Classifications

• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
  • G06T17/05—Geographic models

Definitions

• This invention relates to a digital elevation model (herein abbreviated to DEM) and, more particularly, to an enhanced resolution DEM that is derived from available digital elevation information utilising information that is available independently of the existing DEM.
• DEM digital elevation model
• an enhanced DEM was interpolated from 1 :50000 scale (20m vertical interval) contours using an algorithm developed by the Australian National University.
• One region in respect of which such a DEM was developed is the Western Cape region of South Africa and that particular DEM will be referred to herein as the WCDEM.
• the WCDEM still remains the DEM of choice for many applications for that region. This is mainly due to its relatively high spatial resolution, consistency and accuracy. Centres for geographical analysis such as the Centre for Geographical Analysis (CGA) in South Africa receive frequent requests for more detailed (i.e. larger-scaled) DEMs.
• CGA Centre for Geographical Analysis
• the CDNGI has also made available 1 :10000 contours (ranging from 5m to 20m vertical interval) and spot heights, which were digitized from the 1 :10000 orthophoto map series and the CGA has produced many very high resolution ( ⁇ 20m) DEMs from 1 :10000 scaled contour data, where this information is available, and stereographic aerial and satellite imagery.
• this data set covers only 43% of South Africa.
• CDNGI has developed a 25m DEM (also known as the "ORT- files") covering some parts of South Africa.
• GTOPO30 DEM the 90m Shuttle Radar Topography Mission
• SRTM the 90m Shuttle Radar Topography Mission
• GDEM the 30m Global DEM
• the GTOPO30 DEM, SRTM DEM and GDEM are generally considered to be unsuitable for some applications (e.g. flood modeling, geomorphometry, civil engineering) due to their relatively low resolutions (30m or less) and quality.
• ASTER-GDEM contains anomalies such as residual cloud patters and stripe effects.
• ASTER stands for Advanced Spaceborne Thermal Emission and Reflection Radiometer which is a Japanese sensor which is one of five remote sensory devices on board the Terra satellite launched into Earth orbit by NASA in 1999.
• the instrument has been collecting superficial data since February 2000 and provides high- resolution images of the planet Earth in 15 different bands of the electromagnetic spectrum, ranging from visible to thermal infrared light. The resolution of images ranges between 15 to 90 meters.
• ASTER data are used to create detailed maps of surface temperature of land, emissivity, reflectance, and elevation.
• the so-called SRTM DEM contains some areas with no elevation information at all (i.e. voids).
• the Shuttle Radar Topography Mission is an international research effort that obtained DEMs on a near-global scale from 56° S to 60° N, to generate the most complete high-resolution digital topographic database of Earth prior to the first release of the ASTER GDEM in 2009.
• SRTM used a specially modified radar system that flew on board the Space Shuttle Endeavour.
• the vertical accuracy of the SRTM DEM is, however, relatively high ( ⁇ 6m), which makes it an attractive source for regional applications. Contours are not ideal for interpolating DEMs as their densities vary with slope gradient. Areas of low relief are particularly problematic as contours are often spaced far apart (horizontally) reducing the reliability of interpolations in such areas.
• Contour density is further reduced as the vertical interval of the contours increases (i.e. contours with a 5m vertical interval generally produce a better DEM than contours with a 20m vertical interval) and as scale increases (i.e. contours with a 20m vertical interval captured at 1 :10000 scale usually contain more detail than contours with the same vertical interval captured at 1 :50000 scale).
• a method of producing an enhanced resolution DEM that uses contour data to improve the accuracy of an original DEM, the method comprising fusing, with the original DEM, an intermediate DEM interpolated from contours wherein the intermediate DEM has a resolution higher than the native resolution of the original DEM, the fusion being carried out in a manner that the contour information dominates only in areas where the contour density is significantly higher than the original DEM.
• a method of producing an enhanced resolution DEM comprising the steps of:-
• step 3 deriving a slope gradient raster from either the intermediate DEM or the modified DEM; 4. adding a small constant value (e.g. 1 ) to the result of step 3 to ensure that all values are larger than 1 ;
• step 6 using a mean spatial filter to generalise the result of step 4; 7. normalizing the result of step 6 to a range of between 0 and 1 , using linear scaling;
• step 10 multiplying the result of step 9 with the result of step 1 ; and, 1 1 . adding the result of step 10 to the result of step 8.
• the intermediate DEM to have a resolution several factors higher than the original DEM; for the original DEM to be the SRTM DEM; for the slope gradient derived in step 3 to be selectively derived from the intermediate DEM or modified DEM with the selection typically being that of which the output is generally better (smoother) and that would commonly be the intermediate DEM; for step 1 to be carried out using a facility selected from TopoToRaster_sa; Spline; Nearest Neighbour; and Kiging with a preference towards TopoToRaster_sa; for step 2 to be carried out by converting the original DEM to points using, for example, the RasterToPoint_conversion tool followed by processing these points using a suitable interpolation tool such as the Sline_sa tool such that the cells of the intermediate DEM and the modified DEM match substantially perfectly; and for step 4 to be carried out using the Plus_sa tool in ArcGIS.
• the RasterToPoint_conversion tool such as the Sline_sa tool such that the cells of the intermediate
• Still further features of the invention provide for attribute errors in the digitized contours and spot heights to be corrected, at least to some extent, before interpolation to produce the intermediate DEM; for spatial errors such as gaps and mismatching of contours at the edges of map sheets to be corrected, at least to some extent, before interpolation to produce the intermediate DEM; for voids in the original DEM to be filled in using elevation values interpolated from the corrected contours and spot heights prior to producing the modified DEM; and for elevation spikes in the original DEM to be removed whilst correcting contours and spot heights.
• step 5 the use of a logarithmic transformation of slope gradient is important because it produces a better distributed histogram and prevents the dominance of the original DEM during fusion.
• Step 6 may also be called a low-pass filter or smoothing neighbourhood operation.
• Figure 1 is a schematic illustration of a large area broken up into individual mapping areas
• Figure 2 is an example of hillshades of an area covered by an original SRTM DEM.
• Figure 3 is an example of hill shades of the same area following processing according to the invention.
• the main problems experienced with the input data were related to attribute errors in the digitized contours and spot heights; spatial errors such as gaps and mismatching contours at the edges of map sheets; and voids in the SRTM DEM.
• Attribute errors refer to instances in which the elevations stored in the "HEIGHT" field of contours and spot heights were incorrectly captured from the original maps.
• An algorithm was developed and implemented to identify and correct such errors. The algorithm examines vertical profiles (cross sections) created at regular intervals (determined by the extent of the smallest contour) within a specified area to find errors. Each profile is normalized (i.e. the horizontal distance between contours is unified) and tested against a set of topological rules. The algorithm not only identifies incorrect contours (or sequences of contours) but also "corrects" errors by examining each profile. The corrections were then verified by an operator. About 1 % (2926 of 3479217) of the contours that were used as input to the contour interpolation required attribute corrections.
• Voids in the SRTM DEM were filled using elevation values interpolated from the corrected contours and spot heights.
• a similar procedure was used to remove elevation spikes in the SRTM DEM.
• the procedure of the invention was developed using a combination of algorithms.
• the ANUDEM algorithm (as implemented by the Topo to Raster function in ArcGIS) was used for interpolating a DEM from contours and spot heights.
• ANUDEM is a program that calculates regular grid digital elevation models (DEMs) with sensible shape and drainage structure from arbitrarily large topographic data sets. It has been used to develop DEMs ranging from fine scale experimental catchments to continental scale.
• the product an intermediate DEM, was employed to identify and correct the errors in the SRTM DEM (i.e. voids and spikes). Once corrected, the SRTM DEM was fused with the intermediate DEM using a newly-developed algorithm which ensures that the SRTM DEM is only applied in areas with low densities of contours and spot heights. Although it is recognized that the SRTM DEM is not a true DEM, the fusion procedure reduces the effect of surface objects.
• Equation 1 suggested the use of Equation 1 to calculate the appropriate cell size when interpolating DEM from contours.
• the "optimal" resolution varied between 5m and 50m. Consequently, it was decided to produce the DEM at a 5m resolution to ensure that no topographical variation becomes lost as a result of cell size.
• Producing the upgraded DEM of the invention at 5m resolution will also enable the incorporation of other DEM (e.g. those that were created using stereo images and LiDAR) in the future.
• Equation 1 - TM 2 ⁇ ⁇ /
• p is the pixel size
• A is the total size of the study area
• / represents the contour length
• FocalStatistics_sa (mean with a 1 1 x1 1 cell kernel) is used to generalise the result of step 4.
• step 6 Normalise the result of step 6 to a range between 0 and 1 , using linear scaling. This can be done using the SingleOutputMapAlgebra_sa tool. 8. Multiply the interpolated intermediate DEM's values with the result of step 7 using the Times_sa tool.
• Equation 3 Equation 3:

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Cited By (14)

Citations (1)

• 2013
  • 2013-02-11 WO PCT/IB2013/051117 patent/WO2013121340A1/en active Application Filing
  • 2013-02-11 BR BR112014019836-5A patent/BR112014019836B1/pt not_active IP Right Cessation
• 2014
  • 2014-07-04 ZA ZA2014/04917A patent/ZA201404917B/en unknown

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