2.  Up to what level of classification can we perform on LISSIII/LISSIV data?  Is any advantage of high spectral resolution of LISSIII over LISSIV. If yes than how can we use it for classification ?  Would object based classification method work on LISS III/LISSIV. If yes than what would be the level of accuracy?  Would knowledge based classification give the appropriate result for low and medium resolution images?  Could we increase the accuracy of these classification methods? Objectives

3.  Maximum Likelihood (ML) (Parametric Classifier)  Object Based (OB) (Fuzzy classifier)  Knowledge Based (KB) (Non-parametric Classifier)

4. DATA AND STUDY AREA  Satellite images of the area IRS-P6 LISS IV IRS-P6 LISS III  Toposheet of the area (1:50,000)  Field data (training sites, test sites, GPS locations)

5. Sahaspur, Rampur and adjoining area (Dehradun dist.)

6. Images Preprocessing stages Training Sites Classification Methods Prepare land use /land cover map Accuracy Analysis Comparison Final results LISS IV LISS III Maximum Likelihood Knowledge Based Object Based Maximum Likelihood Knowledge Based Object Based Ground Truth Methodology Flowchart Separability analysis

7. No.First LevelSecond LevelThird Level 1.Built up landResidential Industrial 2.Agriculture landCropland Fallow land 3.ForestEvergreenDense/Open 4.Water bodiesRiverDry/Perennial Water NRSA LANDUSE/ LANDCOVER CLASSIFICATION SCHEME APPLIED ON STUDY AREA

8. LISS III LISS IV FEATURE SPACE FOR LISS III AND LISS IV (MLC)

9. SEPARABILITY ANALYSIS FOR LISS III AND LISS IV

10. CLASSIFIED IMAGE OF LISS III AND IV (MLC) LISS IV LISS III

11. SEGMENTATION PARAMETERS FOR OBJECT-ORIENTED METHOD LISS IV LISS III

12. CLASS DESCRIPTION (OBJECT BASED) Agriculture (LISSIII) Agriculture (LISSIV) Urban (LISSIII) Water (LISSIII) Urban (LISSIV) Water (LISSIV)

13. FEATURE SPACE FOR LISS III AND LISS IV (OBJECT-ORIENTED) LISS IV LISS III

14. Dry river/Industrial Urban/Agriculture FEATURE SPACE OF SPECTRALLY MIXED CLASSES (LISS III OBJECT BASED CLASSIFICATION)

15. Dry river/Industrial Residential/Dry river Industrial/Urban FEATURE SPACE OF SPECTRALLY MIXED CLASSES (LISS IV OBJECT BASED CLASSIFICATION)

16. LISS III, IV CLASSIFIED IMAGE (OBJECT BASED)

17. RULES FOR EXPERT CLASSIFIER

18. LISS IV CLASSIFIED IMAGE (EXPERT CLASSIFIER) After Rule base classification Before Rule base classification

19. Table 6: Overall accuracies (OA) & Kappa (K) achieved through various classification methods. Dataset Pixel based Classification approach(MLC) Object based Expert classifier Increase in accuracy from MLC to Object Based Increase in accuracy from MLC to Expert classifier LISS IV (OA)71.5989.2680.9417.679.35 LISS III (OA) 84.0089.15-5.15- LISS IV (K)62.5786.0474.8823.4712.31 LISS III (K)80.3386.66-6.33

20. CONCLUSION  On LISS III and LISS IV images up to second and third level of classification is possible but consideration of accuracy is needed.  High spectral resolution of LISS III can provide some good results to separate classes as compare to LISS IV.  Object based classification can also be applicable on LISS III and LISS IV images. But in LISS III it needs more parameters as compare to LISS IV.  By the help of expert classifier the accuracy of maximum likelihood results can be improved by the help of some additional layers.