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National Land Record Modernization Program

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

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National Land Record Modernization Program

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  1. National Land Record Modernization Program Presented by : N K Buildcon Pvt Limited, Jaipur

  2. Presentation Layout • NKBPL • Scanning and Digitization • Resurveys

  3. 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

  4. 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

  5. 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.

  6. General Methodology : Land Record Modernization Village (Cadastral) Map Availability Yes No Vectorisation of (Cadastral) Map Survey Fused product f High resolution Satellite Image (Cartosat) Overlap of Cadastral Maps on High resolution Satellite Image Analyse changes in parcel (Size, Shape) & identity areas for Fewer Changes Large Changes Re-Survey Updation Aerial Image, ETS, GPS High resolution Satellite Image, ETS, GPS High resolution Satellite Image, ETS, GPS Digital Cadastral Geospatial Database

  7. 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.

  8. 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 Maps • Sheet 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 data • Attribute data attachment • Output Layout s for printing and hard copy evaluation

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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)

  14. Grid correction of the scanned (raster map) 800 m 700 m 100 m GCP 100 m 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

  15. 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

  16. Digitization errors

  17. Digitization errors

  18. Creation of spatial data 1/9th part Digitized map 1/18th part 1/36th Part

  19. Digitization & Feature extraction • Sample village map (Cadastral) digitized.

  20. 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

  21. Spatial data creation using satellite image Settlements Administrative Boundaries 1/36th part Cartosat

  22. Methodologies for Re-Surveys • Actual Ground Survey-DGPS+ETS • GCP+ Satellite Images • Hybrid Survey Methodology using Aerial Photography and Ground Truthing using DGPS/TS

  23. Decision for Technology • Vegetative cover (dense, sparse) • Built-up areas • Size of survey area • Accuracy • Timeliness • Cost

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

  25. 1999 1995/1997 INDIAN IMAGING SYSTEMS 2001 RESOURCESAT-1 LISS3 - 23 M; 4 XS LISS4 - 5.8 M; 3-XS AWIFS - 70 M; 4-XS IRS-1C/1D LISS-3 (23/70M, STEERABLE PAN (5.8 M); WiFS (188M) INSAT-2E CCD (1KM RESOLUTION; EVERY 30 MNUTESS) 1996 2002 1994 IRS-P3 (1996)WiFS MOS X-Ray, CARTOSAT - 1 PAN - 2.5M, 30 KM, F/A 1999 IRS-P2 LISS-2 IRS-P4 OCEANSAT OCM, MSMR 2003 1988/91 CARTOSAT-2 PAN - 1M IRS-1A & 1B LISS-1&2 (72/36M, 4 BANDS; VIS & NIR) 1982 2005 • IMAGING IMPROVEMENTS • 1KM TO 5.8 M RESOLUTION GLOBAL COVERAGE APPLICATION-SPECIFIC RS-D1 MEGHA-TROPIQUES SAPHIR SCARAB & MADRAS 1979 BHASKARA

  26. 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 Spatial Resolution of various Satellites 1KM 360m 188m

  27. 23m 5.8m …TOWARDS 1m • 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 INDIAN IMAGING CAPABILITY

  28. IRS ID WiFS Spatial Resolution: 188 m

  29. IRS P6 AWiFS Spatial Resolution: 56 m

  30. IRS IC LISS III MSS Image Spatial Resolution: 23.5 m

  31. IRS IC LISS III PAN Image Spatial Resolution: 5.8 m

  32. IRS IC LISS III PAN + LISS –III Merged Image Spatial Resolution: 5.8 m

  33. Quickbird (PAN sharpened Image) Spatial Resolution: 61 cms

  34. Methodology of Land Record Modernization using High Resolution Satellite Data Vectorised Cadastral Maps High Resolution Satellite Image GCP Data DGPS Survey GCP Collection Mathematical Transformation Model Validation of Model (RMS and Residual Error) Geo-referencing of Village Cadastral 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

  35. 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

  36. 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.

  37. Procedure of Geometric Correction • Locate (register) GCPs • Resampling

  38. Locate GCPs on Satellite Image

  39. Collection of Ground Control Points

  40. 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. • Nearest neighbor • Bilinear • Cubic

  41. Land Record updation on satellite image

  42. Sample Parcel Map

  43. Attribute data attachment 3 A-4 22061 1 (Universe polygon) Spatial data 2 3 3 (ARC functions) 4 5 COV# ZONE ZIP 1 0 2 C-19 22060 Attribute data 3 A-4 22061 4 C-22 22060 (INFO or TABLES functions) 5 A-5 22057

  44. Output Layout Parcels Street Network Parcel Boundary Annotation and symbols 350 349 358 362 361 374 378 377 Parcel numbers Neatlines and legend 35 31 61 27 22 57 45 65 62 19 41 40 42 43 32 44 43 20 63 33 21 34 64 58 60 28 41 59 42 6 61 1 60 55 6 4 5 7 1 62 11 5 2 66 56 31 59 10 9 8 11 10 63 64 65 3 4 58 57 37 19 12 13 12 67 13 42 74 75 18 73 2 72 14 38 20 23 68 71 18 69 43 21 3 15 17 22 70 51 16 21 44 20 45 19 82 81 76 80 29 35 36 21 24 26 19 25 79 77 78 20 28 27 22 23 37 27 43 28 30 29 1 29 2 38 88 83 28 31 87 42 32 33 32 39 14 31 33 84 85 86 41 30 41 13 40 7 34 12 24 15 42 52 10 51 11 23 50 43 49 9 48 8 44 53 54 46 47 45 59 50 27 26 25 58 22 51 16 4 3 2 1 32 52 34 33 54 9 10 21 Enumeration Area Map Symbols Province: Cartania 14 358 District: Chartes 032 District EA-Code Locality: Maptown 0221 Locality EA-Code: 00361 Hospital EA N Church Building 17 number School Approximate scale Census National Statistical Office - July 1998 2000

  45. Actual Ground Survey ( DGPS+ETS) • More Accurate • May be Acceptable to the ultimate stakeholder “the Owner”

  46. 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

  47. 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

  48. 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

  49. 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.

  50. 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.

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