转化趋势明显。沙地景观蔓延度整体下降了2.13,优势度增加了16.55,说明科尔沁沙地斑块连通性与多样性降低。湖泊群面积净减61.24 km²,斑块数减少了66个,湖泊群质心朝ESE方向迁移了35.76 km,湖泊景观分离度呈下降趋势,而集群性有所增加、景观演变趋于稳定。气候因素和人类活动因素是科尔沁沙地演化的驱动因素,尤其社会经济和政策因素可短时间内促进沙地景观的演变过程。     

High-resolution mass spectrometric characterization of dissolved organic matter from warm and cold periods in the NEEM ice core

Dissolved organic matter(DOM) is an important component of ice cores but is currently poorly characterized. DOM from one Holocene sample(HS, aged at 1600–4500 B.P.) and one Last Glacial Maximum sample(LS, aged at 21000–25000 B.P.) from the North Greenland Eemian Ice Drilling(NEEM) ice core were analyzed by ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR-MS). CHO compounds contributed 50% of the compounds identified in negative-ionization mode in these two samples, with significant contributions from organic N, S, and P compounds, likely suggesting that marine DOM was an important source in these samples. Overall, the chemical compositions are similar between these two samples, suggesting their consistent DOM sources. However, subtle differences in the DOM between these two samples are apparent and could indicate differences in source strength or chemistry occurring through both pre-and post-depositional processes. For example, higher relative amounts of condensed carbon compounds in the HS DOM(5%), compared to the LS DOM(2%), suggest potentially important contributions from terrestrial sources. Greater incorporation of P in the observed DOM in the LS DOM(22%), compared to the HS DOM(13%), indicate more active microbiological processes that likely contribute to phosphorus incorporation into the DOM pool. Although these two samples present only a preliminary analysis of DOM in glacial/interglacial periods, the data indicate a need to expand the analysis into a broader range of ice-core samples, geographical locations, and glacial/interglacial periods.     

WRF模式对青藏高原那曲地区大气边界层模拟适用性研究

采用WRF（Weather Research and Forecasting）模式4种边界层参数化方案对青藏高原那曲地区边界层特征进行了数值模拟,并利用"第三次青藏高原大气科学试验"在青藏高原那曲地区5个站点的观测资料对模拟结果进行验证,分析不同参数化方案在那曲地区的适用性。研究表明,YSU、MYJ、ACM2和BouLac方案对2 m气温和地表温度的模拟偏低。BouLac方案模拟的地表温度偏差较小。通过对能量平衡各分量的对比分析发现,温度模拟偏低可能是向下长波辐射模拟偏低以及感热通量和潜热通量交换过强导致的。对于边界层风、位温和相对湿度垂直结构的模拟,局地方案的模拟效果均优于非局地方案。BouLac方案对那曲地区近地层温度、边界层内位温和相对湿度的垂直分布模拟效果较好。      

基于全视野数字图像的能见度估算方法

基于全视野数字图像的能见度估算方法是将全视野图像大气透射率与大气能见度通过曲线拟合方法建立联系,得到估算模型进行能见度估算。首先通过历史全视野图像和对应时刻的大气能见度建立样本数据集,再利用暗原色先验理论获取全视野图像大气透射率,通过多项式拟合方法建立离散样本数据集中大气透射率与对应时刻大气能见度的关系,即全视野图像能见度估算模型,最终将所需估算时刻的数字图像输入估算模型进行能见度估算,得到大气能见度数值。结果表明:建立的基于全视野数字图像能见度估算模型在环境光照均匀时大气能见度估算值与能见度实测值有较好的一致性,可作为前向散射仪的补充观测方法,弥补其采样存在的局限性。     

克氏原鳌虾气象因子影响研究现状与展望

克氏原螯虾主要养殖在长江中下游地区,目前最主要的养殖模式为虾稻共作模式。大量研究结果表明,克氏原螯虾的生长发育与气象要素密切相关。水温在25-30℃时,克氏原螯虾生长较快;16-25℃水温范围内,温度越高,越有利于雌虾卵巢发育;20-30℃水温范围内,水温越高,受精卵孵化时间越短。光明和黑暗时间之比为16 h∶8 h时,最有利于雌虾性腺发育。与克氏原螯虾养殖有关的气象灾害主要有暴雨洪涝、高温热害、低温冷害。鉴于目前的养殖和气象因子影响研究及服务现状,建议气象部门开展虾-稻种养基地气象观测站网建设,开展气温与水温相关性和水温预报研究,以及气象要素对克氏原螯虾影响的定量化研究。     

Field determination for roughness length above the different non-erodible surfaces

Non-erodible elements, for its disturbance to the near-surface airflow, have been widely used in arid and semi-arid regions to protect the surface from wind erosion. Roughness length was usually used to evaluate the protection effect of non-erodible elements from wind erosion. In this study, the wind profiles above five types of non-erodible surfaces including gravel, wheat straw checkerboard barriers, cotton stem checkerboard barriers, shrubs, and herbs were measured and analyzed. The wind velocities above these surfaces increased with height approximately in logarithmic functions. The roughness length of different non-erodible surfaces was calculated by the functions of wind profiles. The results reveal that:(1) Roughness length increased with wind velocity in given wind velocity ranges. (2) On vegetative surfaces, wind did not effectively bend the stems. The threshold wind velocity for bending the stems of Achnatherum splendens was 4 m/s, 10 m/s for Agropyron cristatum, and for Artemisia ordosica, no obvious bending of stems even for wind velocity reaching 12 m/s. (3) Correlation analysis results show that the vegetation''s coverage and frontal area affect the roughness length more significantly than the other parameters. (4) The protective results of these non-erodible elements were evaluated. The checkerboard sand barriers made of cotton stem could provide more effective protection than that made of wheat straw. In the same coverage conditions, vegetation could provide more effective protection from wind erosion than gravel, and the blending of different non-erodible elements especially the combination of blending of vegeation and checkerboard sand barriers could provide more effective protection to the surface.     

Classifying natural-language spatial relation terms with random forest algorithm

The exponential growth of natural language text data in social media has contributed a rich data source for geographic information. However, incorporating such data source for GIS analysis faces tremendous challenges as existing GIS data tend to be geometry based while natural language text data tend to rely on natural language spatial relation (NLSR) terms. To alleviate this problem, one critical step is to translate geometric configurations into NLSR terms, but existing methods to date (e.g. mean value or decision tree algorithm) are insufficient to obtain a precise translation. This study addresses this issue by adopting the random forest (RF) algorithm to automatically learn a robust mapping model from a large number of samples and to evaluate the importance of each variable for each NLSR term. Because the semantic similarity of the collected terms reduces the classification accuracy, different grouping schemes of NLSR terms are used, with their influences on classification results being evaluated. The experiment results demonstrate that the learned model can accurately transform geometric configurations into NLSR terms, and that recognizing different groups of terms require different sets of variables. More importantly, the results of variable importance evaluation indicate that the importance of topology types determined by the 9-intersection model is weaker than metric variables in defining NLSR terms, which contrasts to the assertion of ‘topology matters, metric refines’ in existing studies.