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International Cartographic Association, Commission on Cartographic Heritage into the Digital Proceedings 12th ICA Conference Digital Approaches to Cartographic Heritage, Venice, 26-28 April 2017

Editor Evangelos Livieratos AUTH CartoGeoLab, 2017, ISSN 2459-3893

Aristotle University of Thessaloniki

[339] Laboratory of Cartography & Geographical Analysis

Gábor Molnár1, Gábor Timár2, Előd Biszak3 The advantage of publishing intermediate products of historical air photos Summary Aerial photography is a unique type of spatial datasets completing or continuing time series of historical to recent maps representing the actual state of Earth’s surface. To fully take advantage of time series of historical maps, these maps should be georeferenced layers in Geographical Information System software or Web Mapping Services. The aerial photographs to fit geometrically into these systems should be orthorectified. Orthorectification is the process, how a raw aerial image is transformed (resampled) into a georeferenced image matching geometrically to georeferenced maps. In the first step, besides the photographic camera data (interior orientation), the position (coordinates) and attitude (angles) of camera orientation should be calculated. In the case of historical aerial photography these exterior orientation parameters are usually unknown, and are calculated using 10-15 features (Ground Control Points) identified both on aerial photographs and historical maps. In the second step the theory behind orthorectification (a pure spatial geometrical operation) is applied to project image pixels on Earth’s surface. To achieve this, a Digital Elevation Model (DEM) – a grid representing the topographic heights – is used. In this content, intermediate product refers to the scanned aerial photographs attached with the metadata calculated after achieving the first step, saved in ‘GeoTiff’ format. The advantage of providing intermediate product to end-users is making them able to generate orthophotos using their own Digital Elevation Model. The overall accuracy of orthorectified air photos is limited by the accuracy of the Digital Elevation Model used, so an end user having an accurate surface model of the region is able to generate high accuracy orthophotos automatically. We demonstrate the practicability of the method on aerial photographs shot by the Royal Hungarian Air Force carried out a recon mission, photographing the metropolitan area of Budapest after the first Allied bombing raid at 3 April, 1944. Introduction The stormy history of the Hungarian capital in the mid-20th century provides possibility to build geo-databases (Timár & Biszak, 2007; Biszak &Timár, 2007) connected to the most tragic events of the century: the WWII (Allied bombings in 1944 and Russian siege in 1944/45). During the WWII, Budapest was partially destroyed. All Danube bridges were intentionally exploded and at the main battle events and street fights of the siege ravaged important parts of the main residential area. The previous bombings affected heavily the industrial plants. Data After the first Allied bombing raid at 3 April, 1944, the Royal Hungarian Air Force carried out a recon mission, photographing the metropolitan area of Budapest, which was slightly larger than the administrative territory of the capital that time. This is the last available database of the pre-war Budapest, however the bombing damages at southern industrial and transport area is clearly visible. The higher resolution images, taken from 800-1200 m altitude do not cover the whole city (the missing ones were probably taken but later lost), so part of the missed area was covered by an earlier and lower resolution (2000-2500 m altitude) photo mission results.

1MTA-ELTE Geological, Geophysical and Space Science Research Group, Hungarian Academy of Sciences at Eötvös University, Budapest 2 Department of Geophyisics and Spaces Sciences, Eötvös University, Budapest 3 Arcanum Database Ltd, Budapest





These aerial photographs were scanned and stored digitally. However these digitalized photos are not suitable for publication on a Web Map Service without being georeferenced. There are several methods to georeference aerial photos; however the most accurate method is the orthorectification, adjusting for topographic relief, lens distortion, and camera tilt (Fig 1.).

Figure 1. The orthophoto generated from an aerial photograph of NW suburb of Budapest, partly covering Buda Hills area. The photograph was taken after the first Allied bombing raid at 3 April, 1944, during a recon mission carried out by the Royal Hungarian Air Force. The aerial photographs were systematically orthorectified and the result is a georeferenced mosaic. This dataset is web-published, and available online as a georeferenced layer.4 Methods In the orthorectification process, the projective geometry equations are used to resample the raw image into an orthorectified one. These equations require the exterior orientation parameters of the camera at

4 (http://mapire.eu/en/map/bp1944).





the moment of snapping: The position of the optical center (practically the camera position) which is defined by three Cartesian coordinates (Map Eastings, Northings and Height) and camera attitude which is defined by three angles (similar to the Tait-Bryan convention, consisting of pitch, yaw and roll). As usually these six parameters are unknown for archive aerial photos, 10-15 Ground Control Points (GCPs) were identified for each photo to calculate these parameters. GCPs are usually road intersections, building corners, or other features unambiguously identifiable both on the aerial photograph and on a georeferenced map. Each GCP has 5 data: the image coordinates (column, row) of the feature, and the map coordinates (Easting and Northing) with their elevation readout of a DEM or visual interpolation of contour lines of the adjacent topographic map. From these point data, knowing the camera model, exterior orientation parameters are calculated by digital photogrammetric software using a least squares method. With the advent of high-resolution satellite imaginary more complicated acquisition techniques were introduced, and for these images the projective geometry equations were not valid any more. On the one hand, satellite image providers knowing the imaging geometry were not able to orthorectify the images, because of the lack of accurate Ground Control Points and Digital Elevation Model, as end-users were willing to transfer GCPs, but refused to transfer DEM data. On the other hand, end-users were neither able to orthorectify the satellite images, because they did not have the proper equations and coefficients, as satellite imagery providers were against publishing their sensors’ internal structure. To solve this deadlock a Rational Polynomial Camera (RPC) model was introduced. These equations resemble to the rigorous projective geometry equations, however can handle more complex imaging geometry. In practice, applying this model, end-users supplied reasonable number of GCPs to image vendors, and got back satellite images with RPC coefficients, and finally end-users could orthorectify these images by means of their own DEM (Hu et al, 2004). This resulted in a spread of RPC technique, and besides the commercial software, opens source GIS software become capable of orthorectifying images, and RPC model become a quasi-standard (Dial and Grodecki, 2005). It is possible to calculate RPC coefficients for any satellite or aerial image, without knowing anything about the imaging geometry of the sensor, however this requires almost 100 GCP’s (comparable to the number of 92 coefficient of RPC model). In the case of aerial photographs we might be certain about the imaging geometry, and this enables us to calculate RPC coefficients for an aerial photograph, using the six exterior orientation parameters, and additionally we need to know the map projection of the GCPs’ we used. As the RPC model equations originate from the rigorous projection equations, finally we have to calculate only nine coefficients (linear members), and all other values of the 92 coefficients are zeros. Results The intermediate products are the scanned (digitized) aerial photographs with RPC coefficients. These intermediate products are stored in ‘geotiff’ format. These ‘geotiff’ files are not georeferenced, looking exactly like the original scanned aerial photographs. The ‘geotiff’ format is suitable for storing geographical metadata information attached the image, so the 92 RPC model coefficients. Open source software can be used to convert arbitrary file format of scanned photographs to ‘geotiff’ format and append the calculated RPC coefficient to it: gdal_translate. The status (presence and actual values) of these appended coefficients can be checked with gdalinfo. Orthorectification – by means of end-user’s DEM – can be simply performed with gdal_warp. Conclusions and Discussion Publishing intermediate products let end-users orthorectify archive aerial photography by themselves, by means of their own DEM. Published orthorectified images sometimes miss the nicety stored in the raw scans, so end-users can set the pixel resolution or interpolation method by themselves, to preserve the original detailed features.





Even, if the aerial photo provider does not have an accurate DEM of the project area (only georeferenced map or geodetic survey data for GCPs) it can provide an added value product to end-users. Acknowledgement The original aerial photo material was kindly provided by the Map Archive of the Institute and Museum of the Military History of MoD, Budapest and also published in the Hungarian historical photo web-portal ‘Fortepan’ (www.fortepan.hu). References Biszak, S., Timár, G., 2007. Historical street gazetteer of Budapest, with geo-referred maps. DVD issue, Arcanum, Budapest.

Dial, G., Grodecki, J., 2005. RPC replacement camera models. ASPRS 2005 Annual Conference Geospatial Goes Global: From Your Neighborhood to the Whole Planet, March 7-11, 2005 Baltimore, Maryland

Hu, Y., Tao V., Croitoru, A., 2004. Understanding the rational functional model: methdods and applications. ISPRS Archives, Volume 35, Part B4, 663-668.

Warmerdam, F.: RPCs in GeoTIFF. http://geotiff.maptools.org/rpc_prop.html (2017.03.15.)

Timár, G., Biszak, S., 2007. Georeference of the high-scale topographic maps of Budapest prior to 1938 (in Hungarian with English summary). Geodézia és Kartográfia 59(8-9): 47-51.

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