Digital Terrain Model Computation from Contour Lines: How to Derive Quality Information from Artifact Analysis

@article{Bonin2005, abstract = {Digital Terrain Models constructed from contour lines often contain artifacts originating from their construction from irregularly spaced height measurements. We evaluate and illustrate these artifacts and their impact on terrain parameters. We provide algorithms to correct them as much as possible, and propose a methodology to predict areas where uncertainty still remains because of these artifacts. The analysis of these artifacts enables us to derive qualitative parameters such as “likely over-estimated”, “likely underestimated”, and “with no significant bias” on the DTM. Our method provides a qualitative description of local uncertainty, which is often more relevant for geographical applications than global quality parameters.}, author = {Bonin, Olivier and Rousseaux, Frederic }, citeulike-article-id = {364198}, journal = {GeoInformatica}, keywords = {artefacts, contour\_lines, dem, quality}, pages = {253--268}, posted-at = {2005-10-25 08:41:29}, priority = {2}, title = {Digital Terrain Model Computation from Contour Lines: How to Derive Quality Information from Artifact Analysis}, url = {http://www.springerlink.com/openurl.asp?genre=article\&\#38;id=doi:10.1007/s10707-005-1284-2}, volume = {9}, year = {2005} }

TY - JOUR ID - Bonin2005 L3 - citeulike-article-id:364198 TI - Digital Terrain Model Computation from Contour Lines: How to Derive Quality Information from Artifact Analysis JF - GeoInformatica VL - 9 SP - 253 EP - 268 N2 - Digital Terrain Models constructed from contour lines often contain artifacts originating from their construction from irregularly spaced height measurements. We evaluate and illustrate these artifacts and their impact on terrain parameters. We provide algorithms to correct them as much as possible, and propose a methodology to predict areas where uncertainty still remains because of these artifacts. The analysis of these artifacts enables us to derive qualitative parameters such as “likely over-estimated”, “likely underestimated”, and “with no significant bias” on the DTM. Our method provides a qualitative description of local uncertainty, which is often more relevant for geographical applications than global quality parameters. KW - artefacts KW - contour_lines KW - dem KW - quality AU - Bonin, Olivier AU - Rousseaux, Frederic PY - 2005/// UR - http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s10707-005-1284-2 ER -