“一带一路”建设背景下重庆与东盟国家贸易格局演变和影响因素分析

“贸易畅通”是“一带一路”建设的重要内容,重庆作为中国西部地区内陆开放高地,贸易发展优势明显。运用贸易强度指数和HM指数,分析2001—2017年重庆与东盟国家贸易格局和贸易依赖程度,并分析影响重庆与东盟国家贸易格局的影响因素。结果表明：①重庆与东盟国家贸易联系紧密,增长速度快,贸易总额在“一带一路”沿线六大区域中始终保持领先地位;②马来西亚和泰国成为重庆与东盟国家中最重要的贸易伙伴,越南、新加坡、菲律宾和印度尼西亚紧随其后,而与缅甸、柬埔寨、老挝和文莱的贸易总额较少;③在进口方面,形成以马来西亚、泰国和越南为首的多元进口格局,泰国和越南进口伙伴地位上升。在出口方面,形成以马来西亚为首的多元出口新格局,越南出口地位下降;④在市场相互依赖程度方面,重庆出口对东盟国家特别是马来西亚和新加坡贸易市场的重要性程度上升,而对东盟国家市场依赖程度较小;⑤产业结构、贸易通道、文化交流和政策等是影响重庆与东盟国家贸易格局的重要影响因素。     

“一带一路”沿线国家石油资源流动类型演变

综合运用石油自给率、流动比率等方法,以“一带一路”沿线国家为研究对象,对1995—2014年各国石油资源流动类型时空演变进行研究。结果表明：1）1995—2014年石油净补给型国家数量较为稳定,无产型或低产型国家的石油贸易倾向变化相对较小;基本自给型国家数量占比最大,1995年占比1/2,其余四个年份占比稳定在1/3;净支出型国家数量显著增加,至2014年其中有5个国家保持不变,表明这些国家的石油产量具有较大的优势。2）1995年和2014年汇地国家均为39个国家,其中有34个国家一直保持汇地职能,空间分布上呈东多西少,南多北少,东西分化以西亚、中亚、东欧为界;有14个国家一直保持源地职能,其空间分布格局与汇地相应,西多东少,南多北少,主要分布于西亚、东欧及中亚;交流地数量较少,呈分散分布,且分布地不稳定。3）从数量变化来看,研究期内汇地略有增加,源地略有减少,交流地略有增加;“一带一路”源地总出口量与汇地总进口量的比呈逐年降低趋势。     

Gatekeepers,Shareholders, and Evangelists: Expanding Communication Networks of African American Forest Landowners in North Carolina

The Sustainable Forestry and African American Land Retention Program (SFLR) was launched in 2012 to increase adoption of sustainable forestry practices among African American landowners in the southeastern United States to prevent land loss, increase forest health, and build economic assets. One of its main goals was to build communication networks through which African American landowners could obtain and share information about forestry practices and landowner assistance programs independent of public agencies. To measure and examine the growth of these communication networks over a three-year period (2014-2017), we conducted 87 interviews with landowners (24 of whom were interviewed multiple times), SFLR personnel, and Federal and State staff members in North Carolina. We used complementary methods of data gathering and analysis, including social network analysis and qualitative analysis. Our results showed expanding communication networks will be sustained independently of the program over time, although there is still a heavy reliance on program personnel.     

西北贫困地区乡村类型识别与振兴途径研究

乡村振兴战略是新时期我国推进城乡融合发展的重要举措。贫困地区既是脱贫攻坚的主战场,又是乡村振兴的重点区域。如何科学识别村落类型,分类推进典型区域乡村振兴发展,对于破解农村发展不平衡不充分问题具有重要的现实意义。本文解析了乡村地域系统发展理论,阐释了城乡融合发展理论,剖析了村域空间结构格局演变和城乡要素结构功能优化重组;构建了西北干旱贫困地区乡村振兴村落类型识别体系,从乡村主体、产业发展、人居环境、资源禀赋4个子系统进行逐级分类判断,识别乡村主导类型,结合专家征询分析与村落特征,将乡村振兴村落类型识别为集聚提升类、三产融合类、城郊融合类、特色保护类、搬迁撤并类,结合不同乡村振兴模式提出了相应地发展路径,以期为乡村振兴提供理论依据与决策参考。     

中国与“一带一路”沿线国家贸易及其影响因素

利用拓展贸易引力模型,借助Eviews等工具分析了影响中国与“一带一路”沿线国家贸易规模的因素,以及中国对外直接投资的滞后性对双边贸易的影响。结果表明：1）中国与“一带一路”沿线国家贸易规模受到经济发展水平、市场规模、政治制度、贸易畅通性、便利性、中国对外直接投资、民间文化交流紧密度的影响;2）中国对外直接投资对于带动中国与“一带一路”沿线国家间的贸易规模具有正向作用,但其效应具有一定滞后性;3）中国对外直接投资对于带动中国与不同“一带一路”沿线国家贸易规模的引力大小不同,可分为投资带动力巨大型、投资带动型、投资一般型、投资带动力不足型4种类型,中国与东南亚、西亚和撒哈拉以南的非洲国家贸易规模受中国对外直接投资带动作用较强。     

"资源一号"02C卫星影像土地利用变化检测能力分析

“资源一号”02C卫星自成功发射以来,被广泛应用于土地资源、矿产资源、地质环境调查,以及国土资源、地质灾害应急监测等应用领域。“资源一号”02C卫星是一颗填补我国高分辨率遥感数据空白的卫星,是根据国土资源主体业务需求定制的第一颗国产高分辨率业务卫星。本文以吉林省和浙江省某试验区“资源一号”02C卫星数据为例,对“资源一号”02C卫星数据融合影像进行了土地利用遥感监测变化信息检测能力的方法试验。根据试验区数据变化信息提取试验结果,对“资源一号”02C卫星影像在土地利用动态遥感监测中的变化检测能力和适用性开展了试验、分析和评价工作。     

Analysis of Water Resources Carrying Capacity of the “Belt and Road” Initiative Countries based on Virtual Water Theory

Most countries along the route of the “Belt and Road” initiative are faced with a shortage of water resources. However, successful implementation of the initiative depends on water availability to support economic and social development. We designed a water resources carrying capacity evaluation index system, assigned grades and weights to each evaluation index and calculated a water resources carrying index for the 65 countries along the route. We used virtual water theory to analyze China’s net virtual water import from key bulk agricultural products through international trade. For more than half of the countries along the route, their water resources will be unable to support the economic development that will be necessary for fulfilling the goals of the Initiative. As a country with insufficient water resources carrying capacity, China is a net virtual water importer in the virtual water trade. This virtual water trade can improve China’s water resources support capacity, and ensure China’s water and food security for the future.     

荒漠生态质量科学框架:概念、指标、监测及评估（英文）

荒漠生态系统是地球上最大的陆地生态系统,全球四分之一的人口生活在这一区域。清晰地定义荒漠生态系统生态质量,制定反映生态质量优劣的关键监测指标,集成"星–空–地"一体化监测技术、构建综合评价模型可为干旱区生态质量监测、促进区域可持续发展提供技术支撑。荒漠生态质量是指一定时空范围内荒漠生态系统要素、结构和功能的综合特征。该研究通过集成卫星、无人机和地面传感器网络的"星–空–地"一体化监测技术,在区域和站点两个尺度上对荒漠生态系统的生态要素、生物多样性和生态功能进行连续监测,通过标准化生态质量指标数值、厘定其阈值范围,构造判断矩阵建立生态质量综合评价模型,评价荒漠生态系统质量状况。本论文阐明了构建荒漠生态质量动态综合监测技术规范与评价方法的概念框架,为实现我国荒漠生态系统生态质量综合监测、科学诊断和定量评估提供理论基础。     

高分辨率遥感影像配准与变化检测一体化处理

为了克服高分辨率遥感影像配准与变化检测作为单独环节处理的局限,该文提出了一种基于变分理论的配准与变化检测一体化处理方法。该方法将配准误差作为一种光谱变化决策因子,变化信息以权值的方式迭代反馈给变分配准模型的解算过程。为了更准确地检测建筑物这个特定目标的真实变化,该文采用多尺度最大形态学轮廓建筑物检测指数的差异作为另外一个决策因子。最后将配准误差反映的变化和建筑物检测指数的差异这两个决策因子在D-S证据理论框架下建立概率模型进行融合处理,进而得到建筑物的变化检测结果。该文选取WorldView-2数据进行实验,实验结果表明,一体化处理思路可以有效地解决单独处理的局限,从根本上解决配准误差对变化检测结果的影响以及由于变化而使配准精度降低的问题,进而提高配准和变化检测的质量。     

Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.