Evaluating the Potential of the Forthcoming Commercial U.S. High-Resolution Satellite Sensor Imagery at the Ordnance Surveys

Home , Ordnance Survey, Topographic map

Helen M. Ridley, Peter M. Atkinson, Paul Aplin, Jan-Peter Muller, and Ian Dowman

Abstract TABLE1. NATIONALTOPOGRAPHIC DATABASE STATISTICS As the National Mapping Agency of Great Britain, the Ord- Urban Rural Moorland nance Survey" (0s) is driven by a need to reduce costs and Specification 1:1,250 scale 1:2,500 scale 1:10,000 scale commercialize operations, and as such has been investigat- -- - ing photogrammetric methods to improve existing products, Approx. Number of Tiles 67,000 158,000 4,000 Tile Coverage 500 m' 1 kmz 5 kmz streamline existing production, and increase the current portfolio of products. Over the last 18 months, the 0s has been involved in a major research project to tackle these is- sues through an evaluation of the forthcoming commercial duce costs and commercialize operations so that there is a U.S. high spatial resolution satellite sensors which are offer- return on the investment made by the taxpayer. ing 1-m panchromatic and 4-m multispectral spatial resolutions. Work has focused on improving the existing National The National Topographic Database Height Dataset (NHD), reducing the cost of photogrammetric The National Topographic Database (NTD) consists of infor- survey, automatic topographic feature change detection, pro- mation collected over 200 years and converted into digital duction of DM; three-dimensional (30) urban models, and format over the last 25 years. Britain now has a two-dimen- land-use classification. Results from the project using sional (ZD) database with 229,000 map tiles modeling urban simulated imagery indicate that it would have potential areas at a nominal survey scale of 1:1,250 for minor towns, within the 0s in all areas evaluated. The work now needs to 1:2,500 for rural areas, and 1:10,000 for mountain and moor- be followed up when real high spatial resolution satellite im- land areas. This database represents our most major asset agery becomes commercially available. and its maintenance is of prime importance. A summary of the NTD can be seen in Table 1. Introduction The NTD currently holds in excess of 200 million fea- The Ordnance Survey as a National Mapping Agency tures; this includes building outlines, walls, fences ad In 1991, the Ordnance Survey@(0s) celebrated 200 years of hedges, road limits, names, water features, etc., which are continuous operation in providing Britain with a rich map- managed together to create and maintain a continuous model ping base, and within the last five years we have witnessed a of the nation. number of major events and achievements that rank in signif- Keeping the NTD up to date is of vital importance, and icance with this milestone. In 1995, national large-scale digi- the 0s is striving to ensure that "major features" are incorpo- tal data coverage was completed, resulting in the National rated into the NTD within six months of their construction. In Topographic Database (NTD). A national on-demand map urban areas, all significant change is surveyed to this level. plotting service was launched later that year, and, more re- Additionally, in April 1995 the 0s launched a systematic up- cently, a national address database was completed. dating of the NTD for all the rural and moorland areas of the The Ordnance Survey has been a United Kingdom (UK) country on a rolling five- and ten-year basis, respectively government Executive Agency since 1990, and has been in- (Ordnance Survey, 1995). Ensuring that these targets are met creasingly successful in improving its position as the leading is one of the main drivers in the OS. supplier of geospatial data and information in Great Britain. 0s revenue was E66m during the financial year 95/96. This Photogrammetry at the OS is equivalent to a 78 percent return on annual expenditure Photogrammetry plays an important role within the OS, and which is very high compared to other national mapping over the last 10 to 15 years we have witnessed some major agencies. However, the environment under which national photogrammetric advances and successes in migrating from mapping agencies, such as the os, operate is increasingly the 1950's analog technology to analytical instrumentation challenging, and we are now totally driven by the goal to re- and, more recently, their softcopy equivalents (Farrow and Murray, 1992). H.M. Ridley is with the Ordnance Survey, Romsey Road, As a result of a decision in 1995 to systematically up- Southampton SO16 4GU, United Kingdom. date all of the rural and moorland areas on 5- and 10-year P.M. Atkinson and P. Aplin are with the Department of Ge- Photogrammetric Engineering & Remote Sensing, ography, University of Southampton, Highfield, Southampton Vol. 63, No. 8, August 1997, pp. 997-1005. SO17 lBJ, United Kingdom. J-P Muller and I. Dowman are with the Dept. of Photogram- 0099-1112/97/6308-997$3.00/0 metry & Surveying, University College London, Gower Street, 0 1997 American Society for Photogrammetry London, WClE 6BT. and Remote Sensing mid 1997. Currently, three companies in the U.S. -Earth- Scanned Watch, Space Imaging, and Orbital Sciences - have high resolution imaging satellites under development and are es-

, a1r ph; ,471 tablishing international strategic partnerships for reception, processing, and distribution (Fritz, 1996). These systems are 2 Ortho- fl , NTD day NTD offering the potential of up to 1-m panchromatic and 4-m 1 Roll Fed Scanner rect~ficat~on scop~cSurvey Systems Workstat~ons , multispectral spatial resolutions. Table 2 provides an over- view of these systems. Figure 1. The 0s Digital Mono-Plotting System. Current Research Testing the Potential of Space Imagery The OS, in collaboration with the Department of Photogram- cycles, the photogrammetric department at the 0s now faces metry and Surveying at University College London and the the challenge to update around 21,500 rural and 400 moor- Department of Geography at the University of Southampton, has been involved in a project to evaluate the potential of land NTD data tiles per year. This is equivalent to 900,000 units of update (these may be houses, roads, forestry, etc. - the forthcoming commercial U.S. high spatial resolution all features are measured using a common measure of units satellite sensors, which are offering 1-m panchromatic and of change), representing approximately 20 percent of the 4-m multispectral imagery, for use within Britain. The project is partly funded by the British National Space Centre NTD. This is a major undertaking and, as a result, the 0s must investigate moving from more manual photogrammetric through their second Application Demonstration Pro- processes towards automation, particularly in the areas of gramme. Work started in October 1995 and was completed change detection and survey. in March 1997. Recent moves towards automation have focused on a The 0s has a major advantage in research because of the digital monoscopic photogrammetric solution to systemati- extensive existing data available to assist the analysis of the imagery, including a National Height Dataset (NHD) with con- cally update the NTD. Following successful trials and a production pilot, a full production Digital Mono-Plotting (DMP) tours at 5-m vertical intervals and complete digital map system is now in operation, as shown in Figure 1. coverage of the country at 1:1,250, 1:2,500, and 1:10,000 A Global Positioning System (GPS)computer-controlled scales. navigation system is used in the aircraft to take the aerial The project was broken into six research areas which will be discussed in the following sections: photography specifically for the DMP system. This system triggers the camera exposure, resulting in the photographs filling in gaps in the NHD, being centered on each NTD data tile to be updated. The pho- automatic change detection, tography at 1:7,500 scale is then scanned at a ground sample using satellite imagery for topographic mapping, distance (known hereafter as spatial resolution) of 0.2 m on digital elevation models (DEMS), 30 building models, and the roll-fed scanner, ready for orthorectification using Inter- national land-use database. graph's Imagestation softcopy workstation. Orthorectification is carried out using ground control from existing NTD data and height data from the National Height Dataset (NHD).The Test Sites and Imagery Used single orthorectified image is then used as a backdrop to the Test sites have been established in Lincolnshire (low lying NTD data to be updated manually on the workstation. coastal), the Lake District (mountainous), and Hertfordshire The DMP system is currently on schedule for updating (rolling mix of agricultural, urban, and highways). Unfortu- around 14,000 rural NTD data tiles per year, and, in order to nately, during the project there was no satellite imagery actu- do this, each week around 300 to 400 photographs need to ally available at 1-m panchromatic or 4-m multispectral be scanned and orthorectified. spatial resolutions, simulated or otherwise. The OS therefore created simulated imagery at a 1-m spatial resolution by av- Potential of Space Imagery eraging 0.2-m imagery derived from 1:7,500-scale aerial pho- The os has invested extensively in research into the poten- tography, and has acquired imagery from both the tial of satellite imagery for topographic mapping over the spaceborne radar systems ERS-1 and 2 (for deriving DEMs us- past 15 years (Hartley, 1991). This did not produce accept- ing SAR interferometry) and 4-m multispectral airborne im- able results until spatial resolution improved with the agery from the Compact Airborne Spectrographic Imager launch of SPOT-1 in 1986. The 0s then undertook the (CASI)(for land-use evaluation). Where possible, airborne sys- world's first extensive topographic mapping project in the tem parameters were matched as closely as possible to one of civilian sector using SPOT. Stereo hardcopy SPOT imagery the proposed satellite sensor systems. was employed to map over 25,000 kmz of northeast Yemen The project was also scheduled to evaluate data from (Murray and Farrow, 1988). Other investigative work and production projects followed. More recently, this has in- TABLE2. U.S. HIGH SPATIALRESOLUTION SATELLITE SENSOR SYSTEMS volved a collaboration between the 0s and the National Re- mote Sensing Centre Ltd (NRSCL)to produce an image map Planned Spatial of Christmas Island (Havercroft and Fox, 1993). However, System Launch Resolution Comments for satellite imagery to be successful in Britain, it has been Earthwatch Inc Stereo ForeIAft concluded that a spatial resolution of 2 m or better would - Earlybird 1997 3 m Panchromatic be needed to support the applications required to maintain - Quickbird 1998 I m Panchromatic the existing database. Space Imaging Stereo ForeJAft This threshold of spatial resolution is now close to being 1997 4m Multispectral realized with the declassification of military technology by 1 m Panchromatic the Clinton administration. The first of several commercially OrbImage Stereo ForeIAft - Orbview 1 1998 8 m Multispectral owned and operated, very high resolution, digital Earth ob- - Orbview 2 1998 1 &2m Panchromatic serving satellite systems will be launched into polar orbit in

August 1997 PE&RS Earthwatch's EarlyBird satellite (3-m panchromatic spatial not clear but may be due to the quality of the input data, resolution) for validation of the simulated data results. How- limitations of the software, the averaging effect inherent in ever, the delay in the launch meant that this work has not the DEM creation process, or the presence of additional sur- been possible within the timescale of the project. face features which were not edited out, such as vehicles and vegetation. If this systematic error is removed, the accuracy of the DEMS would be much better, as can be seen by I Filling in Gaps in the National Height Dataset (NHD) the standard deviation which is less than 1 m for the DEM The 0s has recently completed a major program to create a created from 0.2-m spatial resolution imagery. digital NHD from the 5-m vertical interval contours on a Editing of the DEM to remove surface features such as 1:10,000-scale paper maps. However, due to cartographic rea- trees, bridges, gantries, large vehicles, etc., around the roads1 sons, contours on the old mapping were broken at the edge railways would have created more accurate DEMs, but it was of major features, such as roads and railways, which are of- not possible in the timescale to test this out. ten surrounded by cuttings and embankments. As a result, the digital NHD product now contains gaps. The aim of this section of the project was therefore to try to automatically fill Automatic Topographic Change Detection in these gaps with height information. This is an important issue when planning the deployment of Accuracy tests have shown that the source contour data around 600 survey staff and resources at the 0% i.e., identi- of the NHD has a root-mean-square error (RMsE) of 1.25 m; fying what change exists and where it actually is. The nature however, in localized areas around features such as major and importance of change varies by topography and geogra- cuttings and embankments along roads, the error is signifi- phy; e.g., a new fence dividing a rural land parcel may be cantly worse. much more important than a similar structure in an urban Because many of the gaps in the NHD occur along the public park. Although urban change is often well reported, lines of roads, the work concentrated in these areas. Existing rural change is often more difficult to detect and hence is topographic map data have helped the process, with road to- rarely fully documented. pography being employed as breaklines. Although the os already employs several manual ap- DEMs were created automatically on Intergraph's Image- proaches to solve this problem, it is believed that change de- Station softcopy workstation from the simulated aerial im- tection methods can be automated. Currently, most major agery at I-m and 0.2-m spatial resolutions (the 0.2-m imagery changes to buildings, roads, etc., are identified through planning applications, but rural changes, which are often exempt I was used as a baseline for analysis). The algorithm used for I the DEM creation was MATCH-T, developed by INPHO, GmbH, from planning control, such as fences and farm buildings, are I Stuttgart, Germany. The minimum DEM grid spacing available notoriously difficult to identify. I 1 with the MATCH-T software was 10 m for 1-m spatial resolu- The aim of this aspect of the project was to see whether tion imagery and 2 m for 0.2-m imagery. The 2D vectors, for 1-m spatial resolution satellite imagery could be used to au- ~ roads and railways, were then automatically extracted from tomate the process of topographic change detection. Two , approaches using DEMs were used: 1 the NTD data and projected onto the DEM, allowing 3D heights along the vectors to be interpolated. Comparison of DEMs from two epochs, and 1 Table 3 shows the results, for a small sample area, of the Masking a new DEM with building polygon data. 3D I spatial accuracy of the vectors interpolated from three dif- I ferent types of DEM, when compared against heights captured conventionally on an analytical plotter using large-scale pho- Comparison of DEMs from Two Epochs tography (1:7,500 scale). DEMs were automatically created from both 1980 and 1995 The 3D vectors interpolated from the DEMs created from aerial imagery at 1-m and 0.2-m spatial resolutions using In- the 0.2-m spatial resolution imagery provided more accurate tergraph's Imagestation softcopy workstation using MATCH-T results (RMSE 2.17 m) than did those created using the NHD DEM software (0.2-m imagery was again used as a baseline for and interpolating between the contour gaps over cuttings and comparison). The DEMs created from the two epochs were embankments (RMSE 4.85 m). Additionally, the heights along then differenced such that analysis could be carried out to 1 these 3D vectors were jagged and would need further pro- see if topographic change could be easily detected. cessing to smooth them out. Figure 2 shows a DEM which has been created by differ- The 3D vectors interpolated from the DEMs created from encing the DEMS created from the 1980 and 1995 aerial im- the 1.0-m spatial resolution imagery provided worse results agery scanned at 0.2 m, with the up-to-date vector NTD data 1 (RMSE 5.66 m) than did those from the original NHD (RMSE superimposed. The lighter areas imply new features since 4.85 m). These results imply that the use of these vectors as 1980, and the darker areas imply that features on the 1980 breaklines within the NHD would degrade the accuracy of the imagery have disappeared in the 1995 imagery. This example original NHD in this area. shows three new buildings since 1980 in the middle area of All of the DEMs created overestimated the height (as the image (the vectors show that these were genuine features shown in the mean). The reason for this systematic shift is which have since been surveyed), and a new area of trees in the northeast corner. Additionally, the vwy dark areas show where vegetation has been cut down. (The diagonal line in the northwest corner is a model join.) Figure 3 shows exactly the same area as Figure 2, but Standard the DEMs have been derived from 1-m spatial resolution im- Source data DEM grid deviation Mean RMSE agery rather than 0.2-m imagery. The diagonal stripes are a for DEM width (m) (m) (m) Range (m) (m) result of the DEM algorithm used. This example shows that 0.2-m (spatial 2.0 0.99 1.93 0.00 to 7.62 2.17 the three new buildings and new area of trees that were resolution) clearly identifiable from DEMs created from 0.2-m spatial res- aerial imagery olution imagery are much less defined, and without the vec- Original NHD 10.0 2.81 3.95 -1.34 to 6.92 4.85 tors the smaller two buildings would not have been identi- 1-m (spatial 10.0 2.34 5.16 -1.57 to 13.52 5.66 resolution) fied at all. The dark patch to the mid left of the image aerial imagery represents a major anomaly in one of the DEMs. Analysis has shown that change can be detected in the Figure 2. The difference between DEMS created from 0.2- Figure 3. The difference between DEMS created from 1-m m spatial resolution imagery from 1980 and 1995 with spatial resolution imagery from 1980 and 1995 with NTD NTD data superimposed. data superimposed.

data using 1-m and 0.2-m spatial resolution imagery; how- Potentially, the new 1-m spatial resolution satellite imagery ever, the change is less pronounced using the l-m imagery offers significant cost savings when compared with aerial because the differences are averaged out. This flattening does photography in the form of larger footprints, requiring less mean that it is more difficult to differentiate between actual ground control and hence less processing and model setting change and blunders in the DEM;as a result, it would be and more frequent revisit times, something of great impor- more difficult to automate the detection of this change. Table tance in Britain where the skies are not always clear. (Con- 4 shows some examples of these differences. versely, the larger footprint means that there is greater likelihood of some cloud cover within the image.) Masking a New DEM with Building Polygon Data Investigation on this aspect of the project has centered The existing NTD contains a wealth of information about the around whether surveying to the current rural specification landscape, including implicit polygons for buildings and veg- is possible using 1-m spatial resolution satellite imagery from etation cover. Analysis, therefore, focused on using these the new sensors. polygons as masks to flatten the surface of the DEM in an at- The work within this aspect of the project was broken tempt to highlight areas of building change. down into an evaluation of monoscopic and stereoscopic A DEM was created using recent photography in the photogrammetric techniques. Both methods used imagery same way as the previous option. The underlying elevation with a spatial resolution of 1 m to simulate the imagery from was then removed by subtracting the M-ID data from it. This the new satellite sensors, together with imagery at a 0.2-m meant that the only features above or below zero theoreti- spatial resolution used as a baseline for comparisons. cally represented topographic change such as buildings, The work in mono was carried out on the DMP system at trees, etc. The NTD data containing building polygons was the 0s. The imagery was orthorectified on Intergraph's then superimposed to automatically mask out the buildings Imagestation softcopy workstation using height data from the that already exist in the database, reducing the DEM down to NHD together with control taken from the existing mapping. zero in these masked areas. Features above or below zero The orthorectified images were then transferred onto the would then represent vegetation and buildings. mono-plotting workstation within the DMP system where, us- Analysis showed that the DEM created from the imagery with 1-m spatial resolution was too coarse to highlight topographic change because of the software limitation, which TABLE4. FEATUREHEIGHTS ON THE DIFFERENCEDDEMs meant that the grid spacing could not be less than 10 m. However, tests using the 0.2-m spatial resolution imagery did Differenced DEM Differenced DEM show up areas of change, proving that the method was feasi- using 0.2-m spatial using 1-rn spatial ble. Feature resolution imagery resolution imagery New Building since +9.55m +6.56m Topographic Mapping 1980 Current photogrammetric methods of topographic mapping New Hedgerows f3.42m f2.23m since 1980 in rural areas (1:2,500 scale) are based around the use of aer- Trees removed after -4.29m -2.41m ial photography either on analytical plotters or on the 0s 1980 Digital Mono-Plotting (DMP)system described in Figure 1.

August 1997 PE&RS Features Fences, Features Interpreted Road Hedges, Missing Identified Correctly Feature Type Buildings Pavement etc. Features Total (%I (%I

Buildings 4 3 16 5 9 72.9 72.9 Road Pavement 86 2 9 9 7 90.7 88.6 Existing Fences, hedges, 15 7 135 155 312 50.3 43.3 NTD data etc. Additional 18 2 30 0 50 Features Total 76 95 167 180 518 Features 76.3 97." 77.C Identified (%) Features 56.6 90.5 73.1 51.0 Interpreted Correctly (%)

ing manual methods, features were surveyed directly off the the 1-m resolution imagery). This represented around 50 per- image on the workstation using a mouse. cent of the features on the 1-m resolution imagery. The stereo work was carried out on Intergraph's Image- It should be noted that the number of features actually Station softcopy workstation. Using GPS control, a semi-auto- surveyed does not necessarily correlate with their size or rel- matic block adjustment was carried out on the area of inter- ative importance, such as a long stretch of road paving and a est, which encompassed eight images, to establish stereo minor fence in a built up area. models for data capture. The features were then surveyed From the limited accuracy assessments carried out on manually in stereo on the same workstation. the surveyed features, results indicated buildings and roads having an RMSE of around 3 m, and fences or hedges having an RMSE of around 4 m. However, it should be noted that the Monoscopic Eva1uation control used to create the orthorectified images was taken The results of feature identification in a rural area, when from the existing topographic detail and, as such, was rela- compared with the existing data specification and the exist- tively low order. The accuracy assessments were carried out ing NTD data of the test areas, can be seen in the confusion by comparing the newly surveyed data from the 1-m spatial matrices shown in Table 5 and Table 6, for 1-m and 0.2-m resolution imagery with the existing NTD data. These results spatial resolution aerial imagery. are outside the expected accuracy of the 1:2,500-scale NTD The tables summarize the results for the three main data. ground features found in rural areas. Interpretation is clearly A similar more limited analysis to this was also under- a problem at 1-m resolution, with only 51 percent of features taken in a moorland (1:10,000-scale)area. Slightly better re- in these main categories actually being identified and inter- sults were achieved, with correct feature identification and preted correctly, and 55.6 percent of features actually being interpretation being around 55 percent. Unfortunately, no ac- identified. curacy assessment could be made for this area. The improved 0.2-m resolution imagery clearly shows Because of the poor feature identification results and the how much more detail can be surveyed (76.0 percent identi- accuracy using monoscopic techniques in both the rural (1: fied and interpreted correctly). 2,500-scale) and moorland (1:10,000-scale)areas, we have Table 6 represents what can be done using the current concluded that 1-m spatial resolution satellite imagery is un- DMP system, which uses 0.2-m resolution aerial imagery; likely to provide a viable alternative to the current use of however, results are significantly improved on the actual sys- 0.2-m aerial imagery on the DMP system using the current tems used at the through the use of contact prints and 0s data specification. stereoscopes. Recent accuracv tests have shown that feature accuracy kdidentification ;sing a stereoscope as an aid to DMP is around 85 percent. Stereoscopic Evaluation Identification and interpretation of both roads and build- Tables 7 and 8 show how the main features within the sur- ings was significantly higher than for the less distinct fence vey specification were identified and interpreted from the and hedge features, with a significant number of these fea- stereo aerial imagery with 1-m and 0.2-m spatial resolutions, tures not being seen at all in the imagery (312 in the case of respectively, in a rural (1:2,500 scale) area. They show a sig-

TABLE6. CONFUSIONMATRIX FOR 0.2-MSPATIAL RESOLUTION IMAGERY - MONOSCOPICEVALUATION Features Fences, Features Interpreted Road Hedges, Missing Identified Correctly Feature Type Buildings Pavement etc. Features Total (%I (%I

Buildings 20 1 2 2 3 91.3 87.0 Road Pavement 44 1 0 45 100.0 97.8 Existing Fences, Hedges, etc. 10 2 63 15 90 83.3 70.0 NTD data Additional Features 3 1 5 0 9 Total 3 3 4 7 70 17 167 Features Identified (%) 90.9 97.9 92.9 84.4 Features Interpreted Correctly (%) 60.6 93.6 90.0 76.0 TnarE7. ConrusrorulVlATRrx FoR 1-w SpnrrnrRESoLUTToN lvncERv - SrenEoscoptcEvnrunrtoru [- Features Fences, Features Interpreted Road Hedges Missing Identified Correctly FeatureType Buildings Pavement etc. Features Total ('/") (%) Buildings 89 2 13 104 B7.5 85.6 Road Pavement 115 I 2 126 98.4 91.3 1.2 ( 196 533 63.2 61.0 Existing Fences,Hedges, etc. "? NTD data Additional Features I 2 30 40 Total 109 LL7 366 21.1. 803 Featurecapture accuracy(%J 92.7 98.3 91.8 68.7 Correctfeature capture accuracy(%) 41.7 98.3 88.8 65.9

nificant improvement in identification and interpretation shown that it is more realistic for it to be used for 1:10,000 when compared againstthe monoscopic evaluation. How- scale and smaller, becauseof the increasedaccuracy and im- ever, the same trends still exist, with the building and road proved identification/interpretationof featureswhen com- detail being easierto survey than the fencesand hedges. pared with the results from the 1:2,500-scalemapping. Topographic mapping from the imagery with 1-m spatial resolution on the stereosoftcopy workstation (65.9 percent) DigitalElevation Models (DEMs) has proved better than using the sameresolution in mono There is increasingdemand throughout Britain for more ac- (51.0percent), but is still not as good as 0.2-m spatialresolu- curate DEMs,particularly in sensitive areassuch as those lia- tion in mono (76.0percent). ble to flooding. DEMscurrently available on a national level The identification and interpretation of buildings and do not fuIfilI the requirementbecause they are generated roads is similar between mono 0.2-m and stereo1-m spatial from 5-m vertical interval contour data, and it is well known resolutions;however, identification of fencesand hedgesis that DEMscreated from such data are not as accurateas DEMs significantly worse and, unfortunately, these form the maior- createddirectly from stereoimagery. Companiesare now in- ity of rural features, terestedin much higher accuracyDEMs, with particular de- The results for the stereoscopicsurvey at 0.2-m spatial mand from the insurance sector of the market. resolution are disappointing as they appear to provide simi- The aim of this aspectof the project was to seewhat lar results for the same resolution at mono. This is unusual DEMaccuracy could be achievedusing 1-m spatial resolution and may be as a result of two different operatorsdoing the satellite sensorimagery. Again, simulated 1-m spatial resolu- survev over a verv small test area. tion aerial imagery was used togetherwith SARinterfero- Fiom the limited accuracyassessment carried out, re- grams from ERS1/2 tandem data. sults from the stereowork indicate buildings and roads hav- Work on this aspectof the project was carried out at ing an RMSEof approximately 1.6 m, and fencesand hedges University CollegeLondon (uct ). approximately 2.3 m. This is significantly better than the ac- cuiacy using the monoscopic methods, probably becauseof DEMs from Aerial Imagery at L-m Spatial Resolution the ground control used to set up the model. Topographic The DEvtsfrom the aerial imagery with 1-m spatial resolution detail control was used for the creation of the orthorectified were automatically createdon two different systems,ucl-- images, whereas GPScontrol was used during the block ad- 3DIM(winner of the 1990 British Computer Society Technical justment for the stereoevaluation. Theseresults indicate Innovation Award) (Muller, 1989) and Zeiss'sPHODIS soft- buildings and roads being within the expectedaccuracy for copy workstation which usesMATCH-I developed by INPHO, 1:2,500-scaleNTD data, but fencesor hedgesfall outside the GmbH, Stuttgart,Germany. accuracvexDected. Resultshave shown that there is considerablepotential The same assessmentswere also undertaken in a moor- for creatingDEMs for use in national mapping from 1-m spa- land (r:ro,ooo-scale)area, where correct feature identifica- tial resolution satellite imagery using standard off the shelf tion and interpretation was around 75 percent and the RMSE DEMgeneration packages. Work still needsto be carried out was approximately 2.2 m, which is well within the expected to evaluatethe possibility for automatingthe work flow, and accuracyfor 1:10,000-scaleNTD data. making more of the available os data to define breaklines, Imagery at l.-m spatial resolution from satellite sensors thus making editing of the DEMsmore efficient. should not be ruled out for survey using stereomethods, be- Preliminary accuracy results for the nnlvls created from causeinterpretation may be improved using real rather than aerial imagery scannedat a 1-m spatial resolution show that simulated imagery. Results from the simulated imagery have the RMSElot Z is in the ranse of 1.5 to 2 m after the nnv has

TneLe8. CorurusroNMnrnrx roR 0.2-rv Sperrnl Resolurroru lvncEnv - SreReoscoptcEvnrunrtou Features Fences, Features InterPreted Road Hedges, Missing Identified Correctly Feature Type Buildings Pavement etc. Features Total (%) ('/")

Buildings 13 0 13 100 100 Road Pavement 50 1- 51 9B SB Existing Fences, Hedges, etc. 1.2 T 93 18 724 d5. J NTD data Additional Features 1 0 13 0 14 Total 26 ol 106 1g 202 Feature capture accuracy (Yo) 96.2 100 87.7 Conect feature capture accuracy (%) 50 s8 87.7

Aueust 1997 PE&RS been edited. It is predicted that high resolution satellite sen- sults were obtained from Leica's Helava system. The DEMs sors will provide more accurate heights than will simulated needed to have grid spacings of either 1 or 3 m to be able to data at the same resolution because of the improved base-to- extract heights for sufficient numbers of small buildings; height ratio. however, technological advances will be needed to produce DEMs at this high grid spacing given the speed of current DEMs from ERS1/2 Tandem Data commercial systems for full swaths envisaged with future IfSAR-DEMs were created from the ERS 112 tandem and ERS-2 1-m spaceborne imagery. 35-day repeat data, using the uCL-3DIM (I~SAR)processing sys- Assessments of whether the minimum, mean, or maxi- tem (mentioned previously) and the ESA-distributedISAR mum heights within the buildings should be used, showed software from the Politecnico di Milano (POLIMI) coupled that the maximum height was the most accurate. From the with a phase coherence estimator developed at UCL (Ferretti small sample taken, these maximum points had elevation et al., 1996). RMSEs ranging between 1.5 and 3 m, compared with the I~SAR-DEMsat a 10-m grid spacing were created using mean points which had elevation RMsEs ranging between 3.5 densification of existing os national height data at a 50-m and 6 m and the minimum points which had elevation grid spacing together with DEMs with a grid spacing of ap- RMSEs ranging between 4 and 10 m. proximately 100 m, which are available for around two- The method used showed that 1-m spatial resolution sat- thirds of the Earth's surface. The accuracy when compared ellite imagery could have potential for creating a national 3D with the National Height Dataset (NHD), which has an RMSE building model if the processes were automated, which of 1.25 m, showed that the RMSE ranged between 5.7 m and would produce a much cheaper source of building heights 20 m for the IfSAR-DEMs; however, the accuracy may be better than making manual measurements off stereo spaceborne im- than the figures suggest because the NHD represents "bare agery or aerial imagery with 1-m spatial resolution. However, ground" and the I~SAR-DEMgives the "observable surface" this much reduced cost would need to be traded against the with vegetation, buildings, etc. The accuracy appeared to be lower accuracy and completeness. directly correlated with phase coherence, with the high phase coherence, giving better accuracies than low phase co- Land Use herence. Land-cover mapping at local to national scales has been hin- The phase coherence varied widely between tandem dered by the relatively coarse spatial resolutions of satellite pairs and was always poorer for the %-day repeat data even sensor imagery. For example, the Land Cover Map (LCM)of from the same season and only a short time apart. The night- Great Britain was generated using Landsat Thematic Mapper time data showed higher phase coherence compared with the (TM) imagery with a spatial resolution of 30 m and a rou- daytime when there were more atmospheric effects. tinely mapped parcel size of greater than 1 ha (Fuller et al., 1994). At this scale, a considerable amount of detail and, 3D Building Modeling therefore, information is lost. There is a growing demand to model the world as we recog- The finest spatial resolution currently available for mul- nize it in three dimensions for specific applications. It is safe tispectral satellite sensor imagery is that provided by the to say that the next generation of data users, who have been Systeme Probatoire d'observation de la Terre (SPOT) High introduced to realistic 3D PC games at an early age, are un- Resolution Visible (HRV) sensor with a spatial resolution of likely to tolerate anything other than an interactive model to 20 m by 20 m. Within the next few years, several satellite test urban planning scenario concepts or environmental im- sensors are proposed which will provide MSS imagery with a pact assessments. 3D city models have a vast number of ap- spatial resolution of 4 m by 4 m (Aplin et al., 1997) and, plications in the planning, development, and management of possibly, lower. These new sources of imagery with fine spa- urban areas (Mason, 1996). tial resolution may increase the capabilities for generating The aim of this aspect of the project was to see if 1-m land-cover information at local to national scales. In spatial resolution satellite imagery could be used to automat- particular, the minimum parcel size at which mapping takes ically create a national 30 building model. place will be considerably smaller than that of contemporary Work on this aspect of the project was carried out at surveys, resulting in an increase in geometric detail and geo- University College London (UCL). metric accuracy. The DEMs were automatically created using three sys- Associated with an increase in spatial resolution is, com- tems: the Leica Helava softcopy workstation, which uses an monly, an increase in the internal variability within land- algorithm which they developed called Hierarchical Relaxa- cover parcels. Thus, while the information content of the tion Correlation; the Zeiss PHODIS (MATCH-T) softcopy work- imagery increases with the increased spatial resolution, the station; and the UCL-3DIM image processing system accuracy of land-cover classification may actually decrease mentioned earlier. The Leica Helava system did not have the on a per-pixel basis. For example, within agricultural fields, same limitations for DEM grid spacing as either the Intergraph ridge and furrow patterns, tramlines, patches of moisture, (used in other aspects of the project) or the Zeiss systems, and footpaths can all lead to mis-classification of individual which were both running MATCH-T DEM software. The Leica pixels. A potential solution was explored by Pedley and Cur- softcopy workstation allowed DEM grid spacings down to 1 m ran (1991) who utilized digital vector data to obtain averages from imagery with 1-m spatial resolution whereas both the (or modal values) for each vector polygon to increase the ac- Zeiss and Intergraph systems were limited to 10 m. The UCL- curacy of land-cover maps obtained from SPOT HRV imagery. 3DIM processing package allowed grid spacing down to 3 m. This has the advantage that the mis-classified pixels within A range of DEMs were created where possible from the each polygon are averaged out. three systems using I-, 3-, 5-, 8-, and 10-m grid spacings for In this part of the project, Compact Airborne Spectro- an assessment of the impact of different grid spacings on the graphic Imager (CASI)multispectral imagery and NTD vector ability to extract building heights. Building objects were then data were combined to generate land-cover information at automatically extracted from the NTD data and merged with the local scale, with the general aim of developing methods the DEMs in the ARCIINFO GIs package to enable calculation of for use at the national scale. CASI imagery with a spatial res- minimum, mean, and maximum heights within each build- olution of 4 m by 4 m was obtained on 31 May 1996 at an ing object. area near St. Albans in Hertfordshire. Three study areas (two Analysis showed that the most accurate and detailed re- agricultural and one urban) were selected for land-cover clas-

PE&RS August 1997 sification. These data were geometrically corrected using an new U.S. satellite systems with 1-m spatial resolution im- extensive coverage of ground control points (GCPS),a global agery become available. bicubic transform, and the nearest-neighbor resampling algo- 3D vectors heighted using DEMS created from the aerial imagery with 0.2-m spatial resolution (used as a baseline) rithm. The geometrically corrected CAsI imagery was then would provide an accuracy equivalent to the existing NHD classified using several per-pixel techniques, including a and therefore could be used for filling in the gaps in the NHD maximum-likelihood classifier. Between four and six NTD along roads/railways, etc. tiles were obtained for each study area, and these data were cleaned and built into polygons. The polygon data were then rasterized to a grid with a cell size of 4 m by 4 m and were Topographic Change Detection then integrated with the classified CASI imagery within the Comparison of DEMs from Two Epochs. Change could be de- ArcIInfo geographic information system. The integrated data tected using DEMs created from aerial imagery with both 1-m set created unique identifiers for individual land-cover poly- and 0.2-m spatial resolutions. However, if an automated gons and enabled the extraction of the modal value of classi- method of change detection is required, then the DEMs must fied pixels for each polygon. have as few blunders in them as possible so that genuine fea- The accuracy of the per-polygon classification was found ture change can be clearly identified. For this to occur, good to be far greater than that of the per-pixel classification. In quality imagery must be used for the automatic DEM creation. This may be in the form of satellite imagery with 1-m spatial addition, the approach allowed the introduction of various resolution for the detection of buildings and areas of vegeta- useful factors into the analysis such as the extraction of a tion. In order to detect finer features such as fences or small (per-polygon) mixed woodland class as a function of the hedges, a spatial resolution of less than 1 m is likely to be (per-pixel) deciduous and coniferous woodland classes. required. Further, the extraction of the percentage cover within each Masking a New DEM with Building Polygon Data. The system polygon of the modal class provided a means by which to as- used to create the DEMS had a software limitation which did sess the uncertainty associated with each per-polygon class, not allow DEM grid spacing less than 10 m for imagery with and a flag for the need for remedial action. 1-m spatial resolution. This grid resolution was too coarse to enable large-scale rural topographic change to be detected. Better results would have been achieved using Leica's Helava Conclusions softcopy workstation which allowed a grid resolution down to f m; unfortunately, this workstation was only available for Space Imagery with l-m and 4m Spatial Resolutions the DEM and 3D modeling aspects of this project at UCL. At this stage, the reliability of data supply from the new high resolution satellite sensors is unknown. The first of these Topographic Mapping new sensors to be launched is scheduled for mid-1997 (Earthwatch's EarlyBird - 3-m panchromatic spatial resolu- Using aerial imagery with 1-m spatial resolution and plotting tion) and, until data start to become available, this will re- in mono proved not to be realistic with the current survey main unknown. Concern also exists over the potential use specification because only 51 percent of features in rural (1: 2,500-scale) areas and 55 percent in moorland (1:10,000- within UK because of the cloud cover, duty cycle, and flexi- scale) areas could actually be correctly identified and bility of the satellites themselves. interpreted from the imagery. The data used for this project have simulated only the Stereo plotting using I-m spatial resolution resulted in 65.9 pixel size and not the geometry of the new high resolution percent of features in rural (1:2,500-scale)areas and 75 per- satellites; this has allowed us to use pre-existing commercial cent of features in moorland (1:10,000-scale) areas actually software and relevant test sites. In practice, the software and being correctly identified and interpreted from the imagery. systems will need to be modified to handle and process the From the limited spatial accuracy tests that were carried out new data but, from recent studies, it seems that few compa- during the project, it was identified that mono survey from nies are gearing up to do this. The following problems need aerial imagery with 1-m spatial resolution was outside the ex- to be dealt with: pected accuracy of the rural mapping, whereas it was border- line for stereo survey. However, the accuracy was well within special software will be required for establishing the interior that expected in the moorland areas using stereo methods. and exterior orientation, computation of elevations, produc- From these results, stereo photogrammetric methods using tion of orthoimages, stereo viewing, and measurement; 1-m spatial resolution imagery could have potential for 1: software to deal with the accurate data recorded for both po- 10,000-scale mapping and smaller; further work should be sition and attitude will be needed if these are to be available done to assess the real 1-m spatial resolution satellite data with the spaceborne image data; when it becomes available because it is expected that the real software will be needed to handle along-track and cross-track imagery will provide better results than did the simulated stereo with large tilts; and imagery used in the project. improved hardwarelsoftware will be required to enable processing of images with improved pixel depth (11 bits expected from companies like Space Imaging). DEMs Aerial Imagery with 1-m Spatial Resolution. DEMs created during the project indicated that there was considerable po- Potential of 1-m Panchromatic and 4m Multispectral Satellite Imagery at the OS tential for creating DEMS in sensitive areas such as flood risk From the evaluations carried out in this project, the follow- areas from imagery with 1-m spatial resolution. However, re- ing conclusions can be drawn: sults definitely point towards the importance of editing the DEM to remove blunders and ground surface features. Further Filling the Gaps in the NHD work needs to be carried out to evaluate DEMs from real satellite imagery and whether there is scope for producing an au- The 3D vectors heighted using DEMs created from the aerial tomatic production system. photographs with 1-m spatial resolution used in this project ERS 11'2 Tandem Data. I~SARDEMS can be used to detect ele- would degrade the accuracy of the NHD if used. However, the vation changes in the Earth's surface due to major engineer- new 1-m spatial resolution satellite imagery may well pro- ing works, etc.; however, it greatly depends on the vide higher accuracy DEMS through the improved base-to- orientation of the SAR sensor with respect to the feature, so it height ratio and increased pixel depth (11 bits quoted by is unlikely that they can be used reliably over the whole of Space Imaging). Further research is recommended when the the LJK. Jan-Peter Muller, Chrystelle Ourzik, and Athula Mandanay- 30 Building Modeling ake (University College London); and Dr. Peter Atkinson, DEMs at 1- or 3-m grid spacing from imagery with 1-m spatial Paul Aplin, Professor Paul Curran, and Dr. Ted Milton (Uni- resolution could be used to generate a national mapping data- versity of Southampton). The Ordnance Survey would also base of maximum building heights for all buildings at least 5 like to thank the British National Space Centre for partially by 10 m in planimetry. There is, therefore, potential for using funding this work. the new 1-m spatial resolution satellite imagery for producing a national building height product. References Land Use Aplin, P., P.M. Atkinson, and P.J. Curran, 1997. Fine spatial resolution satellite sensors for the next decade, International Journal 4-m spatial resolution multispectral imagery from the new of Remote Sensing (in press). satellite sensors could be used for populating and maintain- Ferretti, A., A. Monti-Guarnieri, C. Prati, and F. Rocca, 1996. Multi ing land-cover classes using per-field classification as well as baseline interferometric techniques and applications, Proceed- some land-use classes using a textural classifier. Automation ings ESA FRINGE96 Workshop, University of Zurich, 30 Septem- and development of the procedures developed could make ber - 2 October. this into a realistic production flowline. Fritz, L.W., 1996. The era of commercial earth observation satellites, Photogrammetric Engineering b Remote Sensing, 62(1):3945. General Comments Fuller, R.M., J. Sheail, and C.J. Barr, 1994. The land of Britain, 1930- Because of the lack of real satellite imagery with 1-m (pan- 1990: A comparative study of field mapping and remote sensing chromatic) and 4-m (multispectral) spatial resolutions, simu- techniques, The Geographical Journal, 160(2):173-184. lated data were created using aerial photography. However, Hartley, W.S., 1991. Topographic mapping and satellite remote sens- throughout the different aspects of the project it was felt that ing: is there an economic link? International Journal of Remote the quality of the imagery was poorer than real satellite im- Sensing, 12(9):1799-1810. agery would provide. Consequently, the results identified in Havercroft, M., and D. Fox, 1995. The creation of processed satellite the project should be taken as an indication of the potential imagery products compatible with Ordnance Survey digital of satellite imagery and, where potential for use is border- mapping, Association of Geographic Information, 1993 Confer- line, further work should be carried out when the actual data ence Proceedings, pp. 3.9.1-3.9.4. from the new U.S. high spatial resolution satellite sensors be- Mason, S., 1996. Photogrammetric reconstruction of buildings for ~IJ city models, South African Journal of Surveying 6. Mapping, comes available. 23(5):249-262. This project has been very wide ranging and, as such, Muller, J.-P., 1989. Real-time stereo matching and its role in future has only scratched the surface in analyzing the potential of mapping systems, UK Surveying and Mapping, RICS, University the forthcoming commercial U.S. high spatial resolution sat- of Warwick, 15 p. cllite sensors. However, results have been promising and will Murray, K.J., and J.E. Farrow, 1988. Experiences producing small certainly stimulate further research work. scale line mapping from SPOT imagery, International Archives of Photogrammetry and Remote Sensing, Comm 11, pp. 407421. Acknowledgments Ordnance Survey, 1995. Ordnance Survey Annual Report and Ac- The first author would like to thank everyone for all of their counts 1995/96,43 p. hard work on this project, including Keith Murray, Neil Pedley, M.I., and P.J. Curran, 1991. Per-field classification: An exarn- Smith, David Holland, Paul Russell, Lynne Cowan, and Steve ple using SPOT HRV imagery, lnternational Journal of Remote Worth (Ordnance Survey); Professor Ian Dowman, Professor Sensing, 12:2181-2192.

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