基于高光谱Hyperion数据的线性光谱混合模型与神经网络模型的比较

混合像元问题是定量遥感中的热点问题之一,为了改进从遥感数据中提取定量信息,人们建立了各种混合光谱分解技术,其中线性光谱混合模型和神经网络模型就是两种比较成熟的方法。以陕西省横山地区的高光谱Hyperion数据为研究基础,通过最小噪声变换(MNF)、像元纯度指数(PPI)转换和RMS误差分析的迭代方法相结合提取影像中的纯净像元作为终端端元。分别运用神经网络模型和线性光谱混合模型对影像进行光谱分解,得到各个组分的分解图像。以标准植被指数(NDVI)影像为衡量标准,选取训练样本点,分别对两种模型进行回归分析,结果显示NDVI影像与线性光谱混合模型植被分解图像的判定系数(R2=0.91)要大于其与神经网络模型的判定系数(R2=0.81)。进一步分析表明在一般情况下,线性光谱混合模型具有比神经网络模型略高的分离精度,但是神经网络模型对细部信息的提取的效果要好于线性光谱混合模型,最后提出了端元均方根误差(EAR)指数,一种新的混合像元分解的思路。     

点质模型求定月球重力场及其特征分析

利用Lunar-Prospector扩展任务的视线加速度数据,根据点质模型恢复了月球近区的重力场,将其与LP165月球重力场模型进行了比较和分析,并利用恢复的重力场联合月球地形数据对Mas-con进行分析,总结了月球重力场的主要特征及其研究方向发展趋势,将重力场恢复技术与我国的探月计划-"嫦娥"工程结合起来,为建立高精度的月球重力场和地形模型提供了一种有效而实用的方法。     

基于遥感影像理解模型的土地利用时空变化监测——以龙口市为例

本文从遥感影像理解模型出发,探讨了遥感信息的知识发现及特征提取问题,特别针对士地利用研究领域,提出了纳入GIS信息的遥感影像综合理解模型,将GIS数据(主要包括高程和坡度)与遥感影像结合起来,从中发现知识,并将知识用于遥感影像的专题信息提取,建立了地学规律知识库,从而提高了遥感影像的分类精度。本文基于遥感影像理解模型,发现土地利用变化区域,提取变化信息,动态地监测了龙口市土地利用的时空变化情况。     

华北安鹤煤田煤储层特征与煤层气有利区分布

通过对安鹤煤田采集煤样的煤质、显微组分、煤相、显微裂隙分析,等温吸附、低温氮比表面及孔隙结构和压汞孔隙结构测试,研究了该区煤层气赋存的地质条件、煤层气生气地质特征和煤储层物性特征。并采用基于G IS的多层次模糊数学评价方法计算了该区的煤层气资源量,预测了煤层气有利区分布。研究结果表明,该区煤层气总资源量为1 115.73×108m3,煤层气资源丰度平均为1.18×108m3/km2,具有很好的煤层气资源开发潜力。在煤田中部的四矿到八矿之间的地区以及北部的水冶镇附近地区,煤层累计有效厚度大、煤层气资源丰度高、煤层埋深适中、煤储层孔裂隙系统发育、渗透性高,是该区煤层气勘探开发的最有利目标区。     

井中激电地-井方式井旁球体正反演

以激发极化法中的地-井方式中的体极化球形体作为研究对象,采用解析法对地下半空间的电位场进行求解,利用提取出的井中二次场异常电位差进行反演,得出极化球体的球心离井的距离和球心的埋深。通过计算机进行正反演模拟,验证了进行正反演计算的解析式的正确性,并从物理意义上对正反演过程中出现的现象进行分析。最后给出该方法的适用条件以及注意事项。研究对激发极化法地下勘探目标的定量分析具有明确意义。     

The characteristics and sources of natural gases from Ordovician weathered crust reservoirs in the Central Gas Field in the Ordos Basin

The Central Gas Field is a famous large-sized gas field in the Ordos Basin of China. However, identification of main gas sources of the Ordovician reservoirs in this gas field remains puzzling. On the basis of a lot of geochemical data and geological research on natural gases, the characteristics and sources of natural gases from Ordovician weathered crust reservoirs in the Central Gas Field in the Ordos Basin were studied. The results indicated that natural gases from Ordovician weathered crust reservoirs in the Central Gas Field in the Ordos Basin have similar chemical and isotopic compositions to highly mature and over-mature dry gases. Both coal-derived gases and oil-type gases coexist in the Central Gas Field in the Ordos Basin. The former was derived mainly from Carboniferous-Permian coal measures and the latter from Lower Paleozoic marine carbonates. It is suggested that coal-derived gases occur in the eastern part of the Central Gas Field while oil-type gases may be produced mainly in the northern, western and southern parts of the Central Gas Field in the Ordos Basin.     

δ13c-δ18O Covariance:An Effective Indicator of Hydrological Closure for Lakes?

The correlation between the Δ13c and 18O in primary carbonates is affected by several factors such as hydrological balance, total CO2 concentrations, climatic condition and lake productivity.The influence of these factors on the Δ13c-δ18 correlation may be different on different time scales. In this paper, two different-type lakes in southwestern China, Lake Erhal and Lake Chenghai, are selected to investigate the influence of climatic pattern on the Δ13c-Δ18o correlation and to evaluate the reliability of the Δ13c-Δ18o covariance as an indicator of hydrological closure. The results show that there exists good correlation between the Δ13c and Δ18o in Lake Erhai (overflowing open lake) and inLake Chenghal (closed lake). This suggests that the Δ13c-Δ18o covariance may be not an effective indicator of hydrological closure for lakes, especially on short time scales. On the one hand, a hydrologically open lake may display covariant Δ13c and δ18 as a result of climatic influence. The particular alternate warm-dry and cold-wet climatic pattern in southwestern China may be the principal cause of the Δ13c-δ18 covariance in Lake Erhai and Lake Chenghal. On the other hand, a hydrologically closed lake unnecessarily displays covariant trends between Δ13c and δ18 because of the buffering effect of high CO2 concentration on the Δ13c shift in hyper-alkaline lakes. We should be the buffering feeect of high CO2 concentration on the 13Cshift in hyper-alkaline lakes.We should be prudent when we use the covariance between 13C and 18O to judge the hydrological closure of lake.     

Simulation experiment on hydrocarbon generating potential of various source rocks on the northern margin of the Qaidam Basin,Qinghai, China

The northern margin of the Qaidam Basin is one of the main oil-gas exploration areas in western China, where source rocks are composed mostly of Middle and Lower Jurassic dark mud shale, carbargillite and coal. A large number of subsurface and outcrop samples differing in lithology with different types of organic matter were selected for resource evaluation, research and calculation. And among them, 13 samples were used for simulation experiment on hydrocarbon generating potential of various source rocks. At first, two kinds of heating modes were compared through simulation experiment, including single temperature-step heating and continual heating. Perhaps, the process of hydrocarbon generation and expulsion occurred naturally between a close system and an open system. In addition, the first heating mode was convenient, and all its reaction products were involved in the whole thermal evolution, and the final simulation experimental results were basically in consistency with the natural evolution trend Therefore, the first heating mode was adopted and the hydrocarbon yield of every sample was worked out. According to the type and lithology of organic matter and the hydrocarbon yield of samples for simulation experiment, hydrocarbon generation and expulsion mode with three kinds of lithology and five types of source rock has been established to provide the basis for hydrocarbon generation evaluation, research and resource calculation.     

基于神经网络方法的芦苇叶面积指数遥感反演

提出了一种从TM图像上获取芦苇冠层叶面积指数的方法:首先对芦苇的生长背景进行分类;然后,对不同的背景光谱利用冠层反射率(FCR)模型计算得到查找表;最后,利用实测数据和查找表中的数据作为参数进行BP神经网络模型训练,从而得到芦苇冠层LAI。结果表明,人工神经网络方法有很强的非线性拟合能力,能够消除背景对反演结果的影响,有效提高LAI反演的精度。     

基于GIS的北京市生态环境质量监测与分析

以2006年TM、SPOT 4及QuickBird遥感影像为信息源,在地理信息系统与遥感技术的支持下,结合野外调查及其它辅助数据,运用生态环境状况评价技术规范,对北京市2006年的生态环境质量进行评价,并对2000年与2006年北京市生态环境变化进行动态分析.结果表明: 2006年北京市生态环境质量评价指数为59.707,处于良好等级;2000～2006年间,北京全市生态环境状况稳定保持在"良"的状态,总体变化不大,但北京市耕地面积减少了339.09 km2,城镇建设用地增加了285.24 km2,水域面积减少了118.98 km2,其主要原因是降水量的减少、城市化扩张以及人为因素影响.