遥感综合信息在宁芜地区找矿预测中的应用

为了研究宁芜北段火山岩盆的矿产资源潜力及空间分布,本文以Landsat8中分辨率遥感数据及Pleiades1高分辨率遥感数据为数据源,综合运用目视解译法和多种遥感图像增强技术,结合区域成矿地质背景,对研究区进行了遥感影像解译,提取了与预测矿种密切相关的线、环、色、带、块遥感五要素。通过分析遥感五要素矿产地质特征与矿产点分布关系表明,研究区内的铁铜硫金矿床及星罗棋布的矿点大部分位于构造岩浆成矿亚带中,受区内北东向、东西向、北西向及其它断裂纵横交叉形成的断裂网格及火山机构控制,大多分布在数条断裂带交汇位置,另有一些分布在断裂带与环形构造的交汇处附近。基于主要的矿点受区内断裂网格及火山机构控制,遥感图像的综合地质信息特征与找矿目标紧密相联,说明了基于遥感图像的综合信息可以作为找矿预测的标志。     

基于 Flex 的市级国土资源综合监管平台设计与实现

采用Flex技术,基于NewMap Server进行WebGIS系统的开发,设计并实现呼伦贝尔市级国土资源"一张图"信息监管平台。系统克服数据来源多样、数据格式异构、数据基准不一致等问题,实现土地利用、矿产、地籍等多种数据的复合显示、查询、分析、输出、国土综合应用等功能,为国土管理部门提供管理、决策服务。     

城区内涝淹没模拟算法

针对城区内涝淹没范围和水深模拟问题,该文提出了一种基于约束Delaunay不规则三角网与三棱柱的城区内涝淹没模拟算法。该算法以沿地面三角形的顶点垂直向上引垂线形成的三棱柱为计算单元,通过"等体积"的方法,建立时间序列切片下的淹没水深和积水量的关系,据此实现淹没范围和水深模拟。以北京师范大学(简称"北师大")主校区为例,对单汇水区的水面高程上升模拟结果与实际观测值进行对比,基本吻合;并与传统栅格DEM的淹没效果进行了对比,表明该算法正确有效。     

底水油层水平井产液剖面均衡性评价

胜利油田开采底水特征高含水油层的水平井数量多,其中油层向水平井非均衡供液现象普遍。为评价此类水平井产液剖面均衡性,量化其生产动态改善潜力,定义了产液剖面基尼系数GN,并结合现场案例介绍其计算方法,随后统计胜利油田60口样本井,分析GN对见水时间tRL和底水突破前累积产油量QRL的影响,最后据此对GN分级。计算和分析结果表明:GN可以整体表征实际非均衡产液剖面偏离理想均衡产液剖面的程度,通常取值0~1之间,数值越大,均衡性越差;划分GN0.1为产液剖面不均衡,其样本井数54口,占比90%,以理想均衡产液状态为基准,tRL和QRL分别至少有100%和69.5%的提升潜力。     

Study on the Global Carbon Assimilation System Based on Multisource Remote Sensing Data

The Paris agreement signed in April, 2016 aims to balance global anthropogenic carbon emissions and terrestrial carbon sinks by the middle of the 21^st century. To fulfill this goal, it is necessary to calculate carbon fluxes of different regions reliably. The global carbon assimilation system is an effective technique for achieving this goal. The Ministry of Science and Technology of China supports the project entitled as study on the global carbon assimilation system based on multisource remote sensing data through the national key research and development programs for global change and adaptation during the thirteen-five period. This project will develop synergic inversion techniques for retrieving key parameters of biological and atmospheric cycles and for assimilating multisource remote sensing and ground based data. Then, the high resolution global carbon assimilation system coupled with an ecological model will be constructed. This system is able to assimilate jointly multisource observation data and to optimize key model parameters, photosynthesis and respiration carbon fluxes of global terrestrial ecosystems, and anthropogenic carbon emission fluxes of key regions. This system will be used to study quantitatively the spatial and temporal patterns of carbon fluxes of global terrestrial ecosystems and anthropogenic carbon emission fluxes of key regions and to identify the mechanisms driving the global terrestrial carbon sinks and sources. The outputs of this study will be helpful for the fulfillment of the key research and development programs for global change and adaptation and provide valuable data and technical support for the decision-making in China.     

Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China

A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows.     

基于灵敏度分析的海洋油气资源BP神经网络预测模型的优化

作者针对BP神经网络结构设计中存在的问题,提出利用灵敏度分析方法对BP神经网络预测模型进行优化。通过BP算法与参数灵敏度分析的结合,寻找网络输入属性与输出属性之间的影响因子;在保证精度的前提下优选网络输入属性,简化网络结构,以增强网络的泛化能力,减少人为主观因素对网络设计的影响。最后以海洋油气资源预测为例,结合实测资料建立BP神经网络预测模型并进行了优化及预测精度评价,表明优化后的模型既能有效提高油气资源预测结果的稳定性,又不损失预测精度。     

Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan,China

Quantifying land use patterns and functions is critical for modeling urban ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Methods of determining the optimum scale of land use patterns are commonly considered using landscape metrics. Landscape metrics are quantitative indicators for analyzing landscape heterogeneity at the landscape level. In this study, due to their widespread use in urban landscape analyses and well-documented effectiveness in quantifying landscape patterns, landscape metrics that represent dominance, shape, fragmentation and connectivity were selected. Five metrics include Patch Density, Contagion, Landscape Shape Index, Aggregation Index and Connectivity. Despite a wide application of landscape metrics for land use studies, the majority mainly focuses on the qualitative analysis of the characteristics of landscape metrics. The previous models are limited in exploring the optimum scale of land use patterns for their lack of quantitation. Therefore, taking the City of Wuhan as an example, the land use unit was treated as a patch, and the landscape pattern metrics at different spatial scales were calculated and compared so as to find the optimum one. Furthermore, a mathematical model of landscape metrics was proposed to quantify the scale effect of urban land use patterns, generating a complementary tool to select the optimum scale. In addition, Analytic Hierarchy Process (AHP) was introduced to determine the respective weights of the chosen landscape metrics in this model. Fractal dimension was ultimately applied to verify the chosen optimum scale of our study region. The results indicated that 60 m is confirmed to be the optimum scale for capturing the spatial variability of land use patterns in this study area.     

季节性低温胁迫下陇东黄土高原油污土壤环境因子对耐冷混合菌场地生态修复的响应

为了揭示季节性低温胁迫下陇东黄土高原油污土壤环境因子对耐冷混合菌场地生态修复的响应机制,利用自主筛选构建的耐冷石油降解混合菌在甘肃省庆阳市庆城县马岭镇长庆油田陇东油泥处理站开展了为期7个月的场地修复实验,采用常规方法测定了不同季节土壤理化特性、酶活性和微生物群落特性等环境指标。结果表明：（1）在季节性低温胁迫下（9-11月）M2组（耐冷混合菌处理组）月平均降解率明显增加（P<0.01）,JZJ+M1组（金盏菊联合常温混合菌处理组）和M2组累计TPH降解率分别为15.37%±3.51%和28.64%±4.12%。（2）M2组土壤脱氢酶和多酚氧化酶在低温季节（LT）活性最高,且温度和处理存在显著交互作用（P<0.01）。在土壤营养元素方面,无论何种处理方式（JZJ+M1和M2）二者含量均为RT（常温季节）高于LT（P<0.05）,同时明显高于CK组（P<0.05）。（3）M2组土壤微生物群落Shannon-Wiener指数和均匀度指数在LT高于RT（P<0.05）。（4）NMDS和Pearson相关性分析结果显示,M2组在低温季节具有较高TPH降解率主要与土壤多酚氧化酶、脱氢酶、单月TPH降解率（μ2）和Shannon-Wiener指数有关,且均呈极显著正相关关系。通过分析环境因子的季节响应,优化场地修复在低温环境的降解条件、加速低温期石油烃降解速率,以期为陇东地区低温耐冷混合菌场地生态修复技术的推广应用提供参考和基础数据资料。