Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image...

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Land Cover Classification System

Transcript of Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image...

Page 1: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

Land Cover Classification System

Page 2: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

PRESENTATION FLOWPRESENTATION 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

Page 3: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

INTRODUCTIONINTRODUCTION

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

Page 4: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

FINAL MOSAICS SCHEMA OF AOIFINAL MOSAICS SCHEMA OF AOI

Page 5: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.
Page 6: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

STEPS OF PRE-STEPS OF PRE-PROCESSINGPROCESSING

Page 7: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

KEY POINTSKEY 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

Page 8: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

KEY POINTSKEY POINTS

• Creation of Subsets within working areas

Segmentation created separately on each subset

Page 9: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

SEGMENTATIONSEGMENTATION• 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

Page 10: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

Land Cover Classification Map – Hyderabad & Surroundings

Hyderabad

Indus River

.

Sindh

Page 11: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

QUALITY ASSURANCE OF DATAQUALITY ASSURANCE OF DATA

• Quality Checking – Marking of Errors

• Error Removing

• Re – QC

Page 12: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

GENERAL ERROR MARKINGGENERAL ERROR MARKING

Page 13: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

ERRORERROR REMOVINGREMOVING

Page 14: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

EDGE MATCHINGEDGE MATCHING

Page 15: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

TOPOLOGY CHECKTOPOLOGY CHECK

• Removal of Gaps

• Removal of Overlaps

Page 16: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

TOPOLOGY CHECKTOPOLOGY CHECK

1. Data was first checked for gap errors

2. Correction of gap errors

3. Then, overlap topology was checked

4. 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

Page 17: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

REMOVAL OF GAPSREMOVAL OF GAPS

Page 18: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

REMOVAL OF OVERLAPING REMOVAL OF OVERLAPING ERRORSERRORS

Page 19: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

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.

Land Cover Mapping

Page 20: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

RESULTS VALIDATION THROUGH FIELD RESULTS VALIDATION THROUGH FIELD SURVEYSURVEY

ROUTE OF SURVEYROUTE OF SURVEY

SURVEY TEAMSURVEY TEAM

Page 21: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

RESULTS VALIDATION THROUGH FIELD RESULTS VALIDATION THROUGH FIELD SURVEYSURVEY

WLBA

TCIr

Page 22: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

RESULTS VALIDATION THROUGH FIELD RESULTS VALIDATION THROUGH FIELD SURVEYSURVEY

TCIr / SaD

SaD / WB

Page 23: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

RESULTS VALIDATION THROUGH FIELD RESULTS VALIDATION THROUGH FIELD SURVEYSURVEY

SCIr

WB

Page 24: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

RESULTS VALIDATION THROUGH FIELD RESULTS VALIDATION THROUGH FIELD SURVEYSURVEY

HCIrS

SaD

Page 25: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

SCIr – Shrubs Crop Irrigated TCIr – Trees Crop Irrigated

HCIr – Herbaceous Crop Irrigated HCRf - Herbaceous Crop Rainfed

Page 26: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

WLBA - Water Logged Bare Area WB – Water Bodies

SaFP – Desert Flat Plain BL – Barren Land

Page 27: Land Cover Classification System. P RESENTATION F LOW Introduction Steps of Pre-processing Image Classification in MadCat Quality Assurance of Data Edge.

Thank you