Detection and Labeling of Sensitive Areas in Hydrological Cartography Using Vector Statistics


The recognition and delineation of hydrological stream lines has, historically, been a subjective manual task in cartography. But, digital elevation models (DEMs) are nowadays typically employed to extract stream lines automatically, via the utilization of geographic info systems. Whereas the automatic generation of hydrological networks presents errors, their manual recognition can be virtually arbitrary. During this paper, we have a tendency to propose a technique with that to label potentially sensitive zones in the comparison of hydrological cartographic networks. Two completely different sources were analyzed: a conventional cartographic stream network, and one automatically extracted from a DEM. The seventy two 500 vectors of displacement, representing the spatial disagreement (or work) between the stream networks, were also examined. A variety of outstanding distributions of large errors were identified that were a cause for alarm; these errors are here denoted by “warnings” and are classified into six different groups. The displacement vectors were additionally analyzed in terms of modulus and azimuth, thereby permitting the analysis of the isotropy of the spatial displacements. We propose the utilization of all of the derived info as metadata for hydrological spatial quality, furthermore as the extension of the methodology to any different kind of cartographic part (roads, cadastral, etc.) for that 2 different vector format information sources are compared.

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