共查询到19条相似文献，搜索用时 156 毫秒
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本文初步研究了遥感、GIS和制图一体化实用技术方法。对黄土丘陵区和沙漠地区TM数据进行了特征信息分析;给出了分层分类和GIS辅助分类结果;经模糊推理和人机交互修改,将提“纯”的遥感专题数据作为GIS的动态信息源,对GIS进行扩充与更新;最后在GIS支持下分层提取专题图并进行辅助制图。 相似文献
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地理信息系统数据模型分析 总被引：17，自引：0，他引：17
对数据模型的概念、GIS数据建模的3个抽象层次进行介绍,按照3个层次的划分对GIS数据模型进行分类,并对当前GIS概念模型存在的问题进行讨论.对已有时间概念模型进行分析,提出时空概念模型的4种划分. 相似文献
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基于知识的遥感影像模糊分类方法 总被引：3，自引：1，他引：2
介绍了目前遥感影像分类的常用方法, 提出了一种基于知识的信息提取的遥感影像模糊分类方法.采用GIS数据辅助进行遥感影像模糊法分类,从GIS数据库中提取一定数量的样本信息或挖掘知识形成规则,进行样本的训练学习或辅助进行分类判定.提高了分类的效率和精度,是对模糊分类方法一次有效改进. 相似文献
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介绍了目前遥感影像分类的常用方法,提出了一种基于知识的信息提取的遥感影像模糊分类方法。采用GIS数据辅助进行遥感影像模糊法分类,从GIS数据库中提取一定数量的样本信息或挖掘知识形成规则,进行样本的训练学习或辅助进行分类判定。提高了分类的效率和精度,是对模糊分类方法一次有效改进。 相似文献
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GIS数据在专题地图可视化表达中的应用 总被引：1，自引：1，他引：0
以GIS数据与地图表达的关系为线索,结合林业规划制图过程,分析了GIS数据与地图表达的冲突,提出通过数据选择系统、分析与制图一体化策略及地图表现层次分类系统的构建来实现GIS数据与地图表达的融合,提高专题地图制图质量。 相似文献
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《测绘与空间地理信息》2020,(5)
以现有的利用Arc GIS进行点云手动分类的方法为标准,以利用Terra Scan进行半自动分类的方法为研究分析对象,通过选取6组不同区域类型数据对比分析电力线点分类结果,得出Terra Scan电力线分类精度为98.4%,并在此基础上分析了Terra Scan进行点云分类的区域实用性和参数敏感性,为激光雷达点云数据中电力线自动快速分类提供支撑。 相似文献
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Data mining techniques are used to discover knowledge from GIS database in order to improve remote sensing image classification.Two learning granularities are proposed for inductive learning from spatial data,one is spatial object granularity,the other is pixel granularity.We also present an approach to combine inductive learning with conventional image classification methods,which selects class probability of Bayes classification as learning attributes.A land use classification experiment is performed in the Beijing area using SPOT multi-spectral image and GIS data.Rules about spatial distribution patterns and shape features are discovered by C5.0 inductive learning algorithm and then the image is reclassified by deductive reasoning.Comparing with the result produced only by Bayes classification,the overall accuracy increased by 11% and the accuracy of some classes,such as garden and forest,increased by about 30%.The results indicate that inductive learning can resolve spectral confusion to a great extent.Combining Bayes method with inductive learning not only improves classification accuracy greatly,but also extends the classification by subdividing some classes with the discovered knowledge. 相似文献
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基于空间数据发掘的遥感图像分类方法研究 总被引：16，自引：0，他引：16
采用数据发掘技术从 ＧＩＳ数据库和遥感图像中发现知识,用于改善遥感图像分类。提出了两种实施空间数据归纳学习的途径：在空间对象粒度上学习和直接在像元粒度上学习。分析了两种粒度学习的特点和适用范围,同时提出了一种归纳学习与传统图像分类法的结合方式。用北京地区 ＳＰＯＴ多光谱图像和 ＧＩＳ数据库进行土地利用分类的试验证明,归纳学习能较好地解决同谱异物、同物异谱等问题,显著提高分类精度,并且能够根据发现的知识进一步细分类,扩展了遥感图像分类的能力。 相似文献
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Data mining techniques are used to discover knowledge from GIS database in order to improve remote sensing image classification. Two learning granularities are proposed for inductive learning from spatial data, one is spatial object granularity, the other is pixel granularity. We also present an approach to combine inductive learning with conventional image classification methods, which selects class probability of Bayes classification as learning attributes. A land use classification experiment is performed in the Beijing area using SPOT multi-spectral image and GIS data. Rules about spatial distribution patterns and shape features are discovered by C5.0 inductive learning algorithm and then the image is reclassified by deductive reasoning. Comparing with the results produced only by Bayes classification, the overall accuracy increased by 11% and the accuracy of some classes, such as garden and forest, increased by about 30%. The results indicate that inductive learning can resolve spectral confusion to a great extent. Combining Bayes method with inductive learning not only improves classification accuracy greatly, but also extends the classification by subdividing some classes with the discovered knowledge. 相似文献
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以新疆阜康地区为研究区,利用遥感和GIS技术及数理统计学方法,利用ERDAS软件,通过对70年代MSS和2000年ETM影象的几何校正、图象增强、应用目视解译方法,在地理信息系统软件ArcGIS中编制两期生态景观图,利用矢栅转换和叠置功能来研究土地及植被类型的面积及空间分布状况在两期图中的变化,并通过土地利用与土地覆被变化来研究70年代到2000年西部干旱区土地及植被类型变化过程和趋势。 相似文献
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Manfred Ehlers Monika Ghler Ronald Janowsky 《ISPRS Journal of Photogrammetry and Remote Sensing》2003,57(5-6):315
The advent of very high-resolution satellite programs and digital airborne cameras with ultra high resolution offers new possibilities for very accurate mapping of the environment. With these sensors of improved spatial resolution, however, the user community faces a new problem in the analysis of this type of image data. Standard classification techniques have to be augmented with appropriate analysis procedures because the required homogeneity of landuse/landcover classes can no longer be achieved by the integration effect of large pixel sizes (e.g., 20–80 m). New intelligent techniques will have to be developed that make use of multisensor approaches, geographic information system (GIS) integration and context-based interpretation schemes.The ideal goal should be that GIS ‘intelligence’ (e.g., object and analysis models) should be used to automate the classification process. In return, GIS objects can be extracted from a remote sensing image to update the GIS database. This paper presents the development of an automated procedure for biotope type mapping from ultra high-resolution airborne scanner data (HRSC-A). The hierarchical procedure incorporates a priori GIS information, a digital surface model (DSM) and multispectral image data. The results of this study will serve as a basis for a continuous environmental monitoring process in the tidally influenced region of the Elbe River, Germany. 相似文献
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Analytical Modelling of Positional and Thematic Uncertainties in the Integration of Remote Sensing and Geographical Information Systems 总被引：1，自引：0，他引：1
This paper describes three aspects of uncertainty in geographical information systems (GIS) and remote sensing. First, the positional uncertainty of an area object in a GIS is discussed as a function of positional uncertainties of line segments and boundary line features. Second, the thematic uncertainty of a classified remote sensing image is described using the probability vectors from a maximum likelihood classification. Third, the "S-band" model is used to quantify uncertainties after combining GIS and remote sensing data. 相似文献
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水稻播种面积是农业管理部门关心的重要问题之一。本文介绍了证据理论在遥感图像分类上的应用,并以汉川市为示范区,采用2002年TM遥感影像,在GIS技术支持下,通过建模运算,剔除不可能是水稻的像元。然后将证据理论用于影像分类,将影像初次分类结果,与参考图对照,将不满足要求的区域提取出来,再次进行第二次分类。将第二次分类结果与参考图对照,显示分类效果满足要求;若不满足要求,可继续进行再次分类,直到分类效果满意为止。将两次分类结果中的水稻信息进行叠加,提取出水稻遥感信息,经检验精度达到91.39%。 相似文献
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基于灰度共生矩阵(GLCM)的纹理特征在影像空间分析中具有重要作用,提出了一种在领域空间知识辅助下构建GLCM多尺度窗口与主方向权值的方法,从而提高纹理特征的有效性,并解决影像土地利用分类中存在的不确定性问题。为此,根据人类目视解译的特点,对GIS与RS数据进行集成计算:首先,在图像配准的基础上,利用经典的GIS空间数据挖掘算法,渐近式地提取领域形态知识;接着,采用关联分析法建立其与GLCM构造因子之间的响应机制,并设计了基于地类形状指数的多尺度窗口建立算法,以及基于地类主方向分布指数的方向权值测度算法。试验结果表明,领域形态知识与GLCM空间因子之间具有强相关关系,该方法提取出的纹理特征可以描述复杂地物的空间意义,算法复杂度低,性能优越,有效提高了影像土地利用分类的精度。 相似文献