Improving the accuracy of digital terrain models
01 Jan 2008-
TL;DR: The change from paper maps to GIS, in various kinds of ge- ographical data analysis and applications, has made it easy to use the same spatial data for dierent applications.
Abstract: The change from paper maps to GIS, in various kinds of ge- ographical data analysis and applications, has made it easy to use the same spatial data for dierent
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Journal Article•
01 Jan 2009-The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
TL;DR: In this article, the authors analyzed the capabilities of new space-borne interferometric SAR missions with respect to their potential of deriving building heights, and carried out a thorough analytical accuracy analysis involving various sensor and scene parameters.
Abstract: The great potential of space-borne SAR images for semi- or fully-automatic mapping of topographic features has been shown by many approaches. While most of them focus on 2D mapping of topographic features, some preliminary research on the complex task of automatic delineation of 3D information in urban environments has been initiated in recent years. In this paper, we analyze the capabilities of new space-borne interferometric SAR missions – in particular the German TanDEM-X mission – with respect to their potential of deriving building heights. To this end, we summarize the mathematical framework and carry out a thorough analytical accuracy analysis involving various sensor and scene parameters.
8 citations
Journal Article•
4 citations
TL;DR: In this article, the application of satellite images of SPOT 7, acquired on 10 October 2014, for producing the high spatial resolution digital elevation models of five glaciers in the USA.
Abstract: The present study describes the application of satellite images of SPOT 7, acquired on 10 October 2014 for producing the high spatial resolution digital elevation models of five glaciers in...
2 citations
Cites methods from "Improving the accuracy of digital t..."
...Many methods exists for image matching process and generation of digital elevation model using stereo images (Lucas and Kanade 1981; Droj 2008; Heid and K€a€ab 2012)....
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01 Jan 2010
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01 Jan 2011
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References
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01 Jan 2000
75 citations
01 Jan 2002
TL;DR: In this paper, the authors explored a methodology for quantifying the uncertainty of DEMs created by digitizing topographic maps and examined the origins of uncertainty in DEM production, by computing a vector total of Root Mean Square Error from the source map, sampling and measurement errors, and the interpolation process.
Abstract: This paper explores a methodology for quantifying the uncertainty of DEMs created by digitising topographic maps. The origins of uncertainty in DEM production were identified and examined. The uncertainty of DEM data was quantified by computing a vector total of Root Mean Square Error (RMSE) from the source map, sampling and measurement errors, and the interpolation process. Distributional measures including accuracy surfaces, spatial autocorrelation indices, and variograms were also employed to quantify the magnitude and spatial pattern of the uncertainty. The test for this methodology utilises a portion of a 1:24 000 topographic map centred on Stone Mountain in northeastern Georgia, USA. Five DEMs, constructed with different interpolation algorithms, are found to have the total RMSE ranging from 4.39 to 9.82 meters, and a highly concentrated pattern of uncertainty in rugged terrain. This study suggests that the RMSE provides only a general indicator of DEM uncertainty. Detailed studies should use distributional measures to understand how the uncertainty varies over a surface.
66 citations
01 Jan 2001
TL;DR: In this article, the sensitivity of ordinary Kriging interpolation in the GIS environment was evaluated with respect to the resolution of the predicted grid and conclusions were drawn for applications in spatial analysis.
Abstract: The demand for spatial data is on the rise. However, even the latest technology cannot guarantee an error free database in Geographic Information System (GIS). In natural resources the point field sampling is often used for spatially oriented projects and interpolation methods are implemented to predict the values in an unsampled location and to generate maps. In order to evaluate the performance of Kriging interpolation in GIS the Kriging errors were analyzed and compared to the four other interpolation methods using fundanmental statistical parameters. The sensitivity of ordinary Kriging interpolation in the GIS environment was evaluated with respect to the resolution of the predicted grid and conclusions were drawn for applications in spatial analysis.
34 citations
"Improving the accuracy of digital t..." refers methods in this paper
...Kriging [11], and between IDW, Kriging, Thiessen polygons and TIN [8] and IDW, minimum curvature, modified Shepard and TIN [10]....
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01 Jan 2004
TL;DR: This paper presents an algorithm that produces a non-negative graph through scattered positive data sets using Modified Quadratic Shepard method, which is improved in that it produces the positive graph without much deviation of shapes from the ones due to Modified QuadRatic Shepard scheme.
Abstract: This paper is about the visualization of positive data subject to positivity constraint. It presents an algorithm that produces a non-negative graph through scattered positive data sets using Modified Quadratic Shepard method. The objective of positivity has been achieved by scaling of basis functions as far as it is necessary. This method is improved in that it produces the positive graph without much deviation of shapes from the ones due to Modified Quadratic Shepard scheme. The method is developed and implemented as a global scheme.
17 citations
"Improving the accuracy of digital t..." refers methods in this paper
...These methods are Inverse distance weighted (IDW), Spline Biquadratic interpolation, Spline Bicubic interpolation, B-spline interpolation, Nearest neighbors - Voronoi diagrams , Delaunay Triangulation, Quadratic Shepard interpolation, Kriging interpolation [1, 5, 7]....
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22 Nov 1997
TL;DR: In this article, the authors discuss ways to represent a triangulated irregular network (TIN) in a data structure, and give some of the basic algorithms that work on TINs.
Abstract: Digital elevation models can represent many types of geographic data. One of the common digital elevation models is the triangulated irregular network (also called TIN, or polyhedral terrain, or triangulated terrain). We discuss ways to represent a TIN in a data structure, and give some of the basic algorithms that work on TINs. These include retrieving contour lines, computing perspective views, and constructing TINS from other digital elevation data. We also give a recent method to compress and decompress a TIN for storage and transmission purposes.
15 citations