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991.
The characteristics of Late Cenozoic tectonic uplift of the southern margin of the Qinghai- Tibet Plateau may be inferred from fluvio-lacustrine strata in the Zanda basin, Ngari, Tibet. Magnetostratigraphic study shows that the very thick fluvio-lacustrine strata in the basin are 5.89- 0.78 Ma old and that their deposition persisted for 5.11 Ma, i.e. starting at the end of the Miocene and ending at the end of the early Pleistocene, with the Quaternary glacial stage starting in the area no later than 1.58 Ma. Analysis of the sedimentary environment indicates that the Zanda basin on the southern Qinghai-Tibet Plateau began uplift at -5.89 Ma, later than the northern Qinghai-Tibet Plateau. Presence of gravel beds in the Guge and Qangze Formations reflects that strong uplift took place at -5.15 and -2.71 Ma, with the uplift peaking at -2.71 Ma.  相似文献   
992.
下庄矿田湖子地区铀矿找矿方向探讨   总被引:2,自引:0,他引:2       下载免费PDF全文
湖子地区位于NNE向诸广-新兴铀成矿带与近EW向大东山-漳州大断裂复合部位,是华南早、晚两期铀成矿热液活动叠加区、放射性高场区,既有"硅化带大脉"型铀矿产出,又有"交点"型铀矿存在,找矿前景良好.文章在论述下庄矿田铀成矿地质环境、铀成矿特征及铀矿定位条件基础上,分析了湖子地区铀成矿条件与找矿前景,指出该区今后铀矿找矿方向是:① 6009号硅化断裂带,在其北段找硅化带大脉型铀矿,在其南段找"交点"型铀矿;②新桥-下庄硅化断裂带和6009号带之间成矿部位,寻找硅化带型和"交点"型铀矿;③NW向、近EW向辉绿岩脉与NNE向、NE向构造交汇部位(交点),寻找"交点"型铀矿.  相似文献   
993.
The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha−1 lower than the RMSE (233.35 kg ha−1) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation.  相似文献   
994.
Recent developments in remote sensing technology, in particular improved spatial and temporal resolution, open new possibilities for estimating crop acreage over larger areas. Remotely sensed data allow in some cases the estimation of crop acreage statistics independently of sub-national survey statistics, which are sometimes biased and incomplete. This work focuses on the use of MODIS data acquired in 2001/2002 over the Rostov Oblast in Russia, by the Azov Sea. The region is characterised by large agricultural fields of around 75 ha on average. This paper presents a methodology to estimate crop acreage using the MODIS 16-day composite NDVI product. Particular emphasis is placed on a good quality crop mask and a good quality validation dataset. In order to have a second dataset which can be used for cross-checking the MODIS classification a Landsat ETM time series for four different dates in the season of 2002 was acquired and classified. We attempted to distinguish five different crop types and achieved satisfactory and good results for winter crops. Three hundred and sixty fields were identified to be suitable for the training and validation of the MODIS classification using a maximum likelihood classification. A novel method based on a pure pixel field sampling is introduced. This novel method is compared with the traditional hard classification of mixed pixels and was found to be superior.  相似文献   
995.
流变学:构造地质学和地球动力学的支柱学科   总被引:12,自引:6,他引:6  
地球是一动态系统,其各层圈的构造运动归根到底就是多矿物复合岩石在各种物理条件(例如,温度、围压、差应力、应变速率、应变方式等)下和化学环境(例如,氧逸度和水含量)中的形变。流变学作为研究岩石力学性质和变形行为的科学,现已成为地球动力学和构造地质学的支柱学科。本文对国际上近年来岩石流变学的最新进展做些扼要的介绍,呼吁中国固体地学界加强流变学的研究,做出经得起时间淘洗、实践检验的原创性成果来,使中国的构造地质学研究迈进国际先进的行列。  相似文献   
996.
祁阳山字型构造质疑   总被引:5,自引:1,他引:4  
结合区域构造演化背景及构造变形特征,对祁阳弧形构造的形成机制进行研究。分析表明,传统山字型构造机制难以解释祁阳弧形构造的诸多特征,且前人认为变形动力来源于东西向挤压应力场,也与印支期区域构造应力场实为NWW向的构造背景不符,因此祁阳弧形构造并不属典型山字型构造。基于研究区构造活动的客观实际,提出祁阳弧形构造的可能形成机制:NW向基底隐伏断裂和NNE-NE向主干断裂分别于印支期和燕山期产生强烈左旋走滑活动,从而使区域NNE向构造线在中段产生左旋偏转成为NNW向,从而形成S形的祁阳弧形构造。这一机制可较好解释祁阳弧形构造的若干特征,如关帝庙穹窿呈NWW走向、北反射弧构造形迹不显著、北弧弧顶脱位及内弧曲率大于外弧、南弧弧顶脱位、紫云-中田-高峰串珠状穹窿的形成等。上述认识对华南地区弧形构造研究具有一定启示意义:除山字型构造作用和砥柱作用外,还应注意断裂走滑等其他构造活动对弧形构造的制约,以及多次构造活动叠加对构造形迹可能造成的影响。  相似文献   
997.
神木北部矿区5-2煤层厚度及其底板高程趋势分析   总被引:1,自引:0,他引:1  
为了查清神木北部矿区5-2煤层赋存特征及成因,选取了该矿区172个典型钻孔数据,用趋势分析法研究了5-2煤层的厚度及其底板高程度变化特征。结果显示:该区煤层厚度总体为南北厚中部薄,东厚西薄;底板高程为南北高中部低,东高西低;煤层厚度和其底板高程间普遍存在正相关关系。在该区构造稳定的背景下,后期改造对煤层厚度及其底板的影响很小,煤层赋存特征主要受沉积与剥蚀的控制。  相似文献   
998.
煤体变形程度控制着煤与瓦斯突出和煤层气的可开发性,煤体结构空间展布预测是人们长期关注的焦点。以岩体力学和分形几何学基本理论为指导,以安阳矿区双全井田为例,通过计算岩体强度因子和分形维数,系统探讨了岩性结构对煤体变形的影响。研究表明,岩体强度因子和分形维数与断层和测井曲线判识的煤体结构之间存在密切关系:低强度因子和分形维数区,煤体易发生韧性变形,软煤发育;高强度因子和分形维数区,煤体(和岩体)以脆性变形为主,以断层发育为特征。这一结论为井田构造发育特征和软煤空间展布所证实。岩体力学和分形几何学的引入,为煤体结构空间展布区域预测提供了一种新途径。  相似文献   
999.
This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ 3). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ 3 time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ 3 data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ 3 predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ 3 time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ 3 reveal the best accuracy for LS + AR.  相似文献   
1000.
Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis.  相似文献   
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