随机森林算法在全球干旱评估中的应用

干旱是发生频率最高,造成社会、经济损失和生态破坏最严重、最广泛的自然灾害之一,因此对干旱进行可靠、有效的评估十分重要.本文以月平均降水、月平均温度、月最高温度、月最低温度、土壤湿度、蒸散发、NDVI、叶绿素荧光等作为解释变量,以基于SPI的干旱等级作为目标变量,采用随机森林算法,以2007-2012年的数据作为训练数据...     

中国西南典型地质背景区土壤重金属分布及生态风险特征

中国西南有22.3％的耕地重金属含量超标,区内广泛分布的峨眉山玄武岩和碳酸盐岩被认为是土壤中重金属的主要母质来源.目前,中国西南地区,尤其是峨眉山玄武岩分布区土壤重金属生态风险的研究程度仍有待提升,不同地质背景区(成土母岩)土壤中重金属含量、空间分布与生态风险缺乏对比.本文选择四川省典型地质背景区采集土壤样品,采用原子...     

基于气象站资料的中国地区太阳日辐射量算法研究

现行计算水平面太阳日辐射主要有两种方式:一种是利用影响辐射的相关要素建立模型,另一种是依据实测资料进行空间插值.但后一种方法若要保证精度则需有足够多的样本.针对上述问题,利用我国不同区域67个站点的数据,在VP-RAD模型的基础上,建立了一个适用于中国地区的逐日太阳辐射算法CNR,该算法仅需要输入站点基本信息、最高最低温度和降水量.模拟结果与实际观测结果比较吻合.     

Influence analysis of gaseous absorption on “HY-1A” CZI data processing Simulation and correction for Rayleigh scattering

Besides ozone, oxygen and water vapour should be considered for their absorptive effects on ＂HY--1A＂ CZI data processing. First ,gaseous transmittances under various conditions are computed and analyzed for the band settings of this sensor. Second, transmittances under six standard atmospheres are approximated as functions of zenith angle, the water vapour transmittance is approximated as a function of water vapour content and zenith angle, and the ozone transmittance is approximated as a function of ozone content and zenith angle. Finally, taking Rayleigh scattering as an example, the influence of ignoring gaseous absorption when calculating TOA reflectance is analyzed, and the effect of applying the presented transmittance approximations to gaseous absorption correction for Rayleigh scattering in ＂HY--1A＂ CZI data processing is evaluated.     

Geochemistry of pore waters from the Xisha Trough, northern South China Sea and their implications for gas hydrates

This paper reports all available geochemical data on sediments and pore waters from the Xisha Trough on the northern continental margin of the South China Sea. The methane concentrations in marine sediments display a downhole increasing trend and their carbon isotopic compositions (δ ¹³C = −25 to −51‰) indicate a thermogenic origin. Pore water Cl⁻ concentrations show a range from 537 to 730 mM, and the high Cl⁻ samples also have higher concentrations of Br⁻, Na⁺, K⁺, and Mg²⁺, implying mixing between normal seawater and brine in the basin. The SO₄ ²⁻ concentrations of pore waters vary from 19.9 to 36.8 mM, and show a downhole decreasing trend. Calculated SMI (sulfate-methane interfaces) depths and sulfate gradients are between 21 and 47 mbsf, and between −0.7 and −1.7 mM/m, respectively, which are similar to values in gas hydrate locations worldwide and suggest a high methane flux in the basin. Overall, the geochemical data, together with geological and geophysical evidence, such as the high sedimentation rates, high organic carbon contents, thick sediment piles, salt and mud diapirs, active faulting, abundant thermogenic gases, and occurrence of huge bottom simulating reflector (BSR), are suggestive of a favorable condition for occurrence of gas hydrates in this region.     

准噶尔盆地中部Ⅲ区块原油甾烷异常分布特征与成因

对准噶尔盆地中部Ⅲ区块的3类原油或油砂样品抽提物饱和烃进行了气相色谱-质谱分析,研究了原油饱和烃中甾烷类化合物的分布特征,并对其成因做了初步探讨。结果表明：3类原油的甾烷分布特征具有一定的相似性,C27规则甾烷相对丰度明显低于C28、C29;C27、C28、C29异构体αββ型相对丰度明显高于ααα型（C28αββ（20S）或C29αββ（20R）丰度最高）;但这3类原油的成因是不一致的,其影响因素主要包括热演化、生物降解、运移分馏以及古环境或岩性4个方面,其中第1、3类原油主要以热演化作用与运移作用为主,第1类原油还可能受到古环境或岩性影响,两者均不受生物降解的影响,第2类原油则受到热演化、运移作用及生物降解的共同影响。     

海底孔内水合物观测系统与钻井实施

通过耦合布设海底表面和孔内水合物观测系统获取物理、化学、微生物等数据是了解掌握海洋水合物环境动态变化、碳循环规律和资源开发技术的有效手段,据此初步提出了一套海底孔内水合物观测系统,并指出了系统的关键技术难点。而在钻井布设该孔内观测系统时,要注意防止井内安全事故的发生,充分评估安放位置处含水合物地层的地质力学稳定性并采取适当的钻井和完井方式稳定或强化含水合物地层以支撑孔内观察仪器,实现孔内长期监测。最后讨论了在我国南海实施孔内水合物观测系统的必要性,并提出了初步想法。     

基于ArcSDE的人防数据入库的应用研究

空间数据引擎是实现空间数据库的核心。简要介绍了ESRI公司的空间数据库引擎（spatial database engine）,它能将空间数据和属性数据集成在数据库中。进一步分析了空间数据的存储模式,并以人防工程为例构建了人防的Geodatabase数据模型,最后对实现人防工程数据的入库方法进行了探讨。     

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.     

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.