COVER ARTICLE

Digital Aerial Orthobase for Cadastral Mapping

P. Srinivas & V. Raghu Venkataraman &

I. Jayalakshmi

Received: 28 June 2011 /Accepted: 26 October 2011 /Published online: 23 November 2011# Indian Society of Remote Sensing 2011

Abstract Large scale aerial photographs were ac-quired for one entire district of Andhra Pradesh in thesouthern India encompassing approx. 10,000 sq.kms.The voluminous data was processed using digitalphotogrammetry techniques to generate seamlessdigital orthoimages as a base map for cadastralmapping applications. Historically the cadastral map-ping was carried out with traditional surveyingmethods such as ETS, theodolites not at regularintervals. With the advent of modern surveying &remote sensing techniques, generation of DigitalCadastral Database for Land Information System(LIS) is possible. The trends of cadastral mappingstarted with individual plan of survey of parcels withlocal datum and arbitrary map projections. This studyessentially required an accurate and standard spatialreference for seamless cadastral mapping over theentire Area of Interest (AOI) in single datum andprojection. Towards this a spatial reference in WorldGeodetic System (WGS 84) datum with UniversalTransverse Mercator (UTM) projection was estab-lished. The terrain in the study area is moderatelyundulating and the relief due to manmade featureswas not so significant. The aerial orthobase was foundsuitable for delineating and measuring the individual

parcels information. A good GCP configuration,triangulation accuracy and reliable and consistentDigital Elevation Model (DEM) was ensured thegeneration of Digital aerial orthobases with anaccuracy of better than 25cm over a distance of1000m. The orthobase was used for identification,delineation of the cadastre parcels and most impor-tantly to validate the aerial orthobase with the fieldmeasurements.

Keywords Orthobase . UTM .GPS .WGS 84 .

Photogrammetry . LIS . Cadastral mapping . DEM

Introduction

Historically the cadastral maps are prepared usingconventional direct methods such as chain survey orplane tabling along with theodolites and moderninstruments such as Electronic Total Station (ETS)with GPS. A land parcel is the basic unit in thecadastral system. Each parcel is given a unique parcelnumber and address, which together with parceldimensions are shown on a cadastral survey map.The conventional methods of preparation of cadastralmaps involve lot of time, cost and manpower to coverlarge area of extents (Eugene H. Silayo 2005). Thesemaps are prepared in local datum and projectionswhich are not connected to any common nationalframe of coordinate system. The land records aremaintained at taluk office in volumes and are

J Indian Soc Remote Sens (September 2012) 40(3):497–506DOI 10.1007/s12524-011-0183-2

P. Srinivas (*) :V. R. Venkataraman : I. JayalakshmiISRO/Department of Space,National Remote Sensing Centre,Balanagar, Hyderabad AP–500625, Indiae-mail: srinivas_p12@rediffmail.com

basically available in two types, first one as map datastored in Field Measurement Books (FMBs), and thesecond one as Jamabandi, Khasra Girdawari, Pedigreesheets etc. pertaining to each individual land holdingprimarily classified into land details and the owner-ship details. These land records which are stored inpaper format are difficult to maintain. Depending onthe accuracy needed for the cadastral study, differenttechniques and technologies such as direct methodsand indirect methods or combination of them can beemployed (Corlazzoli and Fernandez 2004).

Presently the methodologies for the preparation ofcadastral maps are carried out by indirect surveyingmethods using remote sensing data either from aerialor satellite platform. Cadastral maps are now preparedusing high resolution satellite data of various spatialresolutions from Cartosat-1 and 2, IKONOS andQuickbird images for parcel information correlation,but could not be effectively used for measurement ofindividual parcels in the field (Oğuz et al. 2006). Forpre-cadastral projects the indirect method of survey-ing such as creation of cadastral maps using highresolution satellite data can be carried out (Corlazzoliand Fernandez 2004).

In this study aerial remote sensing data at 1: 10,000scale was used for the preparation of the digital aerialorthoimages and subsequently as base map for cadastralmapping. This method involved more of lab / systemintensive rather than field intensive activities, therebyminimizing the field visits. The GPS technology hasimproved the accuracy, and reduced the time and cost ofthe ground control surveys (Eugene H. Silayo 2005).The validation of the aerial orthobase was carried outin the field against the higher order measurementsmade by using conventional ground methods and alsowith the age old cadastral maps. This method waseconomical with respect to the resources, time andcost to cover large area of extents (Eugene H. Silayo2005). The cadastral maps prepared are in digital formand easy to maintain. Another advantage of thepresent methodology is that the cadastral maps areprepared in geodatabase format i.e., linking of spatialand non-spatial information such as attaching theindividual parcels with the attributes such as ownershipdetails etc.

In this study the critical requirement for cadastralmapping is that it needs an accurate spatial reference formeasurement of parcels and for identification anddelineation of the property boundaries. Cadastre

reference is composed of spatial reference data i.e.,geodetic control with well distributed control network ofpoints and digital aerial orthoimages, parcel informationand other major boundaries in a nested form. Spatialreference begins with a geodetic network system i.e.,Zero order stations that has been densified to higheraccurate spatial reference network for the intended studyarea. The cadastre spatial reference is derived throughthe GPS and digital photogrammetry techniques for thisstudy area. It is essential to build and integrate the parcelgeometry and supplemental information such as DigitalElevation Models (DEM) for vertical integration.

The supplemental information such as DEM anddigital aerial orthoimages derived from large scale aerialphotographs is necessary to reference the cadastralinformation to the real world coordinate system. Theintersection angle of the stereo pair affects the accuracyof the DEM. The larger the intersection angle, the betterthe DEM. Terrain affects the DEM accuracy consider-ably. With an increase in slope, the accuracy decreases.A strong geometric combination should be selected toproduce a good DEM (Chen et al. 2007)

Digital aerial orthoimages require a very accurateterrain model with the support of basic terraininformation such as break lines, form lines, cutoutareas etc. Measurements made on the digital aerialorthoimages are comparable to the field measure-ments made on the parcels for evaluation andaccuracy assessment. The parcel boundaries and othergeographic features derived from the digital orthobaseand field, form the Cadastral Spatial DatabaseInfrastructure (CSDI).

Objectives of the Study

The study was initiated with the following objectives:

✓ To generate seamless digital orthobase fromaerial photographs.✓ To validate the accuracy of the digital aerialorthobase for preparation of the cadastral maps.

Study Area

The study area covered the rural areas of entireNizamabad district of Andhra Pradesh state in southernIndia and is located between 18° 05′ N and 19° 00′ Nlatitudes, 77° 40′ E and 78° 37′ E longitudes covering an

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area of approximately 10,000 sq kms. The geographicalextent of the study area is 6,500 sq.km.

The boundaries of study area are Karimnagar districtin the east, Medak district in the south, Nandhedu districtin west and Adilabad district in the North directions.Nizamabad district is primarily an agrarian district withalmost 80% populace living in the rural areas.

Database

The data acquisition was carried on aerial platform at1: 10,000 scale for the entire district covering totalarea of 10,000 sq.km. The resolution of the aerialphotographs used in this study is 12.5 cm and thedetails of the data acquisition such as aerial camera,film type, scale of aerial photograph, flying height etcare shown in Table 1.

Georeferencing of aerial images require groundcontrol points (GCP), which were sharp and easilyidentifiable on the aerial image as well as on theground and more importantly for accurate and precisemeasurement of the GCP. For this study area, 283GCP’s were collected and the details such as time ofobservations, epochs, average RMSE of the GCP’s etcare shown in Table 2.

The analog aerial photos were converted to digitalform so as to process the data in digital environment.Aerial photographs are scanned @ 16 μm resolutionusing high precision photogrammetric scanner withgeometric accuracy of ±1 to 2 μ. Each aerial frameoccupied 200 MB of disk space and 7,500 framescovering entire study area totals to 1,500 GB (1.5 TB).In addition intermediate processed files required 3 timesthe disk space occupied by the aerial frames.

The other database / information used in this studyare processed Kinematic GPS data i.e., coordinates ofexposure of each frame and calibration parameters ofthe camera i.e., calibrated focal length, coordinates of

fiducial marks and Principal Point of Auto collimationand radial lens distortions.

Methodology

Flight Planning, Aerial Photography and GroundControl Survey

Flight planning for aerial photography was carried outusing World Wide Mission Planning (WWMP)software and the flight plan data was imported intoComputer Controlled Navigation Software (CCNS),which is installed in the aircraft. The aerial photog-raphy was planned as per the details mentioned in theTable 1. Three base stations were established in thestudy area by connecting to Ground Control PointLibrary (GCPL) of ISRO. Around 283 GCP’s (includingcheck points, pre-targets) as shown in Fig. 1 werecollected in the field using Geodetic GPS receivers indifferential network mode of operation. At each GCPminimum of one hour observations was made @ 30 sepoch using Leica SR 520 Geodetic GPS receivers.

Aerial Triangulation and Block Adjustment

Digital/softcopy photogrammetry techniques wereutilized in this project for aero triangulation and blockadjustment, DEM and digital aerial orthoimagesgeneration. A high end photogrammetry workstationwith SOCETSET 5.0 version and ORIMA blockadjustment software was used in this project (Bacheret al. 1999).

The input data used for photogrammetry processingis the scanned aerial images with 16 μm resolution,camera calibration (for internal geometry of the sensor),Kinematic GPS data and GPS data (for externalgeometry of the sensor). The aero triangulation processinvolved the determination of six parameters (X,Y,Z,

Table 1 Details of the aerialphotography S.No. Activity Specifications

1 Camera used Metric Aerial camera RMK TOP 30/23

2 Film type Panchromatic 2,405

3 Scale of photography 1: 10,000

4 Frame format 240 mm × 240 mm

5 Overlaps Forward–60 to 65%, Lateral–20 to 25%

6 Flying height 3,000 m

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kappa, phi, omega) of each aerial photograph andcoordinates of unknown tie points using known GCPs.The use of Kinematic GPS data (for each photograph)has reduced the number of GCP’s in the field. The tielines flown at the periphery of the study area was alsoused in the aero triangulation, which has helped in thestabilization of the block.

The most important aspect in this study is that theentire block of 7,422 frames were photogrammetri-cally adjusted as a single block which required verygood GCP configuration, better accuracy of GCP’sand Kinematic GPS data and very good quality of thescanned aerial image. The aero triangulation / blockadjustment process is an iterative process and required

good logical analysis to converge the block.Out of 283 GCPs collected in the field using GPS,

70% of points were used for the block adjustment andremaining 30% points have been used as independentcheck points. The 70% of the GCPs were used for theblock adjustment to transform the image coordinatesto ground coordinates. The residuals of few groundcontrol points after the aerotriangulation / blockadjustment are shown in Table 3. The block wasadjusted using ORIMA robust bundle block adjust-ment software with Least Squares algorithm. Sigmanaught of the block, standard deviation of the groundcoordinates and RMSE are the measures of triangulationaccuracy (Kocaman 2005).

Table 2 Details of GPSobservations S.No. Description Specification

1 GPS receiver Leica SR 520 dual frequency ±5 mm+0.5 ppm

2 Sampling rate 30 s

3 GDOP <4

4 Occupation time 1 h

5 Baseline length <50 Km

6 Geodetic reference GCPL reference network of ISRO

7 Data processing Leica Ski pro software

Fig. 1 GCP configurationfor entire Nizamabad district

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DEM Generation

DEM is the digital representation of the earth’s reliefthat consists of ordered array of elevations relative toa datum whereas Digital Terrain Model (DTM) is adigital representation of the both planimetric detailsand height information, which describes the continuousdescription of the surface.

In this study, manual measurements of the masspoints at regular intervals and capturing morpholog-ical features such as break lines, form lines, cutoutareas etc. in stereo mode (Dymond et al. 1992) wascarried out so as to represent the continuous andsmooth terrain accurately. This study has adapted thedata sampling to the type of landscape it representedand to the accuracy needed for the DEM and digitalorthophoto application.

The accuracy of the DEM was validated by usingtwo different methods. The first one is checked with3D visualization by overlaying the finer DEM ontothe stereo model in the photogrammetry system. Thesecond one is checked by comparing the DEM heightvalues derived through photogrammetry process withthe corresponding features in the field derivedthrough GPS process (Kraus et al. 2004).

Digital Orthophoto Generation

An orthoimage is an image that is geometricallycorrected or ortho rectified so that the image scale isuniform from edge to edge. Orthoimages are cor-rected to remove the terrain effects and distortionsthat result from the camera lens and the angle with

which the image has been taken. The goal of orthorectification is to create an image where the distances,angles and areas can be measured directly.

Digital orthoimage typically has geographic refer-ence to the earth such as UTM or state planecoordinate system, so that each pixel in the imagecan be accurately located. Generation of digital aerialorthoimages depends on the geometric quality ofDEM, exterior orientation parameters of the imageand the radiometric quality of the image (Eminnur etal. 2006).

The factors which influenced the planimetricaccuracy of the digital orthoimage are the errorsintroduced by the DTM, control point quality anddistribution, rectification procedures (resection bybundle block adjustment), geometric errors from thesensor and final pixel size of the image in groundunits.

Preparation of New Cadastral Maps

The new cadastral maps were prepared afresh usingdigital aerial orthoimages using 2D drafting package.The individual parcels, water bodies, religious struc-tures and other prominent features were extractedfrom digital aerial orthoimages in different layers.These cadastral maps are in UTM projection with 45zone number, WGS84 datum. The maps are seamlessacross the villages / taluks boundaries consistent withthe project specifications.

These cadastral maps were verified in the groundfor the individual parcels boundaries and otherprominent features. The parcel numbers for individualparcels were collected from the field and incorporatedonto the new cadastral maps by the Survey Settlementand Land Records (SS and LR), Department ofAndhra Pradesh state.

Accuracy Assessment

Between Digital Orthophotos and GroundMeasurements

The accuracy of the digital aerial orthoimages wasassessed in eighteen villages well distributed over theentire Nizamabad district. In each of the villages,points were selected simultaneously on the ortho-image and on the ground. For rural areas, distanceswere measured precisely between the points selected

Table 3 Residuals at few GCP’s after Aerotriangulation/blockadjustment

GCP ID Residuals (X,Y,Z) in metres

475001 0.0094 0.0238 0.0535

475002 −0.0526 0.0042 −0.1471475005 −0.1358 0.0687 0.0144

475007 0.046 0.0533 −0.0469475008 −0.0777 −0.0478 0.0258

475009 −0.0045 0.0812 0.0253

475010 0.0237 −0.1562 −0.116475011 −0.2128 0.0693 0.0892

475013 −0.0883 0.0692 0.0325

475014 0.0739 −0.1142 −0.1548

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on the digital orthoimage using AutoCAD software,whereas in the case of urban areas, distances weremeasured in the stereo photogrammetry system due tothe relief of the structures. Distances were measuredbetween the points in the field using ground basedsurveying instruments such as ETS and tape. Thevariation of the parcel area between the ETS data andthe one derived from the digital orthoimage dependdirectly on the size and the topography of the area(Corlazzoli and Fernandez 2004). Digital aerialorthoimages were generated using very high accurate

DTM (corrected for relief of the terrain) and hencewere suitable for making linear measurements on thedigital orthoimage. The corresponding linear meas-urements from digital orthoimage and ETS werecompared and the mean is computed approx. 12 cm,which is meeting the cadastral map requirements.Therefore linear measurements between the pointswere measured for the parcel boundaries instead ofarea of individual parcels. Table 4 shows thecomparison of measurements made on digital ortho-image and on the ground.

Table 4 Accuracy Assessment of Digital aerial orthoimages based on measurements made on the ground

S. No Village Name ETS distance (metres) Distance on orthophoto (metres) Difference (metres)

01 Pata Rajampet 108.971 109.035 0.064

02 Rampur 188.360 188.511 0.150

03 Rampur 88.249 88.279 0.030

04 Arsapalli 360.185 360.082 0.103

05 Khurdgaon 95.067 95.107 0.040

06 Khurdgaon 61.557 61.751 0.194

07 Varni 134.659 134.748 0.089

08 Bichkunda 177.775 177.964 0.189

09 Bichkunda 122.969 123.205 0.236

10 Timmapur 599.729 599.979 0.250

11 Timmapur 210.713 210.864 0.151

12 Gandi Masanipet 31.647 31.681 0.034

13 Misanpalle 349.892 350.110 0.218

14 Misanpalle 274.542 274.417 0.125

15 Vencheral 226.525 226.568 0.043

16 Venchetal 50.376 50.488 0.112

17 Bhandarpalli 71.008 71.018 0.010

18 Bhandarpalli 55.872 55.926 0.053

19 Bhandarpalli 98.242 98.268 0.026

20 Baridipur 249.085 249.175 0.090

21 Baridipur 105.331 105.428 0.097

22 Biknali 223.886 224.126 0.240

23 Biknali 29.632 29.746 0.114

24 Busapuram 109.321 109.402 0.081

25 Busapuram 152.707 152.524 0.183

26 Koparga 57.414 57.508 0.094

27 Koparga 149.239 149.277 0.038

28 Pentakalan 165.755 165.665 0.090

29 Pentakalan 121.452 121.559 0.107

30 Dichpalli 100.989 101.165 0.176

31 Dichpalli 307.042 307.417 0.375

32 Lingareddi 70.580 70.545 0.035

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It is observed that 90% of the measurements madeon the digital aerial orthoimages and on the groundhad a variation of 25 cm in planimetry. The variations

in remaining 10% measurements are beyond 25 cmwhich may be due to the transfer of the control pointsfrom the ground onto the digital aerial orthoimages.

Fig. 2 Digital Orthobase for Cadastral maps (a) old cadastre and new cadastre (b) new cadastre overlaid on the Digital Orthophoto

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It was suggested to use a modern measuringinstrument such as ETS or GPS which gives betteraccuracy for assessing the digital aerial orthoimages.

Conventional surveying instruments such as tapes andchains cannot be used for measurement due to factorssuch as undulating terrain, sagging, improper ranging

Fig. 3 Digital Orthobase for Cadastral maps (a) old cadastre and new cadastre (b) new cadastre overlaid on the Digital Orthophoto

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and calibration coefficients. All the above mentionedfactors are cumulative in nature and will lead toerroneous results if proper precautions are not taken.

Between the Digital Orthophotos and Cadastral Maps

The accuracy of the digital aerial orthoimages wasassessed on the ground for a pilot area pertaining toLingareddy mandal in Nizamabad district and alsocompared with the old cadastral map at 1: 5,000 scaleavailable with the Survey Settlement and LandRecords (SS and LR) Department of Andhra Pradeshstate. The Fig. 2a shows the present drastic changes inthe ground with respect to the parcel numbers andshape of the cadastre compared with the age oldcadastral map. Figure 2b shows the cadastre overlaidon the digital orthoimage. Figure 3a and b showsanother sample area with the old and new cadastrecomparison and new cadastre overlaid on the digitalorthobase.

The distances made on the new cadastre preparedfrom digital orthoimage are accurate to the ground within20 to 25 cm over a distance of 1,000 m and fulfil therequirement of cadastral maps. Hence the accurate digitalorthobase can be used for the preparation of accuratecadastral maps which have a standard map projection,datum and referenced to the global / national coordinatesystem. The other natural and manmade features can alsobe extracted for other supplementary information.

The age old cadastre was prepared in localcoordinate system without any projections and datum.These scanned cadastral maps were locally georefer-enced to the digital aerial orthoimages with the helpof few common points. Initially the georeferenced oldcadastral maps were validated with the digital aerial

orthoimages for distance measurement of parcelboundaries and in identifying / locating the pillars orcorner stone’s of the individual parcels. It was foundfrom the Fig. 2a and b that the position and shape ofthe parcel boundaries in the ground have changedover a period of time and there was no updation ofthese old cadastral maps. It was difficult to identifythe parcel boundaries in the digital orthobase mapsaccurately and subsequently the very large differences inthe distance measurement of the parcel boundaries. Dueto the above observations it is now understood that theold cadastral maps could not be verified in the groundand the old cadastral maps needs constant updation eitherby using field methods or digital aerial orthoimages.

It is found that there are discrete differences ofdistances between the old cadastral maps and thedigital aerial orthoimages as shown in the Table 5.The reasons for non-systematic differences may bedue to the shrinkage of the cadastral maps, registra-tion error with the digital aerial orthoimages, trans-formation errors from local to standard (UTM)projection and more importantly the changes in theground over a period of time. Hence there are variabledifferences in the distance measurements between anddigital aerial orthoimages and the old cadastral maps.

The comparisons of the distances and percentagevariations between the points made on the digitalaerial orthoimages and the old cadastral map is shownin Table 5.

Results and Discussions

The numerical quality measures sigma, standarddeviation, RMSE in X,Y and Z describe the average

Table 5 Comparison of distance measurement (Digital orthophotos and age old Cadastral map)

S. No. Parcel No. Distance on orthophoto (m) Distance on old cadastral map (m) Difference (m) Percentage variation (%)

1. 1200 265.30 262.50 2.8 1.06

2. 205 97.47 92.5 4.97 5.10

3. 141 61.28 60.0 1.28 2.09

4. 720 71.90 75.0 3.33 −4.315. 67 110.45 107.5 3.64 2.67

6. 648 89.054 85.0 3.10 4.55

7. 833/1 52.525 50.0 2.95 4.81

8. 66 73.64 70.0 2.53 4.94

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measures for the entire block. In this study the resultsof the geometric stability of the block are reported.

The apriori sigma of the block is set to ½ of thepixel size i.e., 8 μm and a good agreement betweenapriori and posteriori sigma was required to achievehigh accuracy. In this study the posteriori sigma / sigmanaught achieved for the block is 8.2 μm. Priori StandardDeviation for GCP’s is 5 cm and for KGPS data is 10 cmin planimetry and 15 cm in height.

RMSE of the control points achieved after theblock adjustment was 10 cm in planimetry and 6 cmin height. The maximum change at the control pointsin the block is 29.8 cm in X, 40.5 cm in Y and 20 cmin Z. Similarly RMSE of the check points was 15 cmin planimetry and 10 cm in height.

DEM generated from stereo large scale aerialimages was evaluated with the check points distributedall over the study area. The RMSE of the DEM is wellwithin 25 to 30 cm and when translated to orthoimage,standard deviation was within 20 cm as validated in thefield (refer to Table 4).

The selection of the control points in the groundwas very critical in this study and therefore utmostcare was taken in selection of the control points forminimum variations during repeated measurementsby different persons. Ground features which weresharp and identifiable both on ground and digitalaerial orthoimages were selected such as narrow fieldbund junction, culvert corner etc.

Conclusions

Digital aerial orthoimages verified and assessed inthis study had demonstrated the geometric fidelity of25 cm for the distance of 1,000 m, which is consistentwith the project requirements. A good geometrystability block was assured due to the extraction oflarge number of tie points and multi ray intersectionfrom different aerial photographs. Accuracy of thetriangulated models and DEM are the mostimportant components which affect the accuracyof the digital aerial orthoimages. Accuracy of thetriangulated stereo models is dependent on theaccuracy of the ground control points. The

optimum and well distributed GCP’s along withhigh accurate DTM has improved the accuracy ofthe digital aerial orthoimages. The study hadconcluded that the digital aerial orthoimagesgenerated by this methodology using large scaleaerial images can be used effectively for thecadastral mapping applications.

Acknowledgements The authors are grateful to Dr. V KDadhwal Director NRSC, former NRSC Directors Dr. VJayaraman, Dr. K Radhakrishnan and Dr. RR Navulgund fortheir extensive guidance, support and encouragement duringthis study. The authors express their sincere thanks to theAircrew & Aerial survey planning team, Ground control surveyteam, data processing team, with whom it was possible to realizethe study objectives. This study was part of the Bhu Bharathiproject executed by NRSC and Survey Settlement and LandRecords (SS and LR) Department of Andhra Pradesh state.

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