Digital Terrain Models for use by the Centre for Black Sea Studies
Niels Chr. Nielsen, SDU-Esbjerg: [email protected], alternatively Kallesbjergvej 28i, 6720 Fanoe:
[email protected], phone: +45 7612 1216.
Background
A digital terrain model (DTM) can be defined as ”a numerical model of a terrain surface, which
along with a mathematical method of interpolation makes it possible to calculate the (surface)
elevation of any point within the domain of the model" (Jacobi in Balstrøm 1999, 61), or simply
"Any digital representation of the continuous variation of relief over space" (Burrough 1986).
DTM's are being increasingly used in Geographical Information Systems (GIS), for visualisation of
landscapes as well as quantitative calculations of erosion risk, drainage conditions and the like.
Great potential for the use of DTM's have also been identified within the fields of archaeology and
history - for instance in reconstruction of landscapes (land use and/or land cover) of earlier times or
as a tool for field surveys, see van Leusen (1993).
Traditionally, the data on which DTMs are based originate from digitisations of existing maps or
stereographic analysis of aerial photography pairs. Both methods are time consuming and thus
expensive, till now making it difficult to obtain DTMs for larger areas. However, during the last
few years a new and promising source of relatively inexpensive terrain elevation data have
appeared, even with a nearly global coverage and a spatial resolution as fine as 30 meters (Rabus et
al. 2003). These are the data from the InSAR radar used on NASA's space shuttle mission SRTM,
flown in February 2000.1 Following substantial (interferometric) calculations on the enormous
amounts of data that was brought back from the 11 days in orbit, carried out at the Jet Propulsion
Laboratory (JPL), release of geo-referenced data for tests and scientific evaluation began in
November 2003, initially for evaluation and scientific purposes. These data cover the land masses
of the Earth from 60 deg. North to 56 deg. South.
In a pilot study made at SDU-Esbjerg during spring 2004, it was found that the above mentioned
”public domain” data i hgt-format2 with relative ease could be used as supplementary data in the
creation of a coherent (land and sea floor) elevation model for Denmark (Nielsen og Ejstrud, in
preparation). Later on, in September 2004, the same type of data were used for a terrain model of
Cyprus, on which the course of ancient roads could be modelled (Ejstrud in press).
The hgt-format used in the above mentioned studies, did however turn out to be an intermediate
product in the creation of global ”Digital Terrain Elevation Data” (DTED). These data are compiled
by the American National Geospatial-Intelligence Agency (NGA), and released after a quality
check - in a format different from the -hgt-data from JPL.3 The main differences from the .hgt data
are:
o points at sea surface have been set to zero value, thus confusion with low lying areas are
avoided and the user does not have to delineate land from sea;
o lakes have been identified and given a uniform value across their surface;
o gaps (holes) and improbably large or small local values have been filled or smoothed out;
o data have undergone a quality check;
As with the .hgt data, the DTED product gives heights for each 3rd arc second in the North-South
and East-West directions. At 45 degrees North this corresponds to about 93 meters North-South and
64 meters East-West. For areas above 50 degrees North, DTED data only have points with heights
for each sixth arc second in the East-West direction, at 55 degress North (latitude of Southern
Denmark) this corresponds to a distance of 105 meters, the North-South distance however remains
the same.
1
See http://www2.jpl.nasa.gov/srtm/
Download from this Internet address: ftp://e0mss21u.ecs.nasa.gov/srtm/
3
Further information and ordering through this address: http://edcsns17.cr.usgs.gov/srtm/
2
1
At SDU-Esbjerg we purchased the CD that contains data for Northern Europe, for use in the
creation of an improved terrain model of Denmark, and are currently generating grids with cell sizes
of 50 and 100 meters, corresponding to map scales of 1:50.000 and 1:100.00. The results from this
work are promising, and will as soon as possible be made publicly available, with access through
the project web site.4
Data and software used
The DTED data are compiled into CD-ROM discs which typically cover areas extending 18 degrees
East-West and 12 degrees North-South. The price of one CD is US$ 45, on top of which comes
shipping expenses, about US$ 25. On-line payment is possible with commonly used credit cards.
The data sets acquired are shown in Appendix 2. Buying these was the only expense connected to
this task, otherwise it has been possible to use (supplementary) data and software which was either
already available at SDU or free for download and use.
MapInfo with Vertical Mapper
The MapInfo GIS extended with the Vertical Mapper module, which handles raster data is installed
or at least available at Aarhus University as well as at SDU in Esbjerg. It was therefore obvious that
this software should be used and that the results should be delivered in formats readable by
MapInfo. For the work on the terrain models described here, version 7.0 of MapInfo (2002) and
version 3.0 of Vertical Mapper have been used.
Supplementary data and software
During the tasks of importing and editing DTED data, various supplementary data sets have been
used. A global map of coast lines and lakes was found to be available in the "Global Self-consistent,
Hierarchical, High-resolution Shoreline Database (GSHHS)" data set, compiled in cooperation
between University of Hawaii and the American National Oceanic and Atmospheric Administration
(NOAA).5 Data are published in "shape" format, which can easily be converted to MapInfo tables.
Along with this data sets comes a global table with all the coast lines and a subset of the Black Sea
coast, to be used for orientation of the subsets.
Satellite image mosaics have been used as support for the digitisation of coast lines. The Landsat
GeoCover data are made available for non-commercial use from the Global Land Cover Facility
(GLCF), operated by the United States Geological Survey (USGS).6 The images are in the strongly
compressed Mr.Sid format, and can readily be shown in MapInfo, the user only has to specify the
projection (UTM, WGS 84) and zone - this will appear from the file name. The files are however
very large (as they typically cover 5 by 6 degrees corresponding to 500*500 km2), thus a fast and
reliable Internet connection is required to acquire them.
University of California holds a collection of Soviet military maps, which combined cover most of
the World.7 A large part of these have been scanned and made available to the public through the
Internet. This is also the case for maps of Ukraine and Georgia (both former Soviet republics),
where maps in scales 1:100.000 and 1:200.000 are available. The scans are of high quality, and
once they have been downloaded as jpeg files, they are easily geo-referenced in MapInfo. These
maps are well suited for digitisation of land elevation and depths in coastal areas, which would be
very useful for the shallow coastal waters around the Crimean peninsula.
The MICRODEM software is used for importing DTED format data. This software has been
developed by the American army for visualisation of and calculations involving terrain data (such a
4
www.humaniora.sdu.dk/kulturmiljoe/
For description of the GSHHS data set and links to download see:
http://www.soest.hawaii.edu/wessel/gshhs/gshhs.html
6
GeoCover data are available through the GLCF portal at http://glcfapp.umiacs.umd.edu:8080/esdi/index.jsp
7
For an overview of the scanned topographic maps see: http://www.lib.berkeley.edu/EART/topo.html
5
2
projectile trajectories). It is a huge software package with many useful features, but in this project it
has only been used because it can quickly (!) read DTED format data and save them as points in a
text file, which can again be read by MapInfo (and other GIS software).
Methods for import and generation of grids
It has been necessary to apply different software for the different steps of the processing chain form
data on CDs to the MapInfo grids and elevation curves that was ultimately deliverede to the Centre
for Black Sea studier on CD-ROM.
For all relevant 1*1 degree blocks, the following operations were performed:
MICRODEM was used to convert files from DTED to XYZ format
Then MapInfo was used to
ÿ open the XYZ file as a table,
ÿ select points with elevation values different from zero (using the fact that a land-mask has
been applied to the DTED data),
ÿ create points (topology/geography),
ÿ save in UTM projection - in this step it must be remembered to check the UTM zone, it has
to correspond to the Landsat GeoCover mosaic being used, and finally
ÿ edit table structure, so that the only remaining field is "Altitude" (measured in meters, from
column 3 of the imported text table).
The XYZ files are in ASCII format and thus use much disk-space, but they are useful as "base data"
and are thus saved in zipped archives. These are delivered on separate CD-ROMs (or DVD).
The UTM "non-zero" files are intermediate products, from which the subsets are taken that are used
for generating the grids. These subsets are defined by rectangular vector files, termed select*
(identifier for the relevant geographic window). The files are merged for each (planned) output
block, into files termed Coastarea*, as such files with points for the Northern Romania will be
termed CoastareaN45E2830nonzero.TAB (more on nomenclature below). These Coastarea files
provide the base for generation of triangulation (TIN) files and subsequent interpolation of terrain
surfaces, as expressed in the grids. However, before generation of the grids that will make up the
final, coherent terrain model, the following steps of digitising and editing data must be taken:
-
Lines are drawn parallel to the coast, as it appears in the GeoCover images. As close as
possible to the actual coastline, a line (polyline) is drawn and given the value -1 (minus one
meter), this value is typed into the only field in the table structure, called Altitude. At a
distance of one to two km from the coast, another line is made in a similar way, this is given
the value -10. The reason for having two lines, each with a negative value, is the wish to
make sure that the terrain in the model slopes downwards from land to sea, so that the zerocurves (contour lines with Altitude =0) agree with the outlines of the DTED and the
GeoCover images. A minor practical problem occurred when digitising subsets on the
border between two different UTM zones, and thus two different Landsat GeoCover
mosaics. Here, the polygons delimiting the subsets appeared to be slightly displaced, when
shown on top of a raster image with a UTM-projection different from their own. However,
since the tables containing point data (the imported DTED data) are correctly placed relative
to the GeoCover images, it was still possible to carry out digitisation and editing of the
subset, and no negative effects has been observed on the final products.
-
The UTM-nonzero files were continuously edited, i.e. harbour facilities and similar manmade features removed. No interpretations about the age of the visible features were made,
and it must be stated that this kind of editing is strongly subjective and personal.
-
After digitisation, the "depth curves" were converted to point files with distance 75 meters
(1 meter depth) or 100 meters (10 m depth), using the Poly-to-Point function of Vertical
Mapper (under the Create Grid option). Then these ptp-files were added to the Coastareafiles using the "Append Rows to Columns" function of MapInfo. Then Vertical Mapper can
3
be used to generate grids with a cell size reflection the users needs. During generation of
grids, the TIN (Triangular Irregular Network) file is saved. This file stores the
mathematical/geometric model mentioned in the introduction, which represents the coherent
model of the terrain surface. It has the suffix .TIN, see below.
-
The grids that are thus created are used for extraction of contour lines with an appropriate
equidistance, defined by the user.
Nomenclature and file structure
The finalised terrain models are delivered on CD-ROM. Files which represent calculations and
partial results are store as back-ups at SDU-Esbjerg, but are not thought to be of interest to the end
users.
Each of the blocks are names from the geographical coordinates within which they lie, first degrees
latitude (North) and then longitude (East). For example, the subset around Histria in Romania,
spanning from 43 to 45 degrees North and 27 to 29 degrees East is termed N4345E2729. The vector
files with contour lines (respectively 10 and 25 meters depending on the local type of terrain) are
named in a similar way, with the file name indicating the equidistance, so that for instance the
vector file for the Histria subset with 25 m equidistance ends up being called:
"Altitude_N4345E2729_TIN50m_contour25lines.TAB".
The Black Sea data set consists of the following general geographical zones (it was aimed at having
one zone on a separate CD-ROM, however for some two was needed):
• Turkey - spread on two CD-ROMs, with the Eastern and Western parts respectively.
• Bulgaria and Romania (abbreviated to the folder BulgRom)
• Ukraine including the Crimean peninsula - spread on two CD-ROMs, with the Eastern and
Western parts respectively.
• Caucasus (with parts of Russia, Georgia and Turkey).
In addition, smaller subsets have been extracted and processed for areas around Antioch in the
Southernmost Turkey, bordering Syria (UTM zone 37) and most of Latium in what is today Italy
(UTM zone 33). The subsets are delivered on a separate CD-ROM.
Auxiliary files include coast lines, or rather the one and ten meter curves mentioned above, digitised
for each map window based on GeoCover images. The triangulations (.TRI files) are also included,
since the generation of these represent the most time consuming process, and they can be used by
Vertical Mapper to generate grids on any desired cell size. For each area, the following directories
have been created:
Grids
These are the actual terrain models, to be used in MapInfo, represented by two-dimensional
matrices of interpolated elevation values. In this version, the cell size is 50 meters. The format is
MapInfo grid, allowing for display "in the background" in map windows when working with
ordinary vector files, and for use in raster format and further calculations with Vertical Mapper.
Contours
These are the contour lines which have been extracted from the terrain models (grids) using Vertical
Mapper. For all subsets there is a version with equidistance 25m, for areas with flat terrain also 10m
equidistances are found. This will appear from the files names (see above).
Triangulations
Here are stored the important calculations on the way from points to grids - represented by .TRIfiles. These can be used for generation of grids with any desired cell size, it is however
recommended to restrict oneself to between 25 and 500 meter.
4
Outlines
In this directory the vector files outlining each block/subset is stored. Their file name begins with
Select*, and they were used when for extraction of the "Coastarea*-files" from the one by one
degree imported blocks of DTED data. Also in this directory are depth contours, typically estimated
values at 1 and 10 meters, these files have names beginning with Coastline*, with the remainder of
the filename indicating the actual subset and depth.
Index
These files are stored at a higher level in the file structure, as they show the location of the subsets
on one or two CD-ROMs. There is a table for each UTM zone, these can be displayed together in
one map window. Along with these files (the combined outlines) are GSHHS coastlines and a
vector file with a latitude-longitude grid for easier orientation, these grids are termed LongLat*
(added the actual area). Projection follows UTM zones, this is done in order to avoid "twisting" the
coordinate system as well as to assure agreement with local/national maps and military (NATO)
maps.
Accuracy, limitations and sources of error
For areas where topographic maps were available, in this study Ukraine and Georgia, elevation
values in the generated grids and extracted contour lines could be directly compared with points and
curves on the (scanned) maps. Unfortunately, in this project no time had been allocated for creation
of a data set on which a statistical assessment of accuracy could be built. However, visual
inspection of the different types of data showed general good agreement. This was also the case
when the extracted contour lines were displayed over Landsat GeoCover data, and the valleys and
ridges outlined by the curves also were seen in illumination and vegetation features in the images.
In spite of the extra work put into the creation of the DTED data, gaps in the data sets can not be
avoided. This is most of all due to the terrain itself. Where a hillside is steeper than the "viweing
angle" of the space borne radar, parts of the terrain will be in "shadow" and then it is simply not
possbile to measure an altitude value. In the delivered products, grids and contour lines, these gaps
are not immediately seen, since they have been filled by interpolation, they can however appear as
unrealistically flat or smoothly sloping surfaces.
In some coastal areas, altitude values below zero were observed, also more frequent than could be
expected. This is due to a "vertical offset", caused by a difference between the local reference sea
level used for topographical mapping and a global reference used for the SRTM data (the WGS84
ellipsoid), as discussed in Kellndorfer et al 2004. The most remarkable deviations were observed for
the Odessa area, with deviations of 2 to 3 meters.
The Altitude values in the data does not necessarily describe the soil surface, but rather an integral
value of the height of elements within the three by three arc second area that reflect radar waves in
the C-band (Rabus et al 2003). This goes for buildings as well as vegetations. The influence of
vegetation, mostly trees on the height values is described in Kellndorfer et al (2004), where it is also
discussed how this can actually be utilised for delineation of forest areas and estimation of tree
heights, given terrain elevation data are available from another source, be it topographic maps of
sufficient accuracy, airborne LIDAR scans of the surface or other remote sensing techniques.
Perspectives and further work
An obvious follow-up activity will be to make this dataset publicly available on the web site
www.pontos.dk, preferably integrated with the "gazetteer" function that is currently being
developed. Ideally, terrain data should be available as "wall-to-wall" coverage of the entire Black
Sea area, allowing users to zoom in and out and download selected subsets in vector or raster format
using a web-based interface (where more data could be added gradually). To do this, the Black Sea
5
Centre would need a web-server capable of handling a geo-referenced data base as well as raster
data.
If necessary, the separate grids can merged to create files covering larger areas, this is done using
the Splicer function of Vertical Mapper. Using other functions, smaller areas can (then) be taken out
for use in local studies or for illustrations.
Further work with terrain models and other GIS data will to a wide extent depend on the research
needs of the different sub-projects of the Black Sea Centre, on the actual problems to address and
specific questions to answer. For instance, a large amount point data have been acquired using
Global Positioning System (GPS) equipment - and initial inspection of these data along with the
terrain models and GeoCover images show a fine agreement.
When terrain data are used for field work and reconnaissance, information on current land use and
land cover will be useful. It is thus relevant to supplement with such data that are available to the
public at various spatial and thematic resolutions, often directly on Internet. For the Western part of
the Black Sea area, an obvious information source will be Corine Land Cover (CLC) 2000 data with
a spatial resolution of 100 meters, since both Romania and Bulgaria are covered by these.8 Through
use of precise and up-to-date land cover data (preferably as close as possibly to February 2000 as
possible), it will be possible to compensate for vegetation influence on terrain height. In practice,
this can be done through assignment of a certain "element height" to each land cover class such as
coniferous or deciduous forest (3-5 meters, see also Kellndorfer et al (2004)). These values are then
subtracted from the surface height in the SRTM-DTED data. For areas outside the current EU,
global vegetation data sets exist with spatial resolutions of 500 and 1000 meters, also building on
satellite image data.
The scanned topographic maps from Berkeley (see section on Data above) can be downloaded as
image files in jpeg-format, these are easily geo-referenced in MapInfo with good geometric
accuracy. Then it is possible not only to compare the extracted contour lines with those on the
maps, town areas and forest can also be identified, digitised and for instance used for correction of
surface values as discussed above. From the numerous points with height values in low-lying parts
of the maps, it will be possible to correct the average height values in each subset. This was not
done in the compilation of the current data set, as it would be very time consuming and also hamper
the "seamless" coherence between data from the different subsets.
If very detailed imagery is required for a particular, smaller area, for instance if burial mounds or
remains of fortifications are to be identified, then very high-resolution satellite imagery is a possible
data source. These are available with pixel sizes down to one meter. They are however relatively
expensive, when ordered through a commercial supplier, especially if there is no data from the area
of interest in the archives and a new snapshot is required (at least the images then are up-to-date). If
on the other hand, older images can do the same job, and it is possible to browse and order declassified "spy" satellite images from United States Geological Survey (USGS), where a large
image archive have been scanned and made accessible on-line.9 Of particular interest to the Black
8
CORINE is an EU funded project, aimed at providing as precise land use/land cover data as possible, in particular for
environmental monitoring and planning. Data must furthermore be comparable across national borders. CORINE is an
acronym for COordination of INformation on the Environment. The project was initiated back in the 80's, and Corine
2000 is an upgrade and update built on collection and interpretation of satellite images acquired in 2000 +/-one year.
Read more about the data set at http://org.eea.eu.int/documents/newsreleases/landscape-en, see also
http://terrestrial.eionet.eu.int/CLC2000
9
The Earth Explorer portal gives access to satellite images as well as aerial photography and cartographic products, the
latter most for the United States. Start at the address: http://edcsns17.cr.usgs.gov/EarthExplorer/
Note that registration as user is required in order to be allowed to view the examples.
6
Sea Centre will be images from the CORONA satellite, whcih were in use from 1959 to 1972, an
example from Crimea is shown in Figure 1 below.
Figure 1 Quicklook of CORONA image of the area around Sebastopol September 1966. The
resolution of the original image is about 2 meters, in this example somewhat more, as the image
was converted to jpeg-format. Data can be ordered from USGS as scanned negatives on CD-ROM
or DVD. Note that the images is rotated, so Northwest faced upwards.
From digital terrain models, a multitude of calculations, analyses and cartographic modelling can be
made. It is quite straight forward to derive values for terrain slope and aspect, two parameters of
importance for the agricultural potential of soils, for accessibility and settlement - for a good
introduction to these issues see Stancic and Kvamme (1998), with analyses of the locations of
bronze age settlements on the Croatian island Brac. Specific modelling of where people chose to
settle within an area, build temples and fortifications and constructed roads still requires a priori
knowledge on (culturally determined) preferences and technological capabilities. With more
advanced models for instance including hydrological parameters and knowledge on soil and subsoil properties, it should be possible to characterise fertility and agricultural potential of the land.
Finally, it can be a goal in itself to reconstruct the landscapes of the past, in order to visualise how
travellers and residents perceived them at different times and under different circumstances. This
will be of particular interest for the Black Sea area, where data sets like this will make it possible to
generate images of how different stretches of the coast have appeared from the sea. However, in
order to make such reconstruction realistic, we should have geological and/or soil,
paleoclimatological and preferably written sources, with descriptions of the use of the land and how
the landscapes appeared.
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Figure 2 Topographic maps at scale 1:100.000 come alive, when they area draped onto the terrain
models. Here map sheet number L-36-128 with Sebastopol in the upper Northwestern corner is
shown on the DEM for the Southern part of Crimea. The town and the bay can be seen in the lower
left corner of the image.
Literature
Balstrøm, Thomas (1999): (Mere om) Digitale Højdemodeller. Pages 115-124 in GIS i Danmark
2, Teknisk Forlag. ISBN 87-571-2272-5.
Ejstrud, B. (in press): Cost surface analysis and ancient roads: A comparison. In: Temps et
espaces de l'homme en societé: Analyses et modèles spatiaux en Archaeologie.
Kellndorfer, Josef, W. Walker, L. Pierce, C. Dobson, J.A. Fites, C. Hunsaker, J. Vona, M.
Clutter (2004): Vegetation height estimation from Shuttle Radar Topography Mission and National
Elevation Datasets. Remote Sensing of Environment vol. 93, no. 3, pp. 339-358.
van Leusen, P. Martijn (1993): Cartographic modelling in a cell-based GIS. Chapter 11, pages
105-123 in Computing the Past, Computer Applications and Quantitative Methods in Archaeology,
CAA92, red. J. Andresen, T. Madsen og I. Scollar. Aarhus University Press, ISBN 87-7288-112-7.
Rabus, Bernhard, M. Eineder, A. Roth, R. Bamler (2003): The shuttle radar topography mission
- a new class of digital elevation models acquired by space borne radar. ISPRS Journal of
Photogrammetry and Remote Sensing vol. 57, pages 241-262.
Stancic, Zoran og Kvamme, Kenneth K. (1998): Settlement Pattern Modelling through Boolean
overlays of social and Environment variables. Pages 231-237 in New Techniques for Old Times,
Computer Applications and Quantitative Methods in Archaeology. Proceedings of the 26th
conference, Barcelona March 1998. Red. Barceló, J, I. Briz, A. Vila. BAR International Series 757.
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Appendix 1 Geographical location of the finished subsets
MapInfo map with subset from the Western part of the Turkish Black Sea coast, made using the
table index_Turkey_all.TAB, with labels from the fields Name, UTMzone and CD_Volume.
Coastlines from GSHHS and country borders from Digital Chart of the World (DCW).
MapInfo map with subset from the Eastern part of the Turkish Black Sea coast, made using the
table index_Turkey_all.TAB, with labels from the fields Name, UTMzone and CD_Volume.
9
MapInfo map with subset from the Westernmost Black Sea coast with Bulgaria and Romania, made
using the table index_Bulg_Rom.TAB, with labels from the fields Name and UTMzone.
MapInfo map with subset from the Northern Black Sea coast and the Sea of Azov, made using the
table index_ Ukraine_Crimea.TAB, with labels from the fields Name, UTMzone and CD_Volume.
Coastlines from GSHHS.
10
MapInfo map with subset from the Eastern Black Sea coast with parts of Russia, Georgia, and
Tyrkey, made using the table index_Kaukasus.TAB, with labels from the fields Name, UTMzone
and CD_Volume. Coastlines from GSHHS.
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Appendix 2 Overview of all DTED data, acquired during the project
Each of the images in this section corresponds to (the geographical area covered by) a CD-ROM
with data, and has been generated in MICRODEM from the file called onc.dir, on each CD placed
in the library text. The numbers on the maps refer to UTM zones.
DTED area 11, from 42 to 54 Degrees North and 11 degrees West to 12 degrees East.
DTED area 12, from 42 to 54 degrees North and 12 to 30 degrees East.
12
DTED area 13, from 42 to 54 degrees North and 30 to 48 degrees East.
DTED area 23, from 30 to 42 degrees North and 10 degrees West to 6 degrees East.
13
DTED area 24, from 30 to 42 degrees North and 6 to 24 degrees East.
DTED area 25, from 30 to 42 degrees North and 24 to 42 degrees East.
14
DTED area 26, from 30 to 42 degrees North and 42 to 60 degrees East.
15