颅脑外伤分类的CT特征   总被引：2，自引：2，他引：0  

马蜂  李恒国 《CT理论与应用研究》1998,7(3):22-25

本文目的在于进一步提高对多种颅脑损伤的认识水平。所用材料和方法为本组１３５例,男９８例,女３７例,年龄４＿７７岁,平均年龄２４．８３岁。车祸伤９３例,跌伤２８例,击伤１４伤,１０１例有昏迷史,全部病例均作头颅ＣＴ轴位平扫。从相互伴发的多种颅脑损伤的角度,详细分析了它们的ＣＴ表现。结果得到了１３５例中,有多种类型颅脑损伤１３３例,单纯脑挫裂伤２例;硬膜外血肿１０４例,合并同一部位骨折７５例,占７２．１５％,合并脑挫裂伤占７０．３７％;硬膜下血肿２０例,位于外力对冲部位１５例．占７５％,合并脑挫伤裂伤１２例,其中１１例邻近硬膜下血肿;外伤后２小时内ＣＴ检查,并于外伤后４小时至５天内ＣＴ复查４７例,发现病变进展３８例,占８０．９５％。结论为硬膜外血肿多伴同部位骨折;在硬膜外血肿中,伴发的脑挫裂伤多位于对冲部位;硬膜下血肿多发生于对冲部位;颅脑损伤后,短期内病变可能会继续发展。  相似文献   

云南山区公路水毁类型及发育机制   总被引：2，自引：0，他引：2  

方向池  黄润秋 《地质灾害与环境保护》1998,9(3):56-61

公路水毁是在气候,水文,地质环境和人类活动的综合作用下,公路沿线产生的一系列对公路工程的破坏和工程披破坏的过程,通过在云南山区公路水毁的调查研究,其主要类型有沿公路发生的崩塌,滑坡,泥石流,水毁桥涵,水毁路基,水毁路面,路基沉陷和路面翻浆等８类,重点探讨其中崩塌,滑坡,泥石流,路基沉陷和路面翻浆５类的发育机制。  相似文献   

一种以能量平衡为基础的干旱指数   总被引：5，自引：0，他引：5  

唐登银 《地理研究》1987,6(2):21-31

本文以能量平衡公式为基础,根据实际蒸发与潜在蒸发的关系依赖于土壤水分含量的事实,导出一种表达干湿状况的指标——土壤水分干旱指数。  相似文献   

Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis   总被引：1，自引：0，他引：1  

Lihong Su   《ISPRS Journal of Photogrammetry and Remote Sensing》2009,64(4):407-413

In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach.  相似文献   

基于要素规则分类的城镇地籍数据建库方法研究     

白兰东  王绘 《四川测绘》2009,32(1):11-14

城镇地籍数据的有效分类与正确组织是地籍数据库规范建立和正常运行的前提条件。本文提出了基于地籍要素规则的分类方法，按照地籍数据的表达类型，描述了宗地背景图形数据、宗地图形数据、测量控制点数据、属性数据和档案数据的各个要素定义和编码规则。以成都市地籍数据库的建设为实例，根据各种来源的地籍数据分别开展了不同类型地籍数据的快速分类与入库工作。  相似文献   

基于时序MODIS NDVI的黑河流域土地覆盖分类研究   总被引：7，自引：1，他引：6  

顾娟  李新  黄春林 《地球科学进展》2010,25(3):317-326

归一化植被指数(NDVI)是植被生长状态及植被覆盖度的最佳指示因子,其时序数据也已成为基于生物气候特征开展大区域植被和土地覆盖分类的基本手段。基于时序NDVI数据的土地覆盖分类,即通过提取NDVI时间信号所包含的植被生物学参数,构建起一个包含植被生物学信息的分类特征空间。利用2006年重建得到的MODIS NDVI 16天合成时间序列数据,并结合1 km分辨率的DEM数据、野外实地调查资料等辅助数据,综合分析了不同土地覆盖类型对应的时序NDVI谱线及其第一、二谐波的特征阈值,建立决策树对黑河流域的土地覆盖开展分类研究。结果表明,基于时序MODIS NDVI谱线特征的决策树分类精度为78%,Kappa系数为0.74。利用1 km时序MODIS NDVI时间序列获得较为准确的黑河流域土地覆盖类型是可行的。  相似文献   

Topographic and spectral data resolve land cover misclassification to distinguish and monitor wetlands in western Uganda     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Wetlands provide vital wildlife habitat and ecosystem services, but changes in human land use has made them one of the world’s most threatened ecosystems. Although wetlands are generally protected by law, growing human populations increasingly drain and clear them to provide agricultural land, especially in tropical Africa. Managing and conserving wetlands requires accurately monitoring their spatial and temporal extent, often using remote sensing, but distinguishing wetlands from other land covers can be difficult. Here, we report on a method to separate wetlands dominated by papyrus (Cyperus papyrus L.) from spectrally similar grasslands dominated by elephant grass (Pennisetum purpureum Schumach.). We tested whether topographic, spectral, and temperature data improved land cover classification within and around Kibale National Park, a priority conservation area in densely populated western Uganda. Slope and reflectance in the mid-IR range best separated the combined papyrus/elephant grass pixels (average accuracy: 86%). Using a time series of satellite images, we quantified changes in six land covers across the landscape from 1984 to 2008 (papyrus, elephant grass, forest, mixed agriculture/bare soil/short grass, mixed tea/shrub, and water). We found stark differences in how land cover changed inside versus outside the park, with particularly sharp changes next to the park boundary. Inside the park, changes in land cover varied with location and management history: elephant grass areas decreased by 52% through forest regeneration but there was no net difference in papyrus areas. Outside the park, elephant grass and papyrus areas decreased by 61% and 39%, mostly converted to agriculture. Our method and findings are particularly relevant in light of social, biotic, and abiotic changes in western Uganda, as interactions between climate change, infectious disease, and changing human population demographics and distribution are predicted to intensify existing agricultural pressure on natural areas.  相似文献   

A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

In recent years, it has been widely agreed that spatial features derived from textural, structural, and object-based methods are important information sources to complement spectral properties for accurate urban classification of high-resolution imagery. However, the spatial features always refer to a series of parameters, such as scales, directions, and statistical measures, leading to high-dimensional feature space. The high-dimensional space is almost impractical to deal with considering the huge storage and computational cost while processing high-resolution images. To this aim, we propose a novel multi-index learning (MIL) method, where a set of low-dimensional information indices is used to represent the complex geospatial scenes in high-resolution images. Specifically, two categories of indices are proposed in the study: (1) Primitive indices (PI): High-resolution urban scenes are represented using a group of primitives (e.g., building/shadow/vegetation) that are calculated automatically and rapidly; (2) Variation indices (VI): A couple of spectral and spatial variation indices are proposed based on the 3D wavelet transformation in order to describe the local variation in the joint spectral-spatial domains. In this way, urban landscapes can be decomposed into a set of low-dimensional and semantic indices replacing the high-dimensional but low-level features (e.g., textures). The information indices are then learned via the multi-kernel support vector machines. The proposed MIL method is evaluated using various high-resolution images including GeoEye-1, QuickBird, WorldView-2, and ZY-3, as well as an elaborate comparison to the state-of-the-art image classification algorithms such as object-based analysis, and spectral-spatial approaches based on textural and morphological features. It is revealed that the MIL method is able to achieve promising results with a low-dimensional feature space, and, provide a practical strategy for processing large-scale high-resolution images.  相似文献   

Integration of intensity textures and local geometry descriptors from Terrestrial Laser Scanning to map chert in outcrops     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

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Land cover classification of finer resolution remote sensing data integrating temporal features from time series coarser resolution data     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Land cover classification of finer resolution remote sensing data is always difficult to acquire high-frequency time series data which contains temporal features for improving classification accuracy. This paper proposed a method of land cover classification with finer resolution remote sensing data integrating temporal features extracted from time series coarser resolution data. The coarser resolution vegetation index data is first fused with finer resolution data to obtain time series finer resolution data. Temporal features are extracted from the fused data and added to improve classification accuracy. The result indicates that temporal features extracted from coarser resolution data have significant effect on improving classification accuracy of finer resolution data, especially for vegetation types. The overall classification accuracy is significantly improved approximately 4% from 90.4% to 94.6% and 89.0% to 93.7% for using Landsat 8 and Landsat 5 data, respectively. The user and producer accuracies for all land cover types have been improved.  相似文献