GIS-based landslide susceptibility mapping using hybrid integration approaches of fractal dimension with index of entropy and support vector machine

The loess area in the northern part of Baoji City, Shaanxi Province, China is a region with frequently landslide occurrences. The main aim of this study is to quantitatively predict the extent of landslides using the index of entropy model(IOE), the support vector machine model(SVM) and two hybrid models namely the F-IOE model and the F-SVM model constructed by fractal dimension. First, a total of 179 landslides were identified and landslide inventory map was produced, with 70%(125) of the landslides which was optimized by 10-fold crossvalidation being used for training purpose and the remaining 30%(54) of landslides being used for validation purpose. Subsequently, slope angle, slope aspect, altitude, rainfall, plan curvature, distance to rivers, land use, distance to roads, distance to faults, normalized difference vegetation index(NDVI), lithology, and profile curvature were considered as landslide conditioning factors and all factor layers were resampled to a uniform resolution. Then the information gain ratio of each conditioning factors was evaluated. Next, the fractal dimension for each conditioning factors was calculated and the training dataset was used to build four landslide susceptibility models. In the end, the receiver operating characteristic(ROC) curves and three statistical indexes involving positive predictive rate(PPR), negative predictive rate(NPR) and accuracy(ACC) were applied to validate and compare the performance of these four models. The results showed that the F-SVM model had the highest PPR, NPR, ACC and AUC values for training and validation datasets, respectively, followed by the F-IOE model.Finally, it is concluded that the F-SVM model performed best in all models, the hybrid model built by fractal dimension has advantages than original model, and can provide reference for local landslide prevention and decision making.     

生产性服务业视角下城市网络的演化模式与机制研究——以长江三角洲为例

从行业属性、企业内部因素和城市所处的环境3个层面的耦合关系视角,对生产性服务业视角下城市网络的形成演化模式和演化机制进行了理论探索。在基于地理空间的行政等级体系基础上,考虑到生产性服务业发展对于城市网络的综合影响,归纳了由初始集聚阶段-非均衡扩散阶段-等级网络形成阶段-网络成熟阶段的生产性服务业视角下城市网络的一般演化模式。实证研究表明,长三角城市网络正处于非均衡扩散向等级网络阶段演化的过渡时期,表现出网络的层级特征愈发明显、水平联系不断增强、联系方向更加多样化、服务功能联系差距缩小等特征。联系便捷程度、创新要素支撑、制造业发展基础,以及城市能级推动等要素对于长三角城市网络的影响较大。     

Isolation of protein from Chlorella sorokiniana CY1 using liquid biphasic flotation assisted with sonication through sugaring-out effect

Microalgae, a sustainable source of multi beneficial components has been discovered and could be utilised in pharmaceutical, bioenergy and food applications. This study aims to investigate the sugaring-out effect on the recovery of protein from wet green microalga, Chlorella sorokiniana CY1 which was assisted with sonication. A comparison of monosaccharides and disaccharides as one of the phaseforming constituents shows that the monosaccharides, glucose was the most suitable sugar in forming the phases with acetonitrile to enhance the production of protein(52% of protein). The protein productivity of microalgae was found to be significantly influenced by the volume ratio of both phases, as the yield of protein increased to 77%. The interval time between the sonication as well as the sonication modes were influencing the protein productivity as well. The optimum protein productivity was obtained with 10 s of resting time in between sonication. Pulse mode of sonication was suitable to break down the cell wall of microalgae compared to continuous mode as a lower protein yield was obtained with the application of continuous mode. The optimum condition for protein extraction were found as followed: 200 g/L glucose as bottom phase with volume ratio of I:1.25, 10 s of resting time for ultrasonication, 5 s of ultrasonication in pulse mode and 0.25 g of biomass weight. The high yield of protein about 81% could be obtained from microalgae which demonstrates the potential of this source and expected to play an important role in the future.     

Responding to Global Warming: Mitigation Policies and Actions of Stakeholders in China’s Tourism Industry

China’s tourism industry has witnessed rapid progress in recent years, and is now an important part of global tourism in dealing with climate change. Within a framework of Pressure-State-Response (PSR), this paper focuses on the emission reduction pressure, carbon emission status, and responses of stakeholders in China’s tourism industry. Findings include: 1) The central government’s strategy and rapid growth of the industry scale exert rising pressure on China’s tourism to reduce carbon emissions. 2) Carbon emissions of China's tourism account for 13%-14.6% of global tourism, and about 3% of China’s emissions overall. Chinese tourists’ per capita carbon emission is lower than half of the global level. 3) The Chinese government attaches great importance to energy-saving and carbon emission reduction. In the tourism industry, documents, standards and other regulative measures have been issued to ensure that business practitioners set up green operational and managerial systems. In the field of tourism transportation, China's high-speed rail, new energy vehicles, and urban shared bicycles, have developed very rapidly in recent years, and they have effectively reduced the carbon emissions in traveling. Furthermore, this paper finds that Chinese tourists already have awareness and willingness for low-carbon tourism.     

基于转录组测序对两种氮素营养条件下多形微眼藻氮代谢途径的解析

探究微藻的氮代谢通路对了解其对不同氮源利用的分子机制具有重要意义。本研究利用Illumina高通量测序技术对两种氮素营养条件下(硝酸氮和尿素)多形微眼藻的转录组进行分析,通过基因功能注释及数字基因表达谱分析,研究了多形微眼藻细胞内氮代谢的调控机制。结果检测出15种参与氮代谢的酶,对应76个编码基因,构建了多形微眼藻的氮代谢通路图。其中10个酶编码基因在两种不同氮素营养条件下存在差异表达,最显著的是谷氨酸合成酶、谷氨酸脱氢酶和谷氨酰胺合成酶相关基因。有机氮源(尿素)实验组中,多形微眼藻细胞内的硝酸盐还原酶、亚硝酸盐还原酶等基因的差异表达明显高于无机氮源(硝酸钠)实验组,表明当环境中的氮源为尿素时,会对多形微眼藻细胞内硝酸盐的转化和利用有一定影响。本研究初步阐述了硝酸盐、尿素的吸收转运对多形微眼藻细胞内氮代谢的影响机制,可为硅藻在不同氮素营养条件下的吸收利用机制及氮代谢响应研究提供依据。     

南海海洋地磁固定观测站建设初步研究

为填补我国海洋地磁固定观测的空白,支撑科学研究、防灾减灾、海洋资源开发,维护国家的海洋权益和履行我国在南海海域负有的国际责任,急需在南海建设岛礁和海底地磁固定观测站。通过初步分析国外海洋地磁观测站案例、南海岛礁基础设施现状以及海底观测网计划实施情况,认为南海海洋地磁固定观测站建设的条件已经成熟。文中给出了合理空间布局、分步实施、因地制宜及智能化观测的建议。     

中国东海陆架海域柱状沉积物对磷的吸附行为

通过研究磷在海洋柱状沉积物上的吸附动力学曲线和吸附等温线,并结合沉积物表面电荷性质以及磷形态分析,考察了我国东部陆架海域沉积物对磷的吸附特征。结果表明,所研究海域沉积物对磷的吸附过程明显分为快慢两段,48h后吸附可达到平衡;吸附后的磷主要为可交换态磷,吸附过程以物理作用为主;吸附等温线可用Langmuir交叉型模式描述,在磷初始浓度较低时,沉积物对磷存在解吸现象;沉积物对磷吸附参数的垂直分布较为复杂,受自身性质影响较大;盐度增大,沉积物对磷的吸附能力呈下降趋势。     

一种海洋混合层深度的智能识别方法研究

文章提出了一种识别混合层深度的人工智能方法。该方法在温度(密度)与压强(或深度)间建立线性模型, 并且将其系数和方差做成一组表征廓线特征的统计量。初始时为模型设定一个主观的先验分布, 在一个自海表向下移动的窗口内通过贝叶斯链式法则和最小描述长度原理学习新数据, 得到系数均值的最大后验概率估计。用F-检验识别系数发生突变的位置, 以此确定混合层的存在性及其深度。通过2017年2月太平洋海域的地转海洋学实时观测阵(Array for Real-time Geostrophic Oceanography, ARGO)数据进行测试, 并且以质量因子(Quality Index, QI)值作为判断识别混合层深度结果准确性的依据, 发现该方法相比于梯度法、阈值法、混合法、相对变化法、最大角度法和最优线性插值法在识别结果上具备更大的QI值。表明该方法能够准确识别混合层深度。     

Succession of the Nanoplankton Community during a Brown Tide in a Scallop Culture Area in China

Ocean Science Journal - Brown tides caused by Aureococcus anophagefferens have occurred frequently in the coastal waters of Qinhuangdao since 2009. The Changli coast is the area most strongly...     

"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。