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A comparative analysis of scanned maps and imagery for mapping applications

机译:对用于地图绘制应用程序的扫描地图和图像的比较分析

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In mapping organizations, the implementation of more automation coupled with the availability of heterogeneous data requires the investigation, adaptation and evaluation of new approaches and techniques. The demand for rapid mapping operations such as database generation and updating is continuously increasing. Due to the rising use of raster data, image analysis techniques have been investigated and tested in this study to introduce automation in the assessment of scanned topographic monochrome maps and Landsat 7 ETM+ imagery for feature separation and extraction in northern Canada. The work focuses on the detection and extraction of lakes-predominant features in the North―as well as on to their spatio-temporal comparison. Various approaches using digital image processing techniques were implemented and evaluated. Thresholding and texture measures were used to evaluate the potential of rapid extraction of certain topographic elements from scanned monochrome maps of northern Canada. A raster to vector approach (R → V) followed for the vectorization of these extracted features. The extraction of features from Landsat 7 ETM+ imagery involved image and theme enhancement by applying various image fusion and spectral transformations (e.g., Brovey, PCI-IMGFUSE, intensity-hue-saturation (IHS), principal component analysis (PCA), Tasseled Cap, Normalized Difference Vegetation Index (NDVI)), followed by image classification and thresholding. Tests showed that the approaches were more or less feature-dependent, while, at the same time, they can augment and significantly enhance the conventional topographic mapping methods. Following the analysis of the map and image data, change detection between two lake datasets was performed both interactively and in an automated mode based on the non-intersection of old and new features. The various approaches and methodology developed and implemented within a GIS environment along with examples, results and limitations are presented and discussed.
机译:在制图组织中,要实现更高的自动化程度以及异构数据的可用性,需要对新方法和新技术进行调查,调整和评估。快速映射操作(例如数据库生成和更新)的需求在不断增长。由于越来越多地使用栅格数据,因此在本研究中对图像分析技术进行了研究和测试,以将自动化技术引入扫描的单色地形图和Landsat 7 ETM +图像的评估中,以进行加拿大北部的特征分离和提取。这项工作着重于对北部主要优势湖泊的探测和提取,以及它们的时空比较。实施和评估了使用数字图像处理技术的各种方法。阈值和纹理度量用于评估从加拿大北部扫描的单色地图中快速提取某些地形元素的潜力。随后采用栅格转矢量方法(R→V)对这些提取的特征进行矢量化。通过应用各种图像融合和光谱变换(例如,Brovey,PCI-IMGFUSE,强度色相饱和度(IHS),主成分分析(PCA),流苏帽,图像处理等),从Landsat 7 ETM +图像中提取特征涉及图像和主题增强。归一化植被指数(NDVI),然后进行图像分类和阈值处理。测试表明,这些方法或多或少地依赖于特征,同时,它们可以增强并显着增强传统的地形图绘制方法。在对地图和图像数据进行分析之后,两个湖数据集之间的交互检测基于旧特征和新特征的不相交以交互方式和自动方式进行。介绍并讨论了在GIS环境中开发和实施的各种方法和方法,以及示例,结果和局限性。

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