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Land Cover Classification System

Land Cover Classification System. Presentation Flow. Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge Matching Topology Check Final Quality Check Layout Development Results Validation through Field Survey. Introduction.

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Land Cover Classification System

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  1. Land Cover Classification System

  2. Presentation Flow • Introduction • Steps of Pre-processing • Image Classification in MadCat • Quality Assurance of Data • Edge Matching • Topology Check • Final Quality Check • Layout Development • Results Validation through Field Survey

  3. Introduction • Land Cover Mapping is an going project in collaboration with FAO UN using the technique of Land Cover Classification System (LCCS) – an important component of FAO / GLCN approach to create a harmonized and extensive representation of land cover features

  4. Final Mosaics schema of AoI

  5. Steps of Pre-processing

  6. Key points • DATA USED • SPOT 5 meter pan- sharpened data • 2.5meter rescaled at 5 meter • Development of Working areas • Working areas of whole province developed with minimum overlap

  7. Key points • Creation of Subsets within working areas Segmentation created separately on each subset

  8. Segmentation • Re-projected into world Mercator (WGS-1984) before segmentation • Segmentation scale used 50 (± 15 depending upon the features on image), shape = 0.1, compactness= 0.9) polygons from outside the boundary were deleted

  9. Land Cover Classification Map – Hyderabad & Surroundings Sindh Indus River Hyderabad

  10. Quality assurance of Data • Quality Checking – Marking of Errors • Error Removing • Re – QC

  11. General Error Marking

  12. ErrorRemoving

  13. Edge Matching

  14. Topology Check • Removal of Gaps • Removal of Overlaps

  15. Topology Check • Data was first checked for gap errors • Correction of gap errors • Then, overlap topology was checked • Overlap errors were corrected in MadCat • Gap corrected layer was imported in segment layer • Polygon containing errors were exported to training areas • Then again move back to segment layer by using Topology over

  16. Removal of Gaps

  17. Removal of Overlaping Errors

  18. Land Cover Mapping The possible areas of application would be Agriculture, Forestry, Environment, Irrigation, Disasters & Hazards Monitoring, Planning & Development, Oil & Gas Exploration, Mining, Wild Life and other emergent requirements.

  19. Results Validation through Field Survey Route of Survey Survey Team

  20. Results Validation through Field Survey WLBA TCIr

  21. Results Validation through Field Survey TCIr / SaD SaD / WB

  22. Results Validation through Field Survey SCIr WB

  23. Results Validation through Field Survey HCIrS SaD

  24. SCIr – Shrubs Crop Irrigated TCIr – Trees Crop Irrigated HCRf - Herbaceous Crop Rainfed HCIr – Herbaceous Crop Irrigated

  25. WLBA - Water Logged Bare Area WB – Water Bodies SaFP – Desert Flat Plain BL – Barren Land

  26. Thank you

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