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Object Based Supervised Classification
          Portland Metro                                                           ...
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Supervised Classifcation Portland Metro

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Supervised Classification Portland Metro

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Transcript of "Supervised Classifcation Portland Metro"

  1. 1. Object Based Supervised Classification Portland Metro First Classification Classes: Rule Applied Bands Parametric Expert Rule Standard nearest Green, Red, NIR, Bare Soil neighbor NDVI, DEM Mean 4-Band Image NDVI Image Grass Others to all classes PCA-1 Ratio DEM < 3Ft. Hi-Reflective Roof Paved Surfaces Residential Roof Tree DEM > 3Ft. Second Classification Classes: Rule Applied Bands Parametric Expert Rule Blue, Green, Red, NIR, Standard nearest NDV, PCA-2, PCA-3, Blue Buildings neighbor DEM Mean DEM > 7Ft. Pool to all classes PCA-1, PCA-3, NDVI Ratio Soil Other Paved Surfaces White & Gray Buildings DEM > 7Ft. Roads Expert Rules applied Blue, NDVI Mean Blue <= Upper Value NDVI < Upper Value PCA Image DEM Image PCA-3 Logical = 'AND' < Upper Value Logical = 'OR' Bands Spatial Date Pixel Depth Projection Source/Platform > Upper Value Resolution (bit) Classification Process Rule Set Classify Tree, Grass, Others Multiresolution Segmentation: 10 [shape:0.10 compct.:0.5] creating 'Level 1' Classification: at Level 1: Bare Soil, Grass, Hi-Reflective Roof, Others, Paved Surfaces, Residential Roof, Tree Assign Class: Unclassified at Level 1: Bare Soil, Hi-Reflective Roof, Others, Paved Surfaces, Residential Roof Classify Blue Bldgs, Soil, White&Gray Bldgs, Paved Surfaces, Pool, Other Land Cover Multiresolution Segmentation: Unclassified at Level 1: 25 [shape:0.1 compct.:0.5] Classification: Unclassified at Level 1: Blue Buildings, Others, Paved Surfaces, Pool, Soil, White & Gray Buildings Classify Roads Assign class: Unclassified at Level 1: Paved Surfaces Classification: Unclassified at Level 1: Roads Final Classification Classify Others Assign class: Unclassified at Level 1: Others Blue Buildings Roads Grass Soil Others Tree Pool White & Gray Buildings Accuracy of Training Samples First Classification Hi-Reflective Paved Residential User Class Sample Bare Soil Grass Roof Others Surfaces Roof Tree Sum Bare Soil 0 0 0 0 0 0 0 0 Grass 0 42 0 0 0 0 0 42 Random polygons were generated using a random number generated in ArcGIS Hi-Reflective Roof Others 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 and added as a field to the Final classification shapefile. The 50 polygons were selected Paved Surfaces 0 0 0 0 0 0 0 0 by the random number then saved as a separate shapefile and overlayed Residential Roof 0 0 0 0 0 2 0 2 Tree 0 0 0 0 0 0 58 58 onto the original image. The random "Reference" polygons classification was then assessed Sum 4 42 17 1 38 48 58 against the known classification class to come up with a total overall accuracy percent. Producer 0 1 0 0 0 0.041666667 1 User undefined 1 undefined undefined undefined 1 1 Rand_Num *Ref_Num Class_name Class_num Accuracy ClassNum Class KIA Per Class 0 1 0 0 0 0.03236246 1 Overall Accuracy 0.49038462 0.000000 4 Tree 4 0 1 Buildings KIA 0.42039958 0.000008 1 Roads 2 1 2 Other Impervious Accuracy of Training Samples Final Classification 0.000010 1 White & Gray Buildings 1 0 3 Unmanaged Soil Sum 0.000013 2 Roads 2 0 4 Trees and Shrubs Blue Buildings 80 0 0 0 0 0 0 0 80 0.000014 1 White & Gray Buildings 1 0 5 Grass Grass 0 42 0 0 0 0 0 0 42 Others 0 0 0 0 0 0 0 0 0 0.000015 2 Roads 2 0 6 Simmings Pool Pool 0 0 0 12 0 0 0 0 12 0.000017 2 Soil 3 1 7 Other Water Bodies Roads 0 0 1 0 0 0 0 0 1 0.000201 1 White & Gray Buildings 1 0 Soil 0 0 0 0 0 13 0 0 13 Tree 0 0 0 0 0 0 58 0 58 0.000201 4 Grass 5 1 *Ref_Num = observed White & Grey Blgs 0 0 0 0 0 0 0 92 92 0.000202 4 Tree 4 0 on original image file Sum 80 42 1 12 0 13 58 92 Total accuracy points 50 in ArcGIS Producer 1 1 0 1 undefined 1 1 1 Count if 0 37 Accuracy User 1 1 undefined 1 0 1 1 1 KIA Per Class 1 1 0 1 undefined 1 1 1 Count if 1 13 37/50 0=match Overall Accuracy 0.996644295 Overall Accuracy 74% 1=no match KIA 0.995649572
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