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APPLYING TERRAIN AND HYDROLOGICAL EDITING TO TANDEM-X DATA TO CREATE A CONSUMER-READY WORLDDEM PRODUCT

APPLYING TERRAIN AND HYDROLOGICAL EDITING TO TANDEM-X DATA TO CREATE A CONSUMER-READY WORLDDEM... The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany APPLYING TERRAIN AND HYDROLOGICAL EDITING TO TANDEM-X DATA TO CREATE A CONSUMER-READY WORLDDEM PRODUCT J. Collins, Dr. G. Riegler, H. Schrader, M. Tinz Airbus Defence and Space, Geo-Intelligence ([email protected]) - Claude-Dornier-Straße, 88090 Immenstaad, Germany KEY WORDS: WorldDEM, TanDEM-X, TerraSAR-X, SAR, DSM, elevation model ABSTRACT: The Geo-intelligence division of Airbus Defence and Space and the German Aerospace Center (DLR) have partnered to produce the first fully global, high-accuracy Digital Surface Model (DSM) using SAR data from the twin satellite constellation: TerraSAR-X and TanDEM-X. The DLR is responsible for the processing and distribution of the TanDEM-X elevation model for the world’s scientific community, while Airbus DS is responsible for the commercial production and distribution of the data, under the brand name WorldDEM™. For the provision of a consumer-ready product, Airbus DS undertakes several steps to reduce the effect of radar-specific artifacts in the WorldDEM data. These artifacts can be divided into two categories: terrain and hydrological. Airbus DS has developed proprietary software and processes to detect and correct these artifacts in the most efficient manner. Some processes are fully- automatic, while others require manual or semi-automatic control by operators. 1. CREATING A CONSUMER-READY WORLDDEM The acquisition strategies described above were undertaken to PRODUCT ensure a maximum coverage of the earth’s surface, with a maximum vertical accuracy. Preliminary results indicate that the 1.1 The TanDEM-X Mission and WorldDEM Product strategy appears to have been successful, with a minimum of areas with no data (voids) and a corresponding high accuracy. Airbus Defence and Space and the German Aerospace Center (Bachmann 2013) However, it was always anticipated that there (DLR) have partnered to produce the first truly global, high- would be certain areas of the earth that would not interact well accuracy Digital Surface Model (DSM) using the with X-band radar signals and would therefore subject to some interferometric data from the twin satellite constellation: invalid and or inaccurate data being collected and processed. TerraSAR-X and TanDEM-X. The DLR is responsible for the The first surface that is highly susceptible to invalid height processing and distribution of the TanDEM-X elevation model elevations in the DSM is waterbodies. Early-on during research to the world’s scientific community, while Airbus DS is on radar signal propagation, it was known that smoother responsible for the commercial production and distribution of surfaces, such as water, can be highly reflective to short-band the data, under the brand name WorldDEM™. radar waves (Davies 1954 and Grant, Yaplee 1957) As radar later became a tool for mapping with the start of widespread X- 1.2 Radar Effects in Processed SAR Elevation Data band SAR data collections (SRTM and commercial airborne radar) it became well understood that the relatively short The WorldDEM DSM is derived from the phase information wavelengths (~3cm) of X-band radar are frequently reflected by from two Synthetic Aperture Radar (SAR) signals using water surfaces, away from the receiving antennas (Farr et.al. interferometric processing of X-band radar signals. The height 2007). The almost complete reflection of the radar signals by information is obtained for any point on the earth’s surface by water surfaces means that the receiving antennas have little or calculating the phase difference received by the two receiving no information about the surface heights of water. When the antennas on the mission’s two satellites (TerraSAR-X or SAR data comes to be processed, there is no interferometric TanDEM-X). In order to accurately measure surface heights baseline for the processor to set an elevation over water: from space, it is essential that the orbits (i.e. height from the therefore the heights calculated for most water surfaces appear ground) of the satellites be precisely measured. In addition, the to be nothing more than random noise in the resulting DSM. In separation of the two receiving antennas must also be known areas of more widespread water, the SAR processors are usually extremely precisely. Fortunately, the precision of the two designed to detect the lack of signal coherence and assume that satellites’ orbits is very well understood, as is the separation an area is water. In these larger areas, no surface elevation is between them in flight. (DLR 2013) calculated and the elevations are simply set using the “no data” The TanDEM-X mission recorded height information for the flag value of -32767m. whole earth’s surface at least two times. (DLR 2013) In more While there are clearly difficulties with X-band radar SAR data “challenging” areas (steep, sandy or heavily-forested areas) up over water, it should be clear that this is not an insoluble to four acquisitions were made, in order to improve the resulting problem. While the elevations calculated over the surface of surface model. These additional acquisitions took advantage of water are not accurate, the elevations calculated on the surfaces different acquisition geometries: either looking at the earth’s immediately adjacent to water (shorelines) are in fact coherent, surface from another orbital direction, or by directly adjusting accurate and consistent. This means that while the elevation of the angle of signal acquisition, with reference to the earth’s the water in a lake might not be correct in the TanDEM-X data, surface. These techniques allowed the satellites to “see” more the elevation of the shoreline of the lake can be assumed to be surfaces in challenging terrain and enabled the improved correct, within the relative accuracy of the overall product. This acquisition of surfaces that were more likely to deflect radar important distinction between incoherent water and coherent waves away from the receiving antennas on the satellites. This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1149 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany shorelines shall become clearer later, when this information can be used to edit the elevations of water in the WorldDEM data. During SAR processing, surfaces other than water can be subject to the same signal reflection challenges as water. These include large areas of sand (deserts, beaches) dry and salt lakes, continuous areas of flat and smooth rock and finally ice and snow (fields and or ice-sheets). In the processed TanDEM-X data, many of these surfaces can exhibit some of the characteristics of water, such as extreme noise and/or voids in the resulting DSM, due to radar signal reflection. As noted above, the TanDEM-X mission planners worked hard to overcome the limitations posed by these smooth surfaces by customizing the acquisition process, where these features are widespread. However, the fact remains that some of these smooth features will not be accurately represented in the resulting TanDEM-X surface model. Figure 2: Elevation spikes on a steep mountain slope A third type of elevation error occurs when the SAR processor has sufficient data to calculate the elevation over an area, but 1.4 Bespoke Production Software for the Production of the uncertainty of the interferometric principle means that the processor generates a consistent surface, which does not have a WorldDEM Products correct elevation. This problem can occur when the processor is Airbus Defence and Space Geo-intelligence division provides unable to accurately calculate the number of height offsets from WorldDEM data to clients in three forms: WorldDEM , the reference surface. This can lead to areas being represented core WorldDEM and WorldDEM DTM. WorldDEM is the as either too high, or too low in the resulting DSM. Islands, core unedited version of the WorldDEM. WorldDEM DTM is particularly in lakes and rivers, are most susceptible to this subject to additional processing, which removes surface features problem. such as buildings and vegetation, to leave the elevations of the Very steep areas can also provide a challenge to the TanDEM-X terrain in the model: however, these two additional products are SAR processor. Steep slopes that face directly into the radar beyond the scope of this paper. during acquisition are generally well-portrayed in the DSM. The WorldDEM product is subject to terrain correction and However, steep slopes that faced away from the acquisition (and hydrological editing, to provide clients with the most reasonable were not acquired from a different angle in a further compromise of data quality, availability and price. In order to acquisition) may be poorly represented in the DSM. This occurs produce WorldDEM over large areas of the globe, a number of as the SAR processor is unable to calculate an accurate surface, terrain and hydrological editing processes were developed by because the elevations change so rapidly in a short distance. It is Airbus DS. In the initial stages, these processes were developed possible for some of these steep areas to be completely void in using commercial mapping and GIS software. However, it was the resulting DSM. always envisioned that the data volumes to be produced would A final challenge that occurs in the TanDEM-X DSM are voids. exceed the reasonable capacities of commercial software. So During the course of more than three years of acquisitions, care Airbus DS Geo entered into a cooperation with a company that was taken to acquire every square kilometer of the earth’s has significant experience with three-dimensional relief surface. The reality is that due to any number of operational portrayal and data manipulation, in order to produce a software factors, some areas of the earth’s surface were never acquired. package to efficiently edit large volumes of WorldDEM data. These areas are portrayed as void in the resulting DSM and set The resulting software package, called Demes, is designed to to the null value of -32,787m, so that they can be easily automate as much of the terrain and hydrological editing as identified. possible, while still leaving the flexibility of human interaction with the data, when the automatic processes to not provide the 1.3 Examples of Radar Effects in TanDEM-X Data intended results. The Demes editing software works on a Shown below are some examples of X-band radar effects, that standard PC workstation, and allows production staff to view, interact with and edit data directly. Demes server software are apparent in the TanDEM-X data before editing is applied. In manages the data workflow process: ensuring that data flows all images, the vertical exaggeration of the shaded relief images is 1x. efficiently and consistently through the production stream, from initial ingest, through to final Quality Control (QC) and client delivery. 1.5 Editing Rules and Editing Guidance In order to ensure consistency across the full edited WorldDEM dataset, a series of editing rules has been developed. These rules guide operators in their daily work to ensure that the correct terrain and hydrological features are being edited. The rules contain information about the identification and size of features to be edited and what software tools are acceptable for editing individual features. Because the earth’s surface is extremely variable from equator to the poles, further guidance is published to ensure that all operators are aware of special or single-instance surface Figure 1: Characteristic roughness of the unedited WorldDEM features. For example, a mangrove area consists of significant DSM over a lake This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1150 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany vegetation that stands in a continuously flooded part of the clients generally prefer to have some DSM information, rather ocean shoreline. This could cause confusion among different than none, when WorldDEM is unable to provide any height operators, with one classifying mangroves as ocean, while information. For the benefit of WorldDEM users, areas of the another classifies them as land. When such uncertain features DSM that are interpolated or infilled with another DSM source are found in the data, a decision is made on how to treat them. are identified in data masks that are delivered along-side of the The decision and detailed technical guidance is posted on an WorldDEM elevation dataset. internal Wiki, so that all operators have access to the same For the filling of larger voids, the Delta Surface Fill (DSF) information. method of void filling is applied. First developed by the National Geo-Spatial Intelligence Agency (NGA) to infill voids 2. TERRAIN EDITING in SRTM data, the Delta Surface method of infilling has the advantage of using the most accurate WorldDEM data at the 2.1 Spike and Well Removal edge of a void to seed the elevations of the less accurate fill source (Grohman 2006). Therefore a fill source that might have Spikes and wells are among the simplest of artefacts to identify an overall acceptable portrayal of a surface feature, but might and remove from the WorldDEM dataset. These are single pixel not be as accurate as WorldDEM data, will be manipulated to elevation errors, where the elevation of a point on the surface conform to the more accurate WorldDEM data at the edges of model is significantly different from the elevations of its the void. neighbors. A spike is a positive elevation difference, while a The Demes software allows the operator to use the DSF method well is a negative elevation difference to neighboring pixel. of filling, either on a single void, multiple voids, or even every These spikes and wells are identified using a threshold large void in a single Geocell. This flexibility allows the difference elevation and are removed using a simple operator to efficiently fill a number of similar voids at the same interpolation using the eight neighboring pixel elevations. The time, while maintaining the flexibility to manually handle a Demes software identifies and corrects spikes and wells in a single more complex void, which might require perhaps a single step. A QC tool is available to identify any spikes and different filling source than the other voids in the Geocell. wells that might have been missed by the tool, especially in steep terrain, or along Geocell edges. These spikes or wells may 2.3 Identification and Correction of Systematic and require individual manual editing to be completely removed. Random Errors 2.2 Identification and Infilling of Voids While voids are generally easy to identify and treat in the WorldDEM data, there are two further categories of surface Another simple terrain artefact to identify and remove is areas elevation artefacts that require additional editing to create a that are void in the DSM. These voids are areas where either the consumer-ready product: random and systematic errors. data was not acquired, or the SAR processor was unable to calculate a valid elevation. Voids are identified in the data as 2.3.1 Identification of systematic and random errors elevations with the null data value of -32,767m. The DLR provides additional data masks as part of the TanDEM-X data package. These masks are generated during 2.2.1 Small voids the SAR processing and subsequent mosaicking of the data into The production strategy with void data is to interpolate small a final DSM product. These masks are central to the voids, while larger voids are infilled (wherever possible) with identification of random and/or systematic errors in the DSM an alternate elevation data source. The definition of a small data. void, is any void that is between one and sixteen contiguous The Height Error Mask (HEM) represents the height error of pixels of void data. Any void larger than sixteen contiguous any pixel in the form of a standard deviation and is derived pixels is considered to be a large void. All calculations of void during the SAR processing from the interferometric coherence sized consider the eight-way connection of pixels (edge- of every pixel measurement in the dataset. adjacent and corner-adjacent). The information derived from the HEM is used to identify areas Small voids are edited in Demes using the Inverse Distance in the DSM that are likely invalid, because the SAR processor Weighted (IDW) method of interpolation. IDW is based on the only had weak or limited information about those areas. In assumption that things that are close to one another are more addition, the height information contained in the pixels with alike than those that are farther apart from each other (ESRI poor values in the HEM are likely somewhat inconsistent with 2007). Therefore any pixel that does not have a measurement neighboring pixels (often visible as a certain “rough” texture in should be interpolated (and its height calculated during the DSM). The assumption is that in any DSM, neighboring interpolation) in reference to closer known points than to known elevation measurements should be somewhat consistent with points that are further away. The IDW process uses a standard each other. This combination of poor HEM values and a low weighting based on the distance to known points, providing a consistency with neighboring pixels, provides a good indication more plausible interpolated height than a simple linear of pixels/areas that likely have a high likelihood of random interpolation would. errors. Surfaces that are frequently subject to high random error include tropical forests and to a lesser extent, highly built-up 2.2.2 Large voids urban areas. The treatment of larger voids is somewhat different. While it is A second mask provided by the DLR, the Consistency Mask also possible to interpolate larger voids, their larger extent (COM) indicates DSM pixels that have inconsistencies between means that the likelihood of the interpolation providing an the different acquisitions (known as a Phase Unwrapping error accurate portrayal of the earth’s surface diminishes greatly as or a Cycle Shift). As noted previously, all areas of the earth’s the void area becomes wider or longer. In such cases, the void surface were collected at least twice during the TanDEM-X area is infilled with an alternate DSM data source, such as mission. A limited instance of the data collected have different SRTM or ASTER GDEM. While these alternate datasets might elevations processed from the two (or more). not have the same accuracy or temporal information as the surrounding WorldDEM data, it is understood that commercial This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1151 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany Figure 4: The RLM (left) indicating an area of forest where elevations are somewhat less reliable 2.5 Editing Terrain Using Demes Figure 3: Example of a Phase Unwrapping error caused by the Before the terrain editing of artefacts identified in the RLM can harvesting of trees in a forest between TanDEM-X acquisitions begin, one more mask transformation is required. Because the RLM identifies each and every pixel that might have a random Pixels that are identified as having two (or even more) or systematic error, a further simplification is required. elevations between acquisitions are identified in the COM. In Generally a single pixel that displays the low to medium the TanDEM-X SAR processing, only a single final height can likelihood of error is not a major concern. Similarly, two or be derived. The processor uses a number of tests to determine three pixels next to each other, showing only a slight likelihood the best-fitting elevation, (such as number of measurements at of an error need not be edited. The goal of this simplification is the same height, pixel coherence from each acquisition, etc…) to identify larger areas of concern, where higher error values are if there is a conflict between acquisitions. Whatever final height present. This is done by creating a new mask: the Feature Mask is derived, the fact that there was an inconsistency between (FTM). In creating the FTM, smaller less error-prone pixels are acquisitions is noted in the COM mask. This allows the Demes removed, while larger error-prone areas have their edges software to identify areas with potential elevation regularized, in order to provide a more convenient edge for inconsistencies and repair them during the terrain editing step. eventual Delta Surface Filling. In addition, areas that are likely to be cycle shifts, as identified in the COM, are given a special 2.4 Creation of the Reliability Mask classification (“offset”) in the FTM. This allows the operator to better understand the type of error that the FTM is identifying. The potential DSM errors identified in the HEM and COM Because there is the possibility that some areas that are masks are somewhat different in their source, but in the end identified in the RLM as random errors, are in fact just the noise they both need to be treated during the terrain editing process. associated with the portrayal of water in the DSM, it is In order to make the terrain editing process as efficient as necessary to screen-out potential water areas from the resulting possible, the information from the HEM and COM masks is FTM. Water bodies will be identified, classified and edited in a combined into a single mask, internal to the Demes software, separate step, outlined later. Editing water during the terrain which clearly identifies areas that require attention and/or editing step is not only inefficient, but there is a chance that repair. This mask is more than a simple combination of the infilling large areas of water with an external DSM source HEM and COM data. Rather, it uses probability values from the might adversely affect the shoreline elevations in the HEM and the DSM in an attempt to determine what is actually WorldDEM. Areas that are identified as possibly being water an error in the DSM and what is likely legitimate noise in the are flagged in the FTM as “water candidates”. These areas will DSM, perhaps caused by the legitimate roughness of a surface, be ignored during the automatic terrain editing steps described such as the top of trees in a forest. next. The option does remain for an operator to manually The amalgamation of COM, HEM and DSM error information override the water candidate class, if it has been incorrectly results in the Reliability Mask (RLM). This is an internal applied in the FTM. Demes mask, which indicates the likelihood that each pixel in a In a final mask preparation step, the size of random errors is DSM Geocell is reliable or not reliable. It further separates the classified in the transition from RLM to FTM. This is because unreliable pixels into ones that are likely unreliable because of random errors of different extents will be treated differently random uncertainty in the DSM (noise) and pixels that are during the editing of the DSM in Demes. Small artefacts are subject to offsets in the DSM due to differences between heights those between 2 and 16 neighboring pixels. Medium artefacts during acquisitions. The RLM does not discriminate between are those between 16 and 46 pixels. Any artefact 47 pixels and the size of erroneous data patches. Even areas of a single pixel larger, is considered to be a Large artefact. (that is considered erroneous) are flagged in the RLM. This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1152 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany The Demes software contains a number of tools to allow for the automatic, semi-automatic and manual delineation of waterbodies. The most important of these tools is called “Perception”. The Perception tool is a type of trained classification tool: the operator finds a small area in a Geocell that is generally representative of the image tone for the full Geocell. The operator classifies this small subset area, by adjusting the sensitivity of the Perception tool to the image tone in the subset. When a plausible result is achieved in distinguishing land areas from water areas in the subset, the same Perception settings are applied to the whole Geocell, thereby identifying waterbodies throughout the whole Geocell Figure 5: The FTM (left) demonstrates how the RLM is simultaneously. Where a Geocell has areas that display widely generalized to assist editing divergent image tones, perhaps due to different data acquisition timings in the same Geocell, the Perception tool can be run on a During editing, all Small artefacts are voided and interpolated. subset of the Geocell only, to improve the local results of the All Medium artefacts are smoothed using a Gaussian smoothing waterbody identification process. After the Perception tool is approach. Large artefacts are voided and filled, using the DSF used, a manual clean-up of some shorelines is usually required process, as described previously. Any area identified as an for some waterbodies. Demes provides the operator with a Offset in the FTM is also a candidate for filling using the DSF variety of drawing and selection tools to improve the tool. However it is recommended that an operator visually delineation of shorelines. identify Offset areas, to ensure that the filling solution is actually an improvement over the existing DSM data. There is 3.2 Waterbody Classification the possibility that a portion of an area that is identified as an offset is actually accurate DSM data and infilling this area Three different types of waterbody class are used in the would only reduce the quality of the WorldDEM. production of WorldDEM data. These three classes are applied once the operator has ensured that the shorelines of the 3. HYDROLOGICAL EDITING automatically detected waterbodies are correct. The three classifications of waterbodies are: Ocean, Lake and River. The In order to remove the characteristic noise that is present in Ocean class is set for any saline waterbody whose geoidal many water bodies in the TanDEM-X data, a three-step process reference elevation is 0m. The Lake classification is set for any must be undertaken. These three steps are: the identification and fresh-waterbody that does not normally contain any flow. The delineation of all waterbodies, their division into the correct River classification is set for drains that have a monotonic flow. class of waterbody and finally, the application of a “flattening” algorithm to set the water body to a plausible elevation. 3.3 Setting the Elevation of Classified Waterbodies 3.1 Identification and Delineation of Waterbodies Once classified, the elevations of the waterbodies are set in the Demes software. Oceans are universally set to 0m. In order to One advantage of editing water over terrain is that waterbodies set the elevation of lakes, the elevation of all adjacent shoreline are generally easier to identify because of the TanDEM-X heights are measured. The elevation of a lake is fixed using the ancillary image data sets (the amplitude image – AMP and the lowest 20% of the measured shoreline elevations. This minimum amplitude image – AM2). Because of the lack of calculation allows for the best elevation to be set where a lake is radar signal return, waterbodies have a distinctive black surrounded by surface features (such as a forest) as only the appearance, especially in the AM2 image. This consistency shoreline elevations that are most likely to be unobstructed are allows for a highly-automatic approach to the detection and selected to set the lake elevation. River elevations are set in a delineation of water bodies. similar manner as lakes, with the exception that rivers must flow downhill monotonically in 50cm steps from their point of first classification. Some operator interaction in the selection of river heights is required, as rivers generally encounter varying slopes throughout their courses. Figure 6: A river’s course is easily identified using the AM2 amplitude image Figure 7: An unedited river (left) and the edited result (right) This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1153 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany ACKNOWLEGEMENTS In order to ensure the hydrological consistency of the All Figures © DLR e.V. 2015 and/or © Airbus DS Geo GmbH WorldDEM dataset, a final automatic step is taken during the setting of waterbody elevations. Any shoreline pixel that would (for any reason) remain lower in elevation than the adjacent waterbody, is automatically raised 50cm above the surface of REFERENCES the waterbody. This ensures that all waterbodies are contained for hydrological modeling: water will not flow out of the edited Bachmann, M. et. al. 2013. Acquisition Status and DEM hydrology in an unexpected manner. Performance. TerraSAR-X/TanDEM-X Science Team Meeting, Oberpfaffenhofen, Germany. June 10 – 14. 4. QUALITY CONTROL PROCESSES FOR WORLDDEM PRODUCTION Davies, H. 1954. The reflection of electromagnetic waves from a rough surface. Proceedings of the IRE, Volume 101, Issue 7, Before the delivery of WorldDEM products to clients or the pp 209 – 214. internal product library, QC checks are performed on every Geocell. These QC checks ensure that all WorldDEM data is DLR. 2013. TanDEM-X Ground Segment: DEM Products produced in a consistent manner. The QC process is divided Specification Document. Doc.: TD-GS-PS-0021, Issue 3. into two components: automatic tools that detect if each tandemx-science.dlr.de/pdfs/TD-GS-PS-0021_DEM-Product- individual Geocell is consistently edited unto itself and its Specification_v3.0.pdf neighbors and a visual review of the edited data to ensure that the editing is consistent across the entirety of the WorldDEM ESRI. 2007. How Inverse Distance Weighted (IDW) dataset. Errors in the WorldDEM product are then marked interpolation works. interactively in the Demes software for review and correction. webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=Ho A final QC step ensures that the complete WorldDEM package w_Inverse_Distance_Weighted_%28IDW%29_interpolation_w is correctly formatted and compiled and ready for delivery to orks customers or the internal product library. Farr, T. et. al. 2007. The Shuttle Radar Topography Mission. 5. CONCLUSION Reviews of Geophysics, Volume 45, Issue 2, pp 1 – 33 The WorldDEM product, after terrain and hydrological editing, Grant, C., Yaplee, B., 1957. Back Scattering from Water and is a consumer-ready Digital Surface Model that is available on a Land at Centimeter and Millimeter Wavelengths. Proceedings global scale, with a consistent “look and feel” everywhere. of the IRE, Volume 45, Issue 7, pp 976 – 982. WorldDEM follows-on from the great success of the original SRTM dataset by providing a higher resolution, greater vertical Grohman, G., Kroenung, G., Strebeck, J., 2006. Filling SRTM accuracy and surface information that is up to twelve years Voids: The Delta Surface Fill Method. Photogrammetric more current than SRTM. Engineering & Remote Sensing, Volume 72, Number 3, pp 213 – 216. Slater, J., Garvey, G., 2006. The SRTM Data “Finishing” Process and Products. Photogrammetric Engineering & Remote Sensing, Volume 72, Number 3, pp 237 – 247. This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1154 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Unpaywall

APPLYING TERRAIN AND HYDROLOGICAL EDITING TO TANDEM-X DATA TO CREATE A CONSUMER-READY WORLDDEM PRODUCT

Collins, J.; Riegler, G.; Schrader, H.; Tinz, M.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – Apr 30, 2015
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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany APPLYING TERRAIN AND HYDROLOGICAL EDITING TO TANDEM-X DATA TO CREATE A CONSUMER-READY WORLDDEM PRODUCT J. Collins, Dr. G. Riegler, H. Schrader, M. Tinz Airbus Defence and Space, Geo-Intelligence ([email protected]) - Claude-Dornier-Straße, 88090 Immenstaad, Germany KEY WORDS: WorldDEM, TanDEM-X, TerraSAR-X, SAR, DSM, elevation model ABSTRACT: The Geo-intelligence division of Airbus Defence and Space and the German Aerospace Center (DLR) have partnered to produce the first fully global, high-accuracy Digital Surface Model (DSM) using SAR data from the twin satellite constellation: TerraSAR-X and TanDEM-X. The DLR is responsible for the processing and distribution of the TanDEM-X elevation model for the world’s scientific community, while Airbus DS is responsible for the commercial production and distribution of the data, under the brand name WorldDEM™. For the provision of a consumer-ready product, Airbus DS undertakes several steps to reduce the effect of radar-specific artifacts in the WorldDEM data. These artifacts can be divided into two categories: terrain and hydrological. Airbus DS has developed proprietary software and processes to detect and correct these artifacts in the most efficient manner. Some processes are fully- automatic, while others require manual or semi-automatic control by operators. 1. CREATING A CONSUMER-READY WORLDDEM The acquisition strategies described above were undertaken to PRODUCT ensure a maximum coverage of the earth’s surface, with a maximum vertical accuracy. Preliminary results indicate that the 1.1 The TanDEM-X Mission and WorldDEM Product strategy appears to have been successful, with a minimum of areas with no data (voids) and a corresponding high accuracy. Airbus Defence and Space and the German Aerospace Center (Bachmann 2013) However, it was always anticipated that there (DLR) have partnered to produce the first truly global, high- would be certain areas of the earth that would not interact well accuracy Digital Surface Model (DSM) using the with X-band radar signals and would therefore subject to some interferometric data from the twin satellite constellation: invalid and or inaccurate data being collected and processed. TerraSAR-X and TanDEM-X. The DLR is responsible for the The first surface that is highly susceptible to invalid height processing and distribution of the TanDEM-X elevation model elevations in the DSM is waterbodies. Early-on during research to the world’s scientific community, while Airbus DS is on radar signal propagation, it was known that smoother responsible for the commercial production and distribution of surfaces, such as water, can be highly reflective to short-band the data, under the brand name WorldDEM™. radar waves (Davies 1954 and Grant, Yaplee 1957) As radar later became a tool for mapping with the start of widespread X- 1.2 Radar Effects in Processed SAR Elevation Data band SAR data collections (SRTM and commercial airborne radar) it became well understood that the relatively short The WorldDEM DSM is derived from the phase information wavelengths (~3cm) of X-band radar are frequently reflected by from two Synthetic Aperture Radar (SAR) signals using water surfaces, away from the receiving antennas (Farr et.al. interferometric processing of X-band radar signals. The height 2007). The almost complete reflection of the radar signals by information is obtained for any point on the earth’s surface by water surfaces means that the receiving antennas have little or calculating the phase difference received by the two receiving no information about the surface heights of water. When the antennas on the mission’s two satellites (TerraSAR-X or SAR data comes to be processed, there is no interferometric TanDEM-X). In order to accurately measure surface heights baseline for the processor to set an elevation over water: from space, it is essential that the orbits (i.e. height from the therefore the heights calculated for most water surfaces appear ground) of the satellites be precisely measured. In addition, the to be nothing more than random noise in the resulting DSM. In separation of the two receiving antennas must also be known areas of more widespread water, the SAR processors are usually extremely precisely. Fortunately, the precision of the two designed to detect the lack of signal coherence and assume that satellites’ orbits is very well understood, as is the separation an area is water. In these larger areas, no surface elevation is between them in flight. (DLR 2013) calculated and the elevations are simply set using the “no data” The TanDEM-X mission recorded height information for the flag value of -32767m. whole earth’s surface at least two times. (DLR 2013) In more While there are clearly difficulties with X-band radar SAR data “challenging” areas (steep, sandy or heavily-forested areas) up over water, it should be clear that this is not an insoluble to four acquisitions were made, in order to improve the resulting problem. While the elevations calculated over the surface of surface model. These additional acquisitions took advantage of water are not accurate, the elevations calculated on the surfaces different acquisition geometries: either looking at the earth’s immediately adjacent to water (shorelines) are in fact coherent, surface from another orbital direction, or by directly adjusting accurate and consistent. This means that while the elevation of the angle of signal acquisition, with reference to the earth’s the water in a lake might not be correct in the TanDEM-X data, surface. These techniques allowed the satellites to “see” more the elevation of the shoreline of the lake can be assumed to be surfaces in challenging terrain and enabled the improved correct, within the relative accuracy of the overall product. This acquisition of surfaces that were more likely to deflect radar important distinction between incoherent water and coherent waves away from the receiving antennas on the satellites. This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1149 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany shorelines shall become clearer later, when this information can be used to edit the elevations of water in the WorldDEM data. During SAR processing, surfaces other than water can be subject to the same signal reflection challenges as water. These include large areas of sand (deserts, beaches) dry and salt lakes, continuous areas of flat and smooth rock and finally ice and snow (fields and or ice-sheets). In the processed TanDEM-X data, many of these surfaces can exhibit some of the characteristics of water, such as extreme noise and/or voids in the resulting DSM, due to radar signal reflection. As noted above, the TanDEM-X mission planners worked hard to overcome the limitations posed by these smooth surfaces by customizing the acquisition process, where these features are widespread. However, the fact remains that some of these smooth features will not be accurately represented in the resulting TanDEM-X surface model. Figure 2: Elevation spikes on a steep mountain slope A third type of elevation error occurs when the SAR processor has sufficient data to calculate the elevation over an area, but 1.4 Bespoke Production Software for the Production of the uncertainty of the interferometric principle means that the processor generates a consistent surface, which does not have a WorldDEM Products correct elevation. This problem can occur when the processor is Airbus Defence and Space Geo-intelligence division provides unable to accurately calculate the number of height offsets from WorldDEM data to clients in three forms: WorldDEM , the reference surface. This can lead to areas being represented core WorldDEM and WorldDEM DTM. WorldDEM is the as either too high, or too low in the resulting DSM. Islands, core unedited version of the WorldDEM. WorldDEM DTM is particularly in lakes and rivers, are most susceptible to this subject to additional processing, which removes surface features problem. such as buildings and vegetation, to leave the elevations of the Very steep areas can also provide a challenge to the TanDEM-X terrain in the model: however, these two additional products are SAR processor. Steep slopes that face directly into the radar beyond the scope of this paper. during acquisition are generally well-portrayed in the DSM. The WorldDEM product is subject to terrain correction and However, steep slopes that faced away from the acquisition (and hydrological editing, to provide clients with the most reasonable were not acquired from a different angle in a further compromise of data quality, availability and price. In order to acquisition) may be poorly represented in the DSM. This occurs produce WorldDEM over large areas of the globe, a number of as the SAR processor is unable to calculate an accurate surface, terrain and hydrological editing processes were developed by because the elevations change so rapidly in a short distance. It is Airbus DS. In the initial stages, these processes were developed possible for some of these steep areas to be completely void in using commercial mapping and GIS software. However, it was the resulting DSM. always envisioned that the data volumes to be produced would A final challenge that occurs in the TanDEM-X DSM are voids. exceed the reasonable capacities of commercial software. So During the course of more than three years of acquisitions, care Airbus DS Geo entered into a cooperation with a company that was taken to acquire every square kilometer of the earth’s has significant experience with three-dimensional relief surface. The reality is that due to any number of operational portrayal and data manipulation, in order to produce a software factors, some areas of the earth’s surface were never acquired. package to efficiently edit large volumes of WorldDEM data. These areas are portrayed as void in the resulting DSM and set The resulting software package, called Demes, is designed to to the null value of -32,787m, so that they can be easily automate as much of the terrain and hydrological editing as identified. possible, while still leaving the flexibility of human interaction with the data, when the automatic processes to not provide the 1.3 Examples of Radar Effects in TanDEM-X Data intended results. The Demes editing software works on a Shown below are some examples of X-band radar effects, that standard PC workstation, and allows production staff to view, interact with and edit data directly. Demes server software are apparent in the TanDEM-X data before editing is applied. In manages the data workflow process: ensuring that data flows all images, the vertical exaggeration of the shaded relief images is 1x. efficiently and consistently through the production stream, from initial ingest, through to final Quality Control (QC) and client delivery. 1.5 Editing Rules and Editing Guidance In order to ensure consistency across the full edited WorldDEM dataset, a series of editing rules has been developed. These rules guide operators in their daily work to ensure that the correct terrain and hydrological features are being edited. The rules contain information about the identification and size of features to be edited and what software tools are acceptable for editing individual features. Because the earth’s surface is extremely variable from equator to the poles, further guidance is published to ensure that all operators are aware of special or single-instance surface Figure 1: Characteristic roughness of the unedited WorldDEM features. For example, a mangrove area consists of significant DSM over a lake This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1150 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany vegetation that stands in a continuously flooded part of the clients generally prefer to have some DSM information, rather ocean shoreline. This could cause confusion among different than none, when WorldDEM is unable to provide any height operators, with one classifying mangroves as ocean, while information. For the benefit of WorldDEM users, areas of the another classifies them as land. When such uncertain features DSM that are interpolated or infilled with another DSM source are found in the data, a decision is made on how to treat them. are identified in data masks that are delivered along-side of the The decision and detailed technical guidance is posted on an WorldDEM elevation dataset. internal Wiki, so that all operators have access to the same For the filling of larger voids, the Delta Surface Fill (DSF) information. method of void filling is applied. First developed by the National Geo-Spatial Intelligence Agency (NGA) to infill voids 2. TERRAIN EDITING in SRTM data, the Delta Surface method of infilling has the advantage of using the most accurate WorldDEM data at the 2.1 Spike and Well Removal edge of a void to seed the elevations of the less accurate fill source (Grohman 2006). Therefore a fill source that might have Spikes and wells are among the simplest of artefacts to identify an overall acceptable portrayal of a surface feature, but might and remove from the WorldDEM dataset. These are single pixel not be as accurate as WorldDEM data, will be manipulated to elevation errors, where the elevation of a point on the surface conform to the more accurate WorldDEM data at the edges of model is significantly different from the elevations of its the void. neighbors. A spike is a positive elevation difference, while a The Demes software allows the operator to use the DSF method well is a negative elevation difference to neighboring pixel. of filling, either on a single void, multiple voids, or even every These spikes and wells are identified using a threshold large void in a single Geocell. This flexibility allows the difference elevation and are removed using a simple operator to efficiently fill a number of similar voids at the same interpolation using the eight neighboring pixel elevations. The time, while maintaining the flexibility to manually handle a Demes software identifies and corrects spikes and wells in a single more complex void, which might require perhaps a single step. A QC tool is available to identify any spikes and different filling source than the other voids in the Geocell. wells that might have been missed by the tool, especially in steep terrain, or along Geocell edges. These spikes or wells may 2.3 Identification and Correction of Systematic and require individual manual editing to be completely removed. Random Errors 2.2 Identification and Infilling of Voids While voids are generally easy to identify and treat in the WorldDEM data, there are two further categories of surface Another simple terrain artefact to identify and remove is areas elevation artefacts that require additional editing to create a that are void in the DSM. These voids are areas where either the consumer-ready product: random and systematic errors. data was not acquired, or the SAR processor was unable to calculate a valid elevation. Voids are identified in the data as 2.3.1 Identification of systematic and random errors elevations with the null data value of -32,767m. The DLR provides additional data masks as part of the TanDEM-X data package. These masks are generated during 2.2.1 Small voids the SAR processing and subsequent mosaicking of the data into The production strategy with void data is to interpolate small a final DSM product. These masks are central to the voids, while larger voids are infilled (wherever possible) with identification of random and/or systematic errors in the DSM an alternate elevation data source. The definition of a small data. void, is any void that is between one and sixteen contiguous The Height Error Mask (HEM) represents the height error of pixels of void data. Any void larger than sixteen contiguous any pixel in the form of a standard deviation and is derived pixels is considered to be a large void. All calculations of void during the SAR processing from the interferometric coherence sized consider the eight-way connection of pixels (edge- of every pixel measurement in the dataset. adjacent and corner-adjacent). The information derived from the HEM is used to identify areas Small voids are edited in Demes using the Inverse Distance in the DSM that are likely invalid, because the SAR processor Weighted (IDW) method of interpolation. IDW is based on the only had weak or limited information about those areas. In assumption that things that are close to one another are more addition, the height information contained in the pixels with alike than those that are farther apart from each other (ESRI poor values in the HEM are likely somewhat inconsistent with 2007). Therefore any pixel that does not have a measurement neighboring pixels (often visible as a certain “rough” texture in should be interpolated (and its height calculated during the DSM). The assumption is that in any DSM, neighboring interpolation) in reference to closer known points than to known elevation measurements should be somewhat consistent with points that are further away. The IDW process uses a standard each other. This combination of poor HEM values and a low weighting based on the distance to known points, providing a consistency with neighboring pixels, provides a good indication more plausible interpolated height than a simple linear of pixels/areas that likely have a high likelihood of random interpolation would. errors. Surfaces that are frequently subject to high random error include tropical forests and to a lesser extent, highly built-up 2.2.2 Large voids urban areas. The treatment of larger voids is somewhat different. While it is A second mask provided by the DLR, the Consistency Mask also possible to interpolate larger voids, their larger extent (COM) indicates DSM pixels that have inconsistencies between means that the likelihood of the interpolation providing an the different acquisitions (known as a Phase Unwrapping error accurate portrayal of the earth’s surface diminishes greatly as or a Cycle Shift). As noted previously, all areas of the earth’s the void area becomes wider or longer. In such cases, the void surface were collected at least twice during the TanDEM-X area is infilled with an alternate DSM data source, such as mission. A limited instance of the data collected have different SRTM or ASTER GDEM. While these alternate datasets might elevations processed from the two (or more). not have the same accuracy or temporal information as the surrounding WorldDEM data, it is understood that commercial This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1151 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany Figure 4: The RLM (left) indicating an area of forest where elevations are somewhat less reliable 2.5 Editing Terrain Using Demes Figure 3: Example of a Phase Unwrapping error caused by the Before the terrain editing of artefacts identified in the RLM can harvesting of trees in a forest between TanDEM-X acquisitions begin, one more mask transformation is required. Because the RLM identifies each and every pixel that might have a random Pixels that are identified as having two (or even more) or systematic error, a further simplification is required. elevations between acquisitions are identified in the COM. In Generally a single pixel that displays the low to medium the TanDEM-X SAR processing, only a single final height can likelihood of error is not a major concern. Similarly, two or be derived. The processor uses a number of tests to determine three pixels next to each other, showing only a slight likelihood the best-fitting elevation, (such as number of measurements at of an error need not be edited. The goal of this simplification is the same height, pixel coherence from each acquisition, etc…) to identify larger areas of concern, where higher error values are if there is a conflict between acquisitions. Whatever final height present. This is done by creating a new mask: the Feature Mask is derived, the fact that there was an inconsistency between (FTM). In creating the FTM, smaller less error-prone pixels are acquisitions is noted in the COM mask. This allows the Demes removed, while larger error-prone areas have their edges software to identify areas with potential elevation regularized, in order to provide a more convenient edge for inconsistencies and repair them during the terrain editing step. eventual Delta Surface Filling. In addition, areas that are likely to be cycle shifts, as identified in the COM, are given a special 2.4 Creation of the Reliability Mask classification (“offset”) in the FTM. This allows the operator to better understand the type of error that the FTM is identifying. The potential DSM errors identified in the HEM and COM Because there is the possibility that some areas that are masks are somewhat different in their source, but in the end identified in the RLM as random errors, are in fact just the noise they both need to be treated during the terrain editing process. associated with the portrayal of water in the DSM, it is In order to make the terrain editing process as efficient as necessary to screen-out potential water areas from the resulting possible, the information from the HEM and COM masks is FTM. Water bodies will be identified, classified and edited in a combined into a single mask, internal to the Demes software, separate step, outlined later. Editing water during the terrain which clearly identifies areas that require attention and/or editing step is not only inefficient, but there is a chance that repair. This mask is more than a simple combination of the infilling large areas of water with an external DSM source HEM and COM data. Rather, it uses probability values from the might adversely affect the shoreline elevations in the HEM and the DSM in an attempt to determine what is actually WorldDEM. Areas that are identified as possibly being water an error in the DSM and what is likely legitimate noise in the are flagged in the FTM as “water candidates”. These areas will DSM, perhaps caused by the legitimate roughness of a surface, be ignored during the automatic terrain editing steps described such as the top of trees in a forest. next. The option does remain for an operator to manually The amalgamation of COM, HEM and DSM error information override the water candidate class, if it has been incorrectly results in the Reliability Mask (RLM). This is an internal applied in the FTM. Demes mask, which indicates the likelihood that each pixel in a In a final mask preparation step, the size of random errors is DSM Geocell is reliable or not reliable. It further separates the classified in the transition from RLM to FTM. This is because unreliable pixels into ones that are likely unreliable because of random errors of different extents will be treated differently random uncertainty in the DSM (noise) and pixels that are during the editing of the DSM in Demes. Small artefacts are subject to offsets in the DSM due to differences between heights those between 2 and 16 neighboring pixels. Medium artefacts during acquisitions. The RLM does not discriminate between are those between 16 and 46 pixels. Any artefact 47 pixels and the size of erroneous data patches. Even areas of a single pixel larger, is considered to be a Large artefact. (that is considered erroneous) are flagged in the RLM. This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1152 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany The Demes software contains a number of tools to allow for the automatic, semi-automatic and manual delineation of waterbodies. The most important of these tools is called “Perception”. The Perception tool is a type of trained classification tool: the operator finds a small area in a Geocell that is generally representative of the image tone for the full Geocell. The operator classifies this small subset area, by adjusting the sensitivity of the Perception tool to the image tone in the subset. When a plausible result is achieved in distinguishing land areas from water areas in the subset, the same Perception settings are applied to the whole Geocell, thereby identifying waterbodies throughout the whole Geocell Figure 5: The FTM (left) demonstrates how the RLM is simultaneously. Where a Geocell has areas that display widely generalized to assist editing divergent image tones, perhaps due to different data acquisition timings in the same Geocell, the Perception tool can be run on a During editing, all Small artefacts are voided and interpolated. subset of the Geocell only, to improve the local results of the All Medium artefacts are smoothed using a Gaussian smoothing waterbody identification process. After the Perception tool is approach. Large artefacts are voided and filled, using the DSF used, a manual clean-up of some shorelines is usually required process, as described previously. Any area identified as an for some waterbodies. Demes provides the operator with a Offset in the FTM is also a candidate for filling using the DSF variety of drawing and selection tools to improve the tool. However it is recommended that an operator visually delineation of shorelines. identify Offset areas, to ensure that the filling solution is actually an improvement over the existing DSM data. There is 3.2 Waterbody Classification the possibility that a portion of an area that is identified as an offset is actually accurate DSM data and infilling this area Three different types of waterbody class are used in the would only reduce the quality of the WorldDEM. production of WorldDEM data. These three classes are applied once the operator has ensured that the shorelines of the 3. HYDROLOGICAL EDITING automatically detected waterbodies are correct. The three classifications of waterbodies are: Ocean, Lake and River. The In order to remove the characteristic noise that is present in Ocean class is set for any saline waterbody whose geoidal many water bodies in the TanDEM-X data, a three-step process reference elevation is 0m. The Lake classification is set for any must be undertaken. These three steps are: the identification and fresh-waterbody that does not normally contain any flow. The delineation of all waterbodies, their division into the correct River classification is set for drains that have a monotonic flow. class of waterbody and finally, the application of a “flattening” algorithm to set the water body to a plausible elevation. 3.3 Setting the Elevation of Classified Waterbodies 3.1 Identification and Delineation of Waterbodies Once classified, the elevations of the waterbodies are set in the Demes software. Oceans are universally set to 0m. In order to One advantage of editing water over terrain is that waterbodies set the elevation of lakes, the elevation of all adjacent shoreline are generally easier to identify because of the TanDEM-X heights are measured. The elevation of a lake is fixed using the ancillary image data sets (the amplitude image – AMP and the lowest 20% of the measured shoreline elevations. This minimum amplitude image – AM2). Because of the lack of calculation allows for the best elevation to be set where a lake is radar signal return, waterbodies have a distinctive black surrounded by surface features (such as a forest) as only the appearance, especially in the AM2 image. This consistency shoreline elevations that are most likely to be unobstructed are allows for a highly-automatic approach to the detection and selected to set the lake elevation. River elevations are set in a delineation of water bodies. similar manner as lakes, with the exception that rivers must flow downhill monotonically in 50cm steps from their point of first classification. Some operator interaction in the selection of river heights is required, as rivers generally encounter varying slopes throughout their courses. Figure 6: A river’s course is easily identified using the AM2 amplitude image Figure 7: An unedited river (left) and the edited result (right) This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1153 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany ACKNOWLEGEMENTS In order to ensure the hydrological consistency of the All Figures © DLR e.V. 2015 and/or © Airbus DS Geo GmbH WorldDEM dataset, a final automatic step is taken during the setting of waterbody elevations. Any shoreline pixel that would (for any reason) remain lower in elevation than the adjacent waterbody, is automatically raised 50cm above the surface of REFERENCES the waterbody. This ensures that all waterbodies are contained for hydrological modeling: water will not flow out of the edited Bachmann, M. et. al. 2013. Acquisition Status and DEM hydrology in an unexpected manner. Performance. TerraSAR-X/TanDEM-X Science Team Meeting, Oberpfaffenhofen, Germany. June 10 – 14. 4. QUALITY CONTROL PROCESSES FOR WORLDDEM PRODUCTION Davies, H. 1954. The reflection of electromagnetic waves from a rough surface. Proceedings of the IRE, Volume 101, Issue 7, Before the delivery of WorldDEM products to clients or the pp 209 – 214. internal product library, QC checks are performed on every Geocell. These QC checks ensure that all WorldDEM data is DLR. 2013. TanDEM-X Ground Segment: DEM Products produced in a consistent manner. The QC process is divided Specification Document. Doc.: TD-GS-PS-0021, Issue 3. into two components: automatic tools that detect if each tandemx-science.dlr.de/pdfs/TD-GS-PS-0021_DEM-Product- individual Geocell is consistently edited unto itself and its Specification_v3.0.pdf neighbors and a visual review of the edited data to ensure that the editing is consistent across the entirety of the WorldDEM ESRI. 2007. How Inverse Distance Weighted (IDW) dataset. Errors in the WorldDEM product are then marked interpolation works. interactively in the Demes software for review and correction. webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=Ho A final QC step ensures that the complete WorldDEM package w_Inverse_Distance_Weighted_%28IDW%29_interpolation_w is correctly formatted and compiled and ready for delivery to orks customers or the internal product library. Farr, T. et. al. 2007. The Shuttle Radar Topography Mission. 5. CONCLUSION Reviews of Geophysics, Volume 45, Issue 2, pp 1 – 33 The WorldDEM product, after terrain and hydrological editing, Grant, C., Yaplee, B., 1957. Back Scattering from Water and is a consumer-ready Digital Surface Model that is available on a Land at Centimeter and Millimeter Wavelengths. Proceedings global scale, with a consistent “look and feel” everywhere. of the IRE, Volume 45, Issue 7, pp 976 – 982. WorldDEM follows-on from the great success of the original SRTM dataset by providing a higher resolution, greater vertical Grohman, G., Kroenung, G., Strebeck, J., 2006. Filling SRTM accuracy and surface information that is up to twelve years Voids: The Delta Surface Fill Method. Photogrammetric more current than SRTM. Engineering & Remote Sensing, Volume 72, Number 3, pp 213 – 216. Slater, J., Garvey, G., 2006. The SRTM Data “Finishing” Process and Products. Photogrammetric Engineering & Remote Sensing, Volume 72, Number 3, pp 237 – 247. This contribution has been peer-reviewed. doi:10.5194/isprsarchives-XL-7-W3-1149-2015 1154

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