National Land Record Modernization Program

Presented by :

N K Buildcon Pvt Limited, Jaipur

Presentation Layout

NKBPL Scanning and Digitization Resurveys

NKBPL Capabilities

Please visit stall -31 or visit at www.nkbuildcon.com

A Financially sound, ISO 9001 Certified, Multi disciplinary consultancy services provider.

Has completed more than 1200000 Ha or 120000 sqkm surveys using ETS, DGPS in five States for various infrastructure projects

Scanning and Digitization

Scanning of Cadastral Maps Digitization of Cadastral Maps Digitization of Imageries Digitization of Captured Survey Data from

Digital topographical database to Spatial form

Land Record Modernization

Computerization of all land records including mutations, digitization of maps and integration of textual and spatial data.

Survey/re-survey and updation of land records.

Computerization of registration and its integration with the land records maintenance system and development of Geospatial Information System (GIS) and capacity building.

General Methodology : Land Record Modernization

Village (Cadastral) Map

Vectorisation of (Cadastral) Map

Overlap of Cadastral Maps on High resolution Satellite Image

Fused product f High resolution Satellite Image (Cartosat)

Survey

Re-Survey Updation

High resolution Satellite Image, ETS, GPS

Aerial Image, ETS, GPS

Digital Cadastral Geospatial Database

High resolution Satellite Image, ETS, GPS

NoYes

Fewer ChangesLarge Changes

Availability

Analyse changes in parcel (Size, Shape)& identity areas for

Cadastral maps Our existing cadastral maps dates back to 80-90 years.

These cadastral maps prepared using plane table survey and chain survey.

Prepared for assessing revenues on the basis of land parcel area, quality of land and output generated.

These maps need to be brought under standard projection/coordinate system for effective linkage of the developmental plans generated in the GIS environment.

Methodology for Digitization of Cadastral Village Maps

Collection of analog cadastral village maps (sheet-wise) Tracing or re-production of the analog map Scanning of Revenue MapsSheet indexing and scanning of the analog maps (converting analog to raster cadastral images) Grid correction of the scanned (raster) map Feature abstraction from the scanned map Creation of spatial dataAttribute data attachmentOutput Layout s for printing and hard copy evaluation

Collection of analog cadastral village maps (sheet wise)

Before executing the project, sheet-wise cadastral maps have to be collected. The maps should be up-to-date and in good condition The condition should be such that it can be scanned

through a contact (roller) scanner or a flat-bed scanner (prefer flat-bed scanner)

it should not be a cloth mounted, nor be torn or ragged, and not have too many folds.

The control points (tics) should be available The features, Parcel number (khasra no.) and All

symbols (alamats) of the map should be clear and distinguishable.

Scanning of Revenue Maps The following minimum specifications must be adopted while

scanning the cadastral sheets. The cadastral maps are scanned using AO size raster scanner Map should be scanned at 200 dpi Black/White (8 bit grey tone

if all the details are not picked up during scanning, the parameter should be changed to 400 dpi on 24 bit color

The raster image of scanned map should be in TIFF format *.tif (I120501007035101.tif) or *.gif

the scanned map orientation should be upright The raster image of scanned map should be cleaned and de-

speckled to remove noise The measured length and width within bounding box of the

scanned map should be +/- 0.1% of the map manuscript measurements

Dimensional accuracy of the raster data implies total correspondence between the raster data and the original map. The following procedures are used to

achieve dimensional accuracy: 1. Checking for expansion. 2. Checking for contraction. 3. Checking for translation. 4. Checking for rotation.

Tracing and re- Production of the analog map

If the analog cadastral village map is not in condition for direct scanning, then the sheet has to be sent for tracing (preferably on a 75-100 GSM mylar film)

Tracing to be done on 75 micron polyester film and it should be done with 0.1 pen using black ink only

All the features should be traced. The labels should be placed neatly in the center of the

feature with free hand drawing. In case the feature is too small to accommodate the label, it should be placed at a convenient location with a marker arrow.

The heading and legend data should also be traced along with scale, north arrow, sheet no., etc. along with map border.

Sheet indexing All sheets have to be indexed with appropriate index numbers. The index number is to be generated using the village metadata

with respect to the various administrative codes (State, district, tehsil, and revenue inspector/patwari/thana/mouza and village code)

A typical example of index number may be I120501007035101 (IDDTTRRHHHVVVVnn)

Grid correction of the scanned (raster map)

A vector grid is generated on raster map There are 28*20 grids depending upon the map

orientation The length of the grid is 2800 meters on one side and

2000 meters on the other side of map The area of each sub-grid is 100 meters by 100

meters, hence the area is one hectare At least 16 to 20 control points are identified on the

scanned maps as will as corresponding map

800 m

700 m

100 m

100 m

GCP

Feature abstraction from the scanned map

The grid-registered scanned cadastral map sheet is displayed in the background, the required environment settings for digitization are set, and the required features are captured into different layers (based on the feature type)

Error should be within permissible limits for digitization, viz., weed tolerance, coordinate movement tolerance, sliver polygon tolerance, coordinate unit, planimetric errors, fuzzy tolerance, etc

is the process of capturing the point, line, and polygon features as vectors and text as annotation.

Point feature- wells, temples, trees, etc Line feature- roads, canals etc Polygon feature- parcel boundary, village boundary etc

Digitization errors

Some common digitizing errors

overshoot

line digitizedtwice

missingline

spike

undershoot

Digitization errors

Creation of spatial data

1/9th part

1/18th partDigitized map

1/36th Part

Digitization & Feature extraction

• Sample village map (Cadastral) digitized.

Attribute data attachment

Attribute data for each parcel is attached in the text layer.

The parcel number and parcel land use are the two main attributes that are linked to the village polygons.

Parcel number is the primary key for linking of RoR details

Spatial data creation using satellite image

Settlements

Administrative

Boundaries

1/36th part Cartosat

Methodologies for Re-Surveys

Actual Ground Survey-DGPS+ETS GCP+ Satellite Images Hybrid Survey Methodology using Aerial

Photography and Ground Truthing using DGPS/TS

Decision for Technology

Vegetative cover (dense, sparse) Built-up areas Size of survey area Accuracy Timeliness Cost

Land Record Updation using High Resolution Satellite Imagery and Ground Truth with DGPS.

CARTOSAT - 1CARTOSAT - 1PAN - 2.5M, 30 KM, PAN - 2.5M, 30 KM,

F/AF/A

RESOURCESAT-1RESOURCESAT-1LISS3 - 23 M; 4 XSLISS3 - 23 M; 4 XSLISS4 - 5.8 M; 3-LISS4 - 5.8 M; 3-

XSXSAWIFS - 70 M; 4-AWIFS - 70 M; 4-

XSXS

CARTOSAT-2CARTOSAT-2PAN - 1M PAN - 1M

MEGHA-MEGHA-TROPIQUES TROPIQUES

SAPHIR SAPHIR SCARAB & SCARAB &

MADRASMADRAS

20012001

20022002

20032003

20052005

IRS-1C/1D LISS-3 (23/70M,STEERABLE PAN (5.8 M);

WiFS (188M)

INSAT-2E CCD (1KM RESOLUTION; EVERY 30 MNUTESS)

INDIAN IMAGING SYSTEMSINDIAN IMAGING SYSTEMS

IMAGING IMPROVEMENTS 1KM TO 5.8 M RESOLUTION GLOBAL COVERAGE APPLICATION-SPECIFIC

19991999

IRS-P2

LISS-2

IRS-P3 (1996)WiFS MOS X-Ray,

IRS-P4 OCEANSAT OCM, MSMR

IRS-1A & 1B LISS-1&2 (72/36M,

4 BANDS; VIS & NIR)

BHASKARA

RS-D1

19791979

19821982

1988/911988/91

1994199419961996

1995/19971995/1997

19991999

Spatial Resolution of various Satellites

•EVERY 30 MIN. IMAGING

•1M+ SCALES

•CLIMATE/WEATHER•EVERY 2 DAYS IMAGING

•1:250K SCALES

•OCEAN APPLICATIONS•EVERY 5 DAYS IMAGING

•1:250K SCALES

•NATIONAL SURVEYS

INDIAN IMAGING CAPABILITY

•EVERY 22 DAYS IMAGING

•1:50K SCALES

•DETAILED RESOURCES SURVEY

•EVERY 5 DAYS IMAGING

•1:12500 SCALES

•LARGE SCALE MAPPING

•STEREO CAPABILITY

•LOCAL AREA IMAGING

•1:2000/4000/1:8000 SCALES

•STEREO CAPABILITY

…TOWARDS

IRS ID WiFSIRS ID WiFS Spatial Resolution: 188 mSpatial Resolution: 188 m

IRS P6 AWiFSIRS P6 AWiFSSpatial Resolution: 56 mSpatial Resolution: 56 m

IRS IC LISS III MSS ImageIRS IC LISS III MSS Image

Spatial Resolution: 23.5 mSpatial Resolution: 23.5 m

IRS IC LISS III PAN ImageIRS IC LISS III PAN Image

Spatial Resolution: 5.8 mSpatial Resolution: 5.8 m

IRS IC LISS III PAN + LISS –III Merged ImageIRS IC LISS III PAN + LISS –III Merged Image

Spatial Resolution: 5.8 mSpatial Resolution: 5.8 m

Quickbird (PAN sharpened Image)Quickbird (PAN sharpened Image) Spatial Resolution: 61 cmsSpatial Resolution: 61 cms

High Resolution Satellite Image

Vectorised Cadastral Maps

GCP Data DGPS Survey

GCP Collection

Mathematical Transformation Model

Validation of Model(RMS and Residual Error)

Geo-referencing of VillageCadastral Maps

Validation of Individual Village

Edge Matching With Neighboring Village

Village (Cadastral) Map Mosaic Generation at Taluk Level

Validation of Mosaic

Overlay of Village (Cadastral) Mosaic on High-Resolution

Satellite Image

Methodology of Land Record Modernization using High Resolution Satellite Data

Steps for GCPs Collection

Identification of the reference station in the centre of the study area

GPS data collection, using dual frequency geodetic GPS receivers.

Determining the reference station coordinates with reference to International Geodetic Survey (IGS) stations

Identification of GCP locations in the satellite image Collection of GPS data at GCP locations Determining the GCP coordinates, with reference to the

reference station, in DGPS mode Quality verification of GCP coordinates

Geometric Correction

Geometric Distribution:

The perspective of the sensor optics The motion of the scanning system The motion of the platform The platform altitude, attitude and velocity The terrain relief The curvature and rotation of the Earth

The intent of geometric correction is to compensate for the distortion introduced by theses so that rectified image will have the highest practical Geometric integrity.

Systematic or predictable distortions: Can be accounted for by accurate modeling of the sensor and platform motion and the geometric

relationship of the platform with the earth. It is usually the first step in geometric correction.

Unsystematic or random distortions: Geometric registration of the image to be knows ground coordinate system. In practice, image registration to Ground Control Points.

Procedure of Geometric Correction

Locate (register) GCPs

Resampling

Locate GCPs on Satellite Image

Collection of Ground Control Points

Resampling Method

The coordinates of each element in the undistorted output matrix are transformed to determine their corresponding location in the original input (distorted –image ) matrix.

Each cell in the output matrix will not directly overlay a pixel in the input matrix. Accordingly, the intensity value or digital number (DN) eventually assigned to a cell in the output matrix is determined on the original input matrix.

1. Nearest neighbor2. Bilinear3. Cubic

Land Record updation on satellite image

Sample Parcel Map

Attribute data attachment

Spatial data(ARC functions)

Attribute data(INFO or TABLES functions)

1 (Universe polygon)

2 3

4 5

3

COV# ZONE ZIP 1 0 2 C-19 22060 3 A-4 22061 4 C-22 22060 5 A-5 22057

3 A-4 22061

Output Layout

358

Lam

bert A

venu

e

Me

rcator Avenue

Cassini Drive

Cassini Drive

Imhof Drive

Eckert Drive

Miller

Driv

eB on n e S tree t

M o llw e id e S tre et

Grinte

n Stree

t

Go

ode

Stree t

B es se l S tre et

S tree t

R o bins on S tre et

Tisso t S tre et

G a ll S tre e t

Ptole

my S

treet

Orte

lius Stre

et

Clarke S

tree t

To b le r Stre etSnyder S

treet

Krasso

wsk ij S

tree

t

361

378

374

349350

358

377

362

Enum eration Area Map Sym bols

Nationa l S tatistica l O ffice - Ju ly 1998Census 2000

EA

Locality

D istrict EA-Code

Hospital

Church

School

Buildingnumber

Province:D istrict:Locality:EA-Code:

CartaniaChartesMaptown

14032

022100361

500 100

Approximate scale

200m

N

4 5

1

2

3

4 56

7

1 2 1 3

891 011

1 4

1 51 6

1 7

1 8

1 9

2 0

2 12 2

2 3

2 42 5 2 6

2 72 82 9

3 0

3 13 2

3 3

3 4

3 5 3 6

3 7

3 8

3 9

4 04 1

4 2

4 3

4 4

4 54 64 7

4 8 4 9 5 0 5 1 5 2

5 35 4

5 5

5 6

5 75 8

5 9

6 06 1

6 2

6 36 46 5

6 6

6 7

6 8

6 9

7 0

7 1

7 27 3

7 4 7 5

7 6

7 77 87 9

8 08 1 8 2

8 3

8 48 58 6

8 78 8

1 2 3 4

9 1 0

1 2

7

891 011

1 2

1 3

1 4

1 5

1 6

2 1

2 2

2 3

2 4

2 5 2 6 2 7

3 2

3 33 4

1 9

2 0

2 1

2 22 3

2 82 9

3 0

3 13 2

3 3

4 1

4 2

4 3

5 0

5 1

5 25 4

5 8

5 9

2 7

2 8

3 1

3 7

3 8

4 2

4 3

4 44 5

5 1

4 34 0

4 14 2

6 15 7

5 85 96 0

6 5 6 2

6 36 4

1 9

2 02 1

2 2 3 1

3 2

3 33 4

3 5

4 14 24 34 4

1

2

34

5

6

1 0

11

1 2 1 3

1 8

1 9 2 02 1

2 72 8

2 9

1 7

1

2

3

4 5

6

7

12 13

891011

14

1516

17

18

19

20

2122

23

2425

26

272829

30

3132

33

34

3536

37

38

39

4041

42

43

44

454647

4849

5051 52

5354

55

56

5758

59

6061

62

636465

66

67

68

69

70

71

7273

74 75

76

777879

80

81 82

83

848586

8788

1 2 3 4

9 10

1 2

7

89

1011

12

13

14

15

16

21

22

23

24

25 26 27

32

3334

19

20

21

22

23

28

2930

3132

33

41

42

43

50

51

5254

58

59

27

28

31

37

38

42

43

4445

51

43

40

4142

6157

585960

65 62

63

64

19

2021

22 31

32

3334

35

41424344

1

2

34

5

6

10

11

12 13

18

1920

21

2728

29

358

Enumeration Area Map Symbols

National Statistical Office -July 1998

Census2000

EA

Locality

District EA-Code

Hospital

Church

School

Buildingnumber

Province:District:Locality:EA-Code:

CartaniaChartesMaptown

14032

022100361

Approximate scale

N

45

17

Street Network Parcels

Parcel Boundary Annotation and symbols

Parcel numbers Neatlines and legend

361

378

374

349350

358

377

362

Actual Ground Survey ( DGPS+ETS)

More Accurate May be Acceptable to the ultimate

stakeholder “the Owner”

Ground Control Points

Primary, Secondary, Tertiary, Auxiliary Control points

Densification and observation time is different All the secondary and tertiary control points

should be connected to the primary control points of the SoI, to ensure connection to the National Framework

SOI May be asked to give the list of location of its GCPs to all states in advance, before starting re-surveys

Survey by ETS

Standardization of Codes Digital topographic database (DTDB) and

final plotting Preparation and distribution of draft land

parcel maps (LPMs) and linking attributes Recording objections

Recording objections A register shall be maintained to record and

track the objections raised by the owner(s)/enjoyer(s). The objections should also be flagged in the DTDB for better control and monitoring.

Objections redressal/adjudication Promulgation of survey

Validation of Land Parcel by the Stakeholder Acceptability Land sold in parts, mutation not reflected on

the ground, if re-demarcation also required under the project.

It will required mapping again. It is proposed to undertake bio-metric surveys

at the time of validation process.

Suggestions…..

Bio metric survey of not only the “owner” but also of the dependents at the time of validation.

This will help again in future …. In legal matters… in accordance with the curtain principles envisaged in conclusive titling.

It is suggested that along with the bio-metrics, the attributes may also be collected, this will substantially help in Unique Identification Number Project also.

It is better to prepare Land Information database of all the states in coherence with the UIN Project.

Thanks