LCMS employs a number of cross-walking methods to combine classes in different ways to meet the need for varying levels of thematic detail. In general, products with higher numbers of classes exhibit lower levels of accuracy. Users should use the level that best matches their error tolerance and need for thematic detail.
This document will provide guidance for crosswalking the delivered LCMS products to these standard Levels. Each level will also have a respective accuracy report provided.
Below are tables illustrating the relationship between the levels and how they are binned
| Level 1 | Level 2 | Level 3 | |
|---|---|---|---|
| 1 | Disturbance | Wind | Wind |
| 2 | Disturbance | Wind | Hurricane |
| 3 | Disturbance | Other Loss | Snow or Ice Transition |
| 4 | Disturbance | Desiccation | Desiccation |
| 5 | Disturbance | Inundation | Inundation |
| 6 | Disturbance | Fire | Prescribed Fire |
| 7 | Disturbance | Fire | Wildfire |
| 8 | Disturbance | Mechanical Land Transformation | Mechanical Land Transformation |
| 9 | Disturbance | Tree Removal | Tree Removal |
| 10 | Disturbance | Insect, Disease, or Drought Stress | Defoliation |
| 11 | Disturbance | Insect, Disease, or Drought Stress | Southern Pine Beetle |
| 12 | Disturbance | Insect, Disease, or Drought Stress | Insect, Disease, or Drought Stress |
| 13 | Disturbance | Other Loss | Other Loss |
| 14 | Vegetation Successional Growth | Vegetation Successional Growth | Vegetation Successional Growth |
| 15 | Stable | Stable | Stable |
| 16 | Non-Processing Area Mask | Non-Processing Area Mask | Non-Processing Area Mask |
| Level 1 | Level 2 | Level 3 | Level 4 | |
|---|---|---|---|---|
| 1 | Vegetated | Tree Vegetated | Tree | Tree |
| 2 | Vegetated | Tree Vegetated | Tree | Tall Shrub & Tree Mix (AK Only) |
| 3 | Vegetated | Tree Vegetated | Tree | Shrub & Tree Mix |
| 4 | Vegetated | Tree Vegetated | Tree | Grass/Forb/Herb & Tree Mix |
| 5 | Vegetated | Tree Vegetated | Tree | Barren & Tree Mix |
| 6 | Vegetated | Non-Tree Vegetated | Shrub | Tall Shrub (AK Only) |
| 7 | Vegetated | Non-Tree Vegetated | Shrub | Shrub |
| 8 | Vegetated | Non-Tree Vegetated | Shrub | Grass/Forb/Herb & Shrub Mix |
| 9 | Vegetated | Non-Tree Vegetated | Shrub | Barren & Shrub Mix |
| 10 | Vegetated | Non-Tree Vegetated | Grass/Forb/Herb | Grass/Forb/Herb |
| 11 | Vegetated | Non-Tree Vegetated | Grass/Forb/Herb | Barren & Grass/Forb/Herb Mix |
| 12 | Non-Vegetated | Non-Vegetated | Barren or Impervious | Barren or Impervious |
| 13 | Non-Vegetated | Non-Vegetated | Snow or Ice | Snow or Ice |
| 14 | Non-Vegetated | Non-Vegetated | Water | Water |
| 15 | Non-Processing Area Mask | Non-Processing Area Mask | Non-Processing Area Mask | Non-Processing Area Mask |
| Level 1 | Level 2 | |
|---|---|---|
| 1 | Anthropogenic | Agriculture |
| 2 | Anthropogenic | Developed |
| 3 | Non-Anthropogenic | Forest |
| 4 | Non-Anthropogenic | Other |
| 5 | Non-Anthropogenic | Rangeland or Pasture |
| 6 | Non-Processing Area Mask | Non-Processing Area Mask |
For the best results, we recommend using the following crosswalks when converting between different levels.
Remap From: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
Remap To: [1, 1, 8, 2, 3, 4, 4, 5, 6, 7, 7, 7, 8, 9, 10, 11]
Visualization JSON:
{'Change_class_names': ['Wind', 'Desiccation', 'Inundation', 'Fire', 'Mechanical Land Transformation', 'Tree Removal', 'Insect, Disease, or Drought Stress', 'Other Loss', 'Vegetation Successional Growth', 'Stable', 'Non-Processing Area Mask'], 'Change_class_palette': ['FF09F3', 'CC982E', '0ADAFF', 'D54309', 'FAFA4B', 'AFDE1C', 'F39268', 'C291D5', '00A398', '3D4551', '1B1716'], 'Change_class_values': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]}
Remap From: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
Remap To: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4]
Visualization JSON:
{'Change_class_names': ['Disturbance', 'Vegetation Successional Growth', 'Stable', 'Non-Processing Area Mask'], 'Change_class_palette': ['D54309', '00A398', '3D4551', '1B1716'], 'Change_class_values': [1, 2, 3, 4]}
Level 3 Visualization JSON:
{'Change_class_names': ['Wind', 'Hurricane', 'Snow or Ice Transition', 'Desiccation', 'Inundation', 'Prescribed Fire', 'Wildfire', 'Mechanical Land Transformation', 'Tree Removal', 'Defoliation', 'Southern Pine Beetle', 'Insect, Disease, or Drought Stress', 'Other Loss', 'Vegetation Successional Growth', 'Stable', 'Non-Processing Area Mask'], 'Change_class_palette': ['FF09F3', '541AFF', 'E4F5FD', 'CC982E', '0ADAFF', 'A10018', 'D54309', 'FAFA4B', 'AFDE1C', 'FFC80D', 'A64C28', 'F39268', 'C291D5', '00A398', '3D4551', '1B1716'], 'Change_class_values': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 13, 14, 15, 16]}
Remap From: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
Remap To: [1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 4, 5, 6, 7]
Visualization JSON:
{'Land_Cover_class_names': ['Tree', 'Shrub', 'Grass/Forb/Herb', 'Barren or Impervious', 'Snow or Ice', 'Water', 'Non-Processing Area Mask'], 'Land_Cover_class_palette': ['004E2B', 'F89A1C', 'E5E98A', '893F54', 'E4F5FD', '00B6F0', '1B1716'], 'Land_Cover_class_values': [1, 2, 3, 4, 5, 6, 7]}
Remap From: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
Remap To: [1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 4]
Visualization JSON:
{'Land_Cover_class_names': ['Tree Vegetated', 'Non-Tree Vegetated', 'Non-Vegetated', 'Non-Processing Area Mask'], 'Land_Cover_class_palette': ['004E2B', '8DA463', '893F54', '1B1716'], 'Land_Cover_class_values': [1, 2, 3, 4]}
Remap From: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
Remap To: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 3]
Visualization JSON:
{'Land_Cover_class_names': ['Vegetated', 'Non-Vegetated', 'Non-Processing Area Mask'], 'Land_Cover_class_palette': ['61BB46', '58646E', '1B1716'], 'Land_Cover_class_values': [1, 2, 3]}
Level 4 Visualization JSON:
{'Land_Cover_class_names': ['Tree', 'Tall Shrub & Tree Mix (AK Only)', 'Shrub & Tree Mix', 'Grass/Forb/Herb & Tree Mix', 'Barren & Tree Mix', 'Tall Shrub (AK Only)', 'Shrub', 'Grass/Forb/Herb & Shrub Mix', 'Barren & Shrub Mix', 'Grass/Forb/Herb', 'Barren & Grass/Forb/Herb Mix', 'Barren or Impervious', 'Snow or Ice', 'Water', 'Non-Processing Area Mask'], 'Land_Cover_class_palette': ['004E2B', '009344', '61BB46', 'ACBB67', '8B8560', 'CAFD4B', 'F89A1C', '8FA55F', 'BEBB8E', 'E5E98A', 'DDB925', '893F54', 'E4F5FD', '00B6F0', '1B1716'], 'Land_Cover_class_values': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]}
Remap From: [1, 2, 3, 4, 5, 6]
Remap To: [1, 1, 2, 2, 2, 3]
Visualization JSON:
{'Land_Use_class_names': ['Anthropogenic', 'Non-Anthropogenic', 'Non-Processing Area Mask'], 'Land_Use_class_palette': ['FF9EAB', '004E2B', '1B1716'], 'Land_Use_class_values': [1, 2, 3]}
Level 2 Visualization JSON:
{'Land_Use_class_names': ['Agriculture', 'Developed', 'Forest', 'Other', 'Rangeland or Pasture', 'Non-Processing Area Mask'], 'Land_Use_class_palette': ['FBFF97', 'E6558B', '004E2B', '9DBAC5', 'A6976A', '1B1716'], 'Land_Use_class_values': [1, 2, 3, 4, 5, 6]}
Overall Accuracy: 97.45 +/- 0.07
Balanced Accuracy: 55.44 +/- 1.29
Kappa: 0.45
Users Accuracy (100%-Commission Error):
Stable: 98.40
Disturbance: 53.58
Vegetation Successional Growth: 52.62
Users Error:
Stable: 0.05
Disturbance: 4.30
Vegetation Successional Growth: 1.53
Producers Accuracy (100%-Omission Error):
Stable: 99.01
Disturbance: 15.04
Vegetation Successional Growth: 52.26
Producers Error:
Stable: 0.04
Disturbance: 1.63
Vegetation Successional Growth: 1.53
Number of Samples in each class:
Stable: 55984
Disturbance: 551
Vegetation Successional Growth: 1478
| Observed | ||||||||
|---|---|---|---|---|---|---|---|---|
| Stable | Disturbance | Vegetation Successional Growth | Users Acc | Users SE | ||||
| Predicted | Stable | 55929.39 | 400.52 | 510.55 | 98.4 | 0.05 | ||
| Disturbance | 60.97 | 72.10 | 1.48 | 53.58 | 4.3 | |||
| Vegetation Successional Growth | 498.15 | 6.62 | 560.53 | 52.62 | 1.53 | |||
| Producers Acc | 99.01 | 15.04 | 52.26 | |||||
| Producers SE | 0.04 | 1.63 | 1.53 |
Overall Accuracy: 93.24 +/- 0.04
Balanced Accuracy: 56.60 +/- 0.45
Kappa: 0.41
Users Accuracy (100%-Commission Error):
Stable: 95.69
Disturbance: 45.62
Vegetation Successional Growth: 50.57
Users Error:
Stable: 0.03
Disturbance: 0.89
Vegetation Successional Growth: 0.39
Producers Accuracy (100%-Omission Error):
Stable: 97.21
Disturbance: 32.06
Vegetation Successional Growth: 40.53
Producers Error:
Stable: 0.03
Disturbance: 0.70
Vegetation Successional Growth: 0.35
Number of Samples in each class:
Stable: 313362
Disturbance: 8172
Vegetation Successional Growth: 32059
| Observed | ||||||||
|---|---|---|---|---|---|---|---|---|
| Stable | Disturbance | Vegetation Successional Growth | Users Acc | Users SE | ||||
| Predicted | Stable | 325476.79 | 2830.49 | 11817.92 | 95.69 | 0.03 | ||
| Disturbance | 1579.79 | 1431.28 | 126.65 | 45.62 | 0.89 | |||
| Vegetation Successional Growth | 7751.86 | 203.19 | 8139.79 | 50.57 | 0.39 | |||
| Producers Acc | 97.21 | 32.06 | 40.53 | |||||
| Producers SE | 0.03 | 0.70 | 0.35 |
Overall Accuracy: 97.44 +/- 0.07
Balanced Accuracy: 22.12 +/- 7.65
Kappa: 0.45
Users Accuracy (100%-Commission Error):
Desiccation: Too few samples to assess accuracy
Fire: 85.69
Veg-Growth: 55.99
Harvest: 0.00
Insect-Disease-Drought: 4.23
Inundation: Too few samples to assess accuracy
Mechanical: Too few samples to assess accuracy
Other: 3.26
Stable: 98.39
Wind: Too few samples to assess accuracy
Users Error:
Desiccation: Too few samples to assess accuracy
Fire: 4.44
Veg-Growth: 1.58
Harvest: 0.00
Insect-Disease-Drought: 3.68
Inundation: Too few samples to assess accuracy
Mechanical: Too few samples to assess accuracy
Other: 3.57
Stable: 0.05
Wind: Too few samples to assess accuracy
Producers Accuracy (100%-Omission Error):
Desiccation: Too few samples to assess accuracy
Fire: 46.83
Veg-Growth: 51.63
Harvest: 0.00
Insect-Disease-Drought: 4.05
Inundation: Too few samples to assess accuracy
Mechanical: Too few samples to assess accuracy
Other: 0.28
Stable: 99.04
Wind: Too few samples to assess accuracy
Producers Error:
Desiccation: Too few samples to assess accuracy
Fire: 4.68
Veg-Growth: 1.53
Harvest: 0.00
Insect-Disease-Drought: 3.52
Inundation: Too few samples to assess accuracy
Mechanical: Too few samples to assess accuracy
Other: 0.31
Stable: 0.04
Wind: Too few samples to assess accuracy
Number of Samples in each class:
Desiccation: 2 (Too few samples to assess accuracy)
Fire: 147
Veg-Growth: 1477
Harvest: 101
Insect-Disease-Drought: 85
Inundation: 9 (Too few samples to assess accuracy)
Mechanical: 23 (Too few samples to assess accuracy)
Other: 185
Stable: 55984
Wind: 0
| Observed | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Desiccation | Fire | Veg-Growth | Harvest | Insect-Disease-Drought | Inundation | Mechanical | Other | Stable | Wind | Users Acc | Users SE | ||
| Predicted | Desiccation | 0.0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 1.10 | 35.69 | 0.0 | 0.0 | 0.0 |
| Fire | 0.0 | 53.29 | 1.48 | 0.15 | 0.00 | 0.00 | 0.00 | 0.00 | 7.27 | 0.0 | 85.69 | 4.44 | |
| Veg-Growth | 0.0 | 2.49 | 553.19 | 4.70 | 2.44 | 0.00 | 0.00 | 0.00 | 425.14 | 0.0 | 55.99 | 1.58 | |
| Harvest | 0.0 | 1.48 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.0 | 0.0 | 0.0 | |
| Insect-Disease-Drought | 0.0 | 0.00 | 0.00 | 1.58 | 1.27 | 3.09 | 0.00 | 0.07 | 24.00 | 0.0 | 4.23 | 3.68 | |
| Inundation | 0.0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 34.36 | 0.0 | 0.0 | 0.0 | |
| Mechanical | 0.0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.55 | 0.00 | 0.03 | 0.0 | 94.44 | 29.99 | |
| Other | 0.0 | 1.48 | 0.00 | 5.56 | 0.15 | 0.00 | 0.13 | 0.81 | 16.63 | 0.0 | 3.26 | 3.57 | |
| Stable | 2.2 | 55.04 | 516.79 | 25.31 | 27.53 | 1.94 | 2.17 | 285.73 | 55945.40 | 0.0 | 98.39 | 0.05 | |
| Wind | 0.0 | 0.00 | 0.00 | 0.07 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.0 | 0.0 | 0.0 | |
| Producers Acc | 0.0 | 46.83 | 51.63 | 0.00 | 4.05 | 0.00 | 19.35 | 0.28 | 99.04 | 0.0 | |||
| Producers SE | 0.0 | 4.68 | 1.53 | 0.00 | 3.52 | 0.00 | 23.42 | 0.31 | 0.04 | 0.0 |
Overall Accuracy: 92.97 +/- 0.04
Balanced Accuracy: 30.10 +/- 2.21
Kappa: 0.40
Users Accuracy (100%-Commission Error):
Desiccation: 28.14
Fire: 84.29
Veg-Growth: 51.04
Harvest: 88.51
Insect-Disease-Drought: 17.38
Inundation: 38.38
Mechanical: 43.59
Other: 0.24
Stable: 95.67
Wind: 7.82
Users Error:
Desiccation: 2.52
Fire: 3.66
Veg-Growth: 0.40
Harvest: 1.81
Insect-Disease-Drought: 1.06
Inundation: 2.81
Mechanical: 5.31
Other: 0.15
Stable: 0.04
Wind: 3.58
Producers Accuracy (100%-Omission Error):
Desiccation: 50.25
Fire: 29.60
Veg-Growth: 40.62
Harvest: 17.10
Insect-Disease-Drought: 17.71
Inundation: 30.74
Mechanical: 7.11
Other: 1.43
Stable: 97.13
Wind: 9.26
Producers Error:
Desiccation: 3.74
Fire: 2.72
Veg-Growth: 0.35
Harvest: 0.94
Insect-Disease-Drought: 1.08
Inundation: 2.38
Mechanical: 1.11
Other: 0.90
Stable: 0.03
Wind: 4.20
Number of Samples in each class:
Desiccation: 154
Fire: 399
Veg-Growth: 31503
Harvest: 3374
Insect-Disease-Drought: 2653
Inundation: 313
Mechanical: 794
Other: 304
Stable: 304586
Wind: 79
| Observed | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Desiccation | Fire | Veg-Growth | Harvest | Insect-Disease-Drought | Inundation | Mechanical | Other | Stable | Wind | Users Acc | Users SE | ||
| Predicted | Desiccation | 89.67 | 0.00 | 9.74 | 0.00 | 0.72 | 10.62 | 0.61 | 0.58 | 206.75 | 0.00 | 28.14 | 2.52 |
| Fire | 0.00 | 83.20 | 9.17 | 1.99 | 0.88 | 0.57 | 0.14 | 0.02 | 2.73 | 0.00 | 84.29 | 3.66 | |
| Veg-Growth | 0.27 | 6.91 | 7964.43 | 110.78 | 19.99 | 37.59 | 22.90 | 3.04 | 7432.31 | 6.21 | 51.04 | 0.4 | |
| Harvest | 0.00 | 5.67 | 5.95 | 274.83 | 0.59 | 4.49 | 3.34 | 0.43 | 14.52 | 0.71 | 88.51 | 1.81 | |
| Insect-Disease-Drought | 0.00 | 9.18 | 86.09 | 17.36 | 220.24 | 0.00 | 0.08 | 2.25 | 930.84 | 1.20 | 17.38 | 1.06 | |
| Inundation | 0.00 | 0.00 | 5.23 | 0.00 | 0.00 | 115.10 | 0.88 | 0.31 | 178.36 | 0.00 | 38.38 | 2.81 | |
| Mechanical | 0.00 | 0.00 | 1.65 | 7.48 | 0.00 | 0.00 | 38.01 | 0.00 | 40.06 | 0.00 | 43.59 | 5.31 | |
| Other | 1.76 | 8.41 | 21.61 | 417.14 | 20.69 | 6.78 | 26.57 | 2.48 | 513.09 | 5.24 | 0.24 | 0.15 | |
| Stable | 86.75 | 167.41 | 11502.21 | 759.51 | 979.00 | 198.63 | 437.55 | 164.49 | 316418.45 | 29.85 | 95.67 | 0.04 | |
| Wind | 0.00 | 0.31 | 0.57 | 17.77 | 1.47 | 0.61 | 4.42 | 0.00 | 26.81 | 4.41 | 7.82 | 3.58 | |
| Producers Acc | 50.25 | 29.60 | 40.62 | 17.10 | 17.71 | 30.74 | 7.11 | 1.43 | 97.13 | 9.26 | |||
| Producers SE | 3.74 | 2.72 | 0.35 | 0.94 | 1.08 | 2.38 | 1.11 | 0.90 | 0.03 | 4.20 |
Overall Accuracy: 95.37 +/- 0.09
Balanced Accuracy: 95.13 +/- 0.15
Kappa: 0.88
Users Accuracy (100%-Commission Error):
VEG: 98.18
NON-VEG: 87.68
Users Error:
VEG: 0.06
NON-VEG: 0.26
Producers Accuracy (100%-Omission Error):
VEG: 95.60
NON-VEG: 94.65
Producers Error:
VEG: 0.10
NON-VEG: 0.19
Number of Samples in each class:
VEG: 48503
NON-VEG: 9510
| Observed | |||||
|---|---|---|---|---|---|
| VEG | NON-VEG | Users Acc | Users SE | ||
| Predicted | VEG | 41697.53 | 771.60 | 98.18 | 0.06 |
| NON-VEG | 1917.78 | 13653.41 | 87.68 | 0.26 | |
| Producers Acc | 95.60 | 94.65 | |||
| Producers SE | 0.10 | 0.19 |
Overall Accuracy: 95.29 +/- 0.04
Balanced Accuracy: 80.95 +/- 0.23
Kappa: 0.59
Users Accuracy (100%-Commission Error):
VEG: 97.79
NON-VEG: 58.91
Users Error:
VEG: 0.03
NON-VEG: 0.32
Producers Accuracy (100%-Omission Error):
VEG: 97.19
NON-VEG: 64.72
Producers Error:
VEG: 0.03
NON-VEG: 0.33
Number of Samples in each class:
VEG: 320406
NON-VEG: 33187
| Observed | |||||
|---|---|---|---|---|---|
| VEG | NON-VEG | Users Acc | Users SE | ||
| Predicted | VEG | 328828.31 | 7421.66 | 97.79 | 0.03 |
| NON-VEG | 9495.61 | 13612.19 | 58.91 | 0.32 | |
| Producers Acc | 97.19 | 64.72 | |||
| Producers SE | 0.03 | 0.33 |
Overall Accuracy: 83.95 +/- 0.15
Balanced Accuracy: 85.55 +/- 0.24
Kappa: 0.76
Users Accuracy (100%-Commission Error):
TREE_VEG: 79.39
NON-TREE_VEG: 85.90
NON-VEG: 87.68
Users Error:
TREE_VEG: 0.27
NON-TREE_VEG: 0.24
NON-VEG: 0.26
Producers Accuracy (100%-Omission Error):
TREE_VEG: 87.21
NON-TREE_VEG: 74.80
NON-VEG: 94.65
Producers Error:
TREE_VEG: 0.24
NON-TREE_VEG: 0.28
NON-VEG: 0.19
Number of Samples in each class:
TREE_VEG: 25183
NON-TREE_VEG: 23320
NON-VEG: 9510
| Observed | ||||||
|---|---|---|---|---|---|---|
| TREE VEG | NON-TREE VEG | NON-VEG | Users Acc | Users SE | ||
| Predicted | TREE VEG | 17195.03 | 4245.79 | 217.40 | 79.39 | 0.27 |
| NON-TREE VEG | 2380.32 | 17876.40 | 554.20 | 85.9 | 0.24 | |
| NON-VEG | 141.23 | 1776.55 | 13653.41 | 87.68 | 0.26 | |
| Producers Acc | 87.21 | 74.80 | 94.65 | |||
| Producers SE | 0.24 | 0.28 | 0.19 |
Overall Accuracy: 86.71 +/- 0.06
Balanced Accuracy: 79.92 +/- 0.20
Kappa: 0.75
Users Accuracy (100%-Commission Error):
TREE_VEG: 90.33
NON-TREE_VEG: 87.56
NON-VEG: 58.91
Users Error:
TREE_VEG: 0.08
NON-TREE_VEG: 0.07
NON-VEG: 0.32
Producers Accuracy (100%-Omission Error):
TREE_VEG: 84.57
NON-TREE_VEG: 90.47
NON-VEG: 64.72
Producers Error:
TREE_VEG: 0.10
NON-TREE_VEG: 0.07
NON-VEG: 0.33
Number of Samples in each class:
TREE_VEG: 204320
NON-TREE_VEG: 116086
NON-VEG: 33187
| Observed | ||||||
|---|---|---|---|---|---|---|
| TREE VEG | NON-TREE VEG | NON-VEG | Users Acc | Users SE | ||
| Predicted | TREE VEG | 116082.93 | 10913.86 | 1515.68 | 90.33 | 0.08 |
| NON-TREE VEG | 19937.65 | 181893.87 | 5905.98 | 87.56 | 0.07 | |
| NON-VEG | 1248.40 | 8247.21 | 13612.19 | 58.91 | 0.32 | |
| Producers Acc | 84.57 | 90.47 | 64.72 | |||
| Producers SE | 0.10 | 0.07 | 0.33 |
Overall Accuracy: 72.41 +/- 0.19
Balanced Accuracy: 76.77 +/- 0.43
Kappa: 0.65
Users Accuracy (100%-Commission Error):
TREES: 79.39
SHRUBS: 73.12
GRASS: 43.86
BARREN: 67.90
SNOW: 91.92
WATER: 95.99
Users Error:
TREES: 0.27
SHRUBS: 0.47
GRASS: 0.46
BARREN: 0.61
SNOW: 0.34
WATER: 0.34
Producers Accuracy (100%-Omission Error):
TREES: 87.21
SHRUBS: 42.99
GRASS: 60.64
BARREN: 82.98
SNOW: 96.34
WATER: 90.47
Producers Error:
TREES: 0.24
SHRUBS: 0.40
GRASS: 0.53
BARREN: 0.55
SNOW: 0.24
WATER: 0.50
Number of Samples in each class:
TREES: 25183
SHRUBS: 14860
GRASS: 8460
BARREN: 4587
SNOW: 2828
WATER: 2095
| Observed | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| TREES | SHRUBS | GRASS | BARREN | SNOW | WATER | Users Acc | Users SE | ||
| Predicted | TREES | 17195.03 | 3146.10 | 1099.69 | 156.07 | 0.00 | 61.33 | 79.39 | 0.27 |
| SHRUBS | 1232.24 | 6615.81 | 1149.73 | 50.39 | 0.00 | 0.00 | 73.12 | 0.47 | |
| GRASS | 1148.08 | 4952.04 | 5158.82 | 280.47 | 0.00 | 223.34 | 43.86 | 0.46 | |
| BARREN | 141.23 | 674.95 | 778.51 | 3927.49 | 212.63 | 49.30 | 67.9 | 0.61 | |
| SNOW | 0.00 | 1.91 | 249.25 | 271.59 | 5953.62 | 0.78 | 91.92 | 0.34 | |
| WATER | 0.00 | 0.00 | 71.93 | 47.17 | 13.70 | 3177.14 | 95.99 | 0.34 | |
| Producers Acc | 87.21 | 42.99 | 60.64 | 82.98 | 96.34 | 90.47 | |||
| Producers SE | 0.24 | 0.40 | 0.53 | 0.55 | 0.24 | 0.50 |
Overall Accuracy: 78.40 +/- 0.07
Balanced Accuracy: 69.16 +/- 2.63
Kappa: 0.69
Users Accuracy (100%-Commission Error):
TREES: 90.33
SHRUBS: 74.31
GRASS: 72.88
BARREN: 41.93
SNOW: 67.66
WATER: 92.31
Users Error:
TREES: 0.08
SHRUBS: 0.17
GRASS: 0.12
BARREN: 0.39
SNOW: 6.75
WATER: 0.31
Producers Accuracy (100%-Omission Error):
TREES: 84.57
SHRUBS: 58.92
GRASS: 87.22
BARREN: 54.31
SNOW: 53.79
WATER: 76.13
Producers Error:
TREES: 0.10
SHRUBS: 0.17
GRASS: 0.10
BARREN: 0.45
SNOW: 6.42
WATER: 0.46
Number of Samples in each class:
TREES: 204320
SHRUBS: 36175
GRASS: 79911
BARREN: 21697
SNOW: 1004
WATER: 10486
| Observed | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| TREES | SHRUBS | GRASS | BARREN | SNOW | WATER | Users Acc | Users SE | ||
| Predicted | TREES | 116082.93 | 5931.78 | 4982.08 | 861.14 | 0.00 | 654.54 | 90.33 | 0.08 |
| SHRUBS | 6466.48 | 47981.18 | 8135.46 | 1987.35 | 0.00 | 0.00 | 74.31 | 0.17 | |
| GRASS | 13471.17 | 21439.98 | 104337.26 | 2650.43 | 0.00 | 1268.21 | 72.88 | 0.12 | |
| BARREN | 1115.31 | 6062.77 | 1846.96 | 6653.04 | 27.90 | 159.87 | 41.93 | 0.39 | |
| SNOW | 0.00 | 0.00 | 1.30 | 14.22 | 32.48 | 0.00 | 67.66 | 6.75 | |
| WATER | 133.09 | 14.45 | 321.73 | 83.94 | 0.00 | 6640.73 | 92.31 | 0.31 | |
| Producers Acc | 84.57 | 58.92 | 87.22 | 54.31 | 53.79 | 76.13 | |||
| Producers SE | 0.10 | 0.17 | 0.10 | 0.45 | 6.42 | 0.46 |
Overall Accuracy: 64.97 +/- 0.20
Balanced Accuracy: 36.15 +/- 0.35
Kappa: 0.58
Users Accuracy (100%-Commission Error):
TREES: 71.90
TS-TREES: nan
SHRUBS-TRE: 2.55
GRASS-TREE: 0.60
BARREN-TRE: nan
TS: 60.36
SHRUBS: 28.21
GRASS-SHRU: nan
BARREN-SHR: nan
GRASS: 42.79
BARREN-GRA: 5.56
BARREN-IMP: 67.90
SNOW: 91.92
WATER: 95.99
Users Error:
TREES: 0.31
TS-TREES: nan
SHRUBS-TRE: 2.22
GRASS-TREE: 0.36
BARREN-TRE: nan
TS: 0.64
SHRUBS: 0.80
GRASS-SHRU: nan
BARREN-SHR: nan
GRASS: 0.46
BARREN-GRA: 2.57
BARREN-IMP: 0.61
SNOW: 0.34
WATER: 0.34
Producers Accuracy (100%-Omission Error):
TREES: 92.26
TS-TREES: 0.00
SHRUBS-TRE: 0.08
GRASS-TREE: 0.29
BARREN-TRE: 0.00
TS: 64.99
SHRUBS: 14.96
GRASS-SHRU: 0.00
BARREN-SHR: 0.00
GRASS: 62.94
BARREN-GRA: 0.78
BARREN-IMP: 82.98
SNOW: 96.34
WATER: 90.47
Producers Error:
TREES: 0.21
TS-TREES: 0.00
SHRUBS-TRE: 0.07
GRASS-TREE: 0.17
BARREN-TRE: 0.00
TS: 0.64
SHRUBS: 0.46
GRASS-SHRU: 0.00
BARREN-SHR: 0.00
GRASS: 0.54
BARREN-GRA: 0.37
BARREN-IMP: 0.55
SNOW: 0.24
WATER: 0.50
Number of Samples in each class:
TREES: 21599
TS-TREES: 472
SHRUBS-TRE: 1787
GRASS-TREE: 1121
BARREN-TRE: 204
TS: 5407
SHRUBS: 5641
GRASS-SHRU: 3541
BARREN-SHR: 271
GRASS: 7843
BARREN-GRA: 617
BARREN-IMP: 4587
SNOW: 2828
WATER: 2095
| Observed | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TREES | TS-TREES | SHRUBS-TRE | GRASS-TREE | BARREN-TRE | TS | SHRUBS | GRASS-SHRU | BARREN-SHR | GRASS | BARREN-GRA | BARREN-IMP | SNOW | WATER | Users Acc | Users SE | ||
| Predicted | TREES | 15195.19 | 272.77 | 1093.85 | 553.71 | 57.98 | 1224.39 | 1267.96 | 309.62 | 47.37 | 904.30 | 0.78 | 145.41 | 0.00 | 61.33 | 71.9 | 0.31 |
| TS-TREES | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | NaN | NaN | |
| SHRUBS-TRE | 9.89 | 0.00 | 1.28 | 2.99 | 0.00 | 1.51 | 34.65 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 2.55 | 2.22 | |
| GRASS-TREE | 0.00 | 4.52 | 0.00 | 2.84 | 0.00 | 2.47 | 123.61 | 102.37 | 32.15 | 193.51 | 1.10 | 10.66 | 0.00 | 0.00 | 0.6 | 0.36 | |
| BARREN-TRE | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | NaN | NaN | |
| TS | 332.58 | 139.06 | 200.18 | 66.71 | 28.44 | 3557.09 | 1138.64 | 92.39 | 12.88 | 323.22 | 0.00 | 1.98 | 0.00 | 0.00 | 60.36 | 0.64 | |
| SHRUBS | 185.24 | 70.23 | 149.40 | 60.40 | 0.00 | 429.08 | 890.00 | 430.19 | 65.53 | 823.50 | 3.01 | 48.40 | 0.00 | 0.00 | 28.21 | 0.8 | |
| GRASS-SHRU | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | NaN | NaN | |
| BARREN-SHR | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | NaN | NaN | |
| GRASS | 628.44 | 26.11 | 187.25 | 299.72 | 6.54 | 252.78 | 2251.83 | 2355.93 | 40.82 | 4999.24 | 155.18 | 256.24 | 0.00 | 223.34 | 42.79 | 0.46 | |
| BARREN-GRA | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 50.67 | 0.00 | 0.00 | 4.41 | 24.24 | 0.00 | 0.00 | 5.56 | 2.57 | |
| BARREN-IMP | 119.39 | 0.00 | 7.75 | 9.71 | 4.38 | 5.96 | 242.36 | 341.77 | 84.86 | 392.73 | 385.78 | 3927.49 | 212.63 | 49.30 | 67.9 | 0.61 | |
| SNOW | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 1.91 | 234.74 | 14.51 | 271.59 | 5953.62 | 0.78 | 91.92 | 0.34 | |
| WATER | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 71.93 | 0.00 | 47.17 | 13.70 | 3177.14 | 95.99 | 0.34 | |
| Producers Acc | 92.26 | 0.00 | 0.08 | 0.29 | 0.00 | 64.99 | 14.96 | 0.00 | 0.00 | 62.94 | 0.78 | 82.98 | 96.34 | 90.47 | |||
| Producers SE | 0.21 | 0.00 | 0.07 | 0.17 | 0.00 | 0.64 | 0.46 | 0.00 | 0.00 | 0.54 | 0.37 | 0.55 | 0.24 | 0.50 |
Overall Accuracy: 66.74 +/- 0.08
Balanced Accuracy: 38.47 +/- 1.87
Kappa: 0.56
Users Accuracy (100%-Commission Error):
TREES: 81.69
TS-TREES: Not Modeled
SHRUBS-TRE: 14.92
GRASS-TREE: 35.60
BARREN-TRE: 6.74
TS: Not Modeled
SHRUBS: 42.58
GRASS-SHRU: 37.44
BARREN-SHR: 27.25
GRASS: 72.40
BARREN-GRA: 1.20
BARREN-IMP: 41.93
SNOW: 67.66
WATER: 92.31
Users Error:
TREES: 0.11
TS-TREES: Not Modeled
SHRUBS-TRE: 1.21
GRASS-TREE: 0.44
BARREN-TRE: 2.20
TS: Not Modeled
SHRUBS: 0.42
GRASS-SHRU: 0.23
BARREN-SHR: 0.49
GRASS: 0.12
BARREN-GRA: 1.16
BARREN-IMP: 0.39
SNOW: 6.75
WATER: 0.31
Producers Accuracy (100%-Omission Error):
TREES: 93.68
TS-TREES: Not Modeled
SHRUBS-TRE: 1.99
GRASS-TREE: 15.23
BARREN-TRE: 0.37
TS: Not Modeled
SHRUBS: 21.10
GRASS-SHRU: 39.77
BARREN-SHR: 16.46
GRASS: 88.77
BARREN-GRA: 0.04
BARREN-IMP: 54.31
SNOW: 53.79
WATER: 76.13
Producers Error:
TREES: 0.08
TS-TREES: Not Modeled
SHRUBS-TRE: 0.17
GRASS-TREE: 0.22
BARREN-TRE: 0.13
TS: Not Modeled
SHRUBS: 0.24
GRASS-SHRU: 0.24
BARREN-SHR: 0.32
GRASS: 0.09
BARREN-GRA: 0.04
BARREN-IMP: 0.45
SNOW: 6.42
WATER: 0.46
Number of Samples in each class:
TREES: 164664
TS-TREES: Not Modeled
SHRUBS-TRE: 10962
GRASS-TREE: 26573
BARREN-TRE: 2121
TS: Not Modeled
SHRUBS: 13165
GRASS-SHRU: 15860
BARREN-SHR: 7150
GRASS: 76631
BARREN-GRA: 3280
BARREN-IMP: 21697
SNOW: 1004
WATER: 10486
| Observed | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TREES | SHRUBS-TRE | GRASS-TREE | BARREN-TRE | SHRUBS | GRASS-SHRU | BARREN-SHR | GRASS | BARREN-GRA | BARREN-IMP | SNOW | WATER | Users Acc | Users SE | ||
| Predicted | TREES | 94549.13 | 3380.73 | 9667.57 | 524.50 | 1700.99 | 1327.21 | 21.86 | 3093.52 | 80.68 | 765.03 | 0.00 | 632.14 | 81.69 | 0.11 |
| SHRUBS-TRE | 238.16 | 128.97 | 182.65 | 0.04 | 193.15 | 11.75 | 64.80 | 44.18 | 0.00 | 0.53 | 0.00 | 0.00 | 14.92 | 1.21 | |
| GRASS-TREE | 2007.32 | 719.98 | 4191.68 | 385.79 | 1021.21 | 1081.86 | 487.26 | 1721.20 | 42.51 | 93.17 | 0.00 | 22.40 | 35.6 | 0.44 | |
| BARREN-TRE | 0.00 | 0.00 | 97.61 | 8.80 | 0.27 | 8.72 | 12.71 | 0.00 | 0.00 | 2.40 | 0.00 | 0.00 | 6.74 | 2.2 | |
| SHRUBS | 179.34 | 566.97 | 854.76 | 188.03 | 5860.58 | 3387.43 | 1046.30 | 1266.04 | 188.51 | 226.08 | 0.00 | 0.00 | 42.58 | 0.42 | |
| GRASS-SHRU | 222.63 | 645.76 | 2673.30 | 340.37 | 10380.32 | 15965.32 | 5546.63 | 5159.41 | 824.09 | 888.92 | 0.00 | 0.00 | 37.44 | 0.23 | |
| BARREN-SHR | 17.43 | 130.75 | 365.53 | 281.61 | 926.95 | 2644.07 | 2223.57 | 441.16 | 256.25 | 872.35 | 0.00 | 0.00 | 27.25 | 0.49 | |
| GRASS | 3231.74 | 869.63 | 9222.00 | 147.80 | 6605.15 | 13670.10 | 1081.95 | 103584.15 | 752.05 | 2645.64 | 0.00 | 1268.21 | 72.4 | 0.12 | |
| BARREN-GRA | 0.00 | 0.00 | 0.00 | 0.00 | 56.29 | 17.43 | 9.05 | 0.00 | 1.06 | 4.79 | 0.00 | 0.00 | 1.2 | 1.16 | |
| BARREN-IMP | 372.88 | 11.92 | 266.75 | 463.77 | 1031.79 | 2021.89 | 3009.08 | 1056.95 | 790.01 | 6653.04 | 27.90 | 159.87 | 41.93 | 0.39 | |
| SNOW | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.10 | 1.20 | 14.22 | 32.48 | 0.00 | 67.66 | 6.75 | |
| WATER | 106.94 | 16.78 | 3.90 | 5.46 | 4.60 | 8.14 | 1.71 | 319.56 | 2.17 | 83.94 | 0.00 | 6640.73 | 92.31 | 0.31 | |
| Producers Acc | 93.68 | 1.99 | 15.23 | 0.37 | 21.10 | 39.77 | 16.46 | 88.77 | 0.04 | 54.31 | 53.79 | 76.13 | |||
| Producers SE | 0.08 | 0.17 | 0.22 | 0.13 | 0.24 | 0.24 | 0.32 | 0.09 | 0.04 | 0.45 | 6.42 | 0.46 |
Overall Accuracy: 99.83 +/- 0.02
Balanced Accuracy: 71.37 +/- 2.77
Kappa: 0.58
Users Accuracy (100%-Commission Error):
Anthro: 92.38
Non-Anthro: 99.84
Users Error:
Anthro: 3.09
Non-Anthro: 0.02
Producers Accuracy (100%-Omission Error):
Anthro: 42.74
Non-Anthro: 99.99
Producers Error:
Anthro: 3.92
Non-Anthro: 0.00
Number of Samples in each class:
Anthro: 2226
Non-Anthro: 55787
| Observed | |||||
|---|---|---|---|---|---|
| Anthro | Non-Anthro | Users Acc | Users SE | ||
| Predicted | Anthro | 68.23 | 5.62 | 92.38 | 3.09 |
| Non-Anthro | 91.40 | 57875.08 | 99.84 | 0.02 | |
| Producers Acc | 42.74 | 99.99 | |||
| Producers SE | 3.92 | 0.00 |
Overall Accuracy: 91.17 +/- 0.05
Balanced Accuracy: 89.62 +/- 0.09
Kappa: 0.78
Users Accuracy (100%-Commission Error):
Anthro: 81.18
Non-Anthro: 95.04
Users Error:
Anthro: 0.12
Non-Anthro: 0.04
Producers Accuracy (100%-Omission Error):
Anthro: 86.35
Non-Anthro: 92.89
Producers Error:
Anthro: 0.11
Non-Anthro: 0.05
Number of Samples in each class:
Anthro: 74865
Non-Anthro: 278728
| Observed | |||||
|---|---|---|---|---|---|
| Anthro | Non-Anthro | Users Acc | Users SE | ||
| Predicted | Anthro | 81320.12 | 18858.40 | 81.18 | 0.12 |
| Non-Anthro | 12856.97 | 246322.28 | 95.04 | 0.04 | |
| Producers Acc | 86.35 | 92.89 | |||
| Producers SE | 0.11 | 0.05 |
Overall Accuracy: 84.88 +/- 0.15
Balanced Accuracy: 73.49 +/- 3.70
Kappa: 0.77
Users Accuracy (100%-Commission Error):
Agriculture: 90.85
Developed: 92.57
Forest: 83.31
Other: 91.69
Rangeland: 82.02
Users Error:
Agriculture: 5.21
Developed: 3.84
Forest: 0.27
Other: 0.23
Rangeland: 0.25
Producers Accuracy (100%-Omission Error):
Agriculture: 76.00
Developed: 35.15
Forest: 85.04
Other: 88.49
Rangeland: 82.75
Producers Error:
Agriculture: 7.05
Developed: 4.31
Forest: 0.26
Other: 0.26
Rangeland: 0.24
Number of Samples in each class:
Agriculture: 1076
Developed: 1150
Forest: 24106
Other: 9535
Rangeland: 22146
| Observed | ||||||||
|---|---|---|---|---|---|---|---|---|
| Agriculture | Developed | Forest | Other | Rangeland | Users Acc | Users SE | ||
| Predicted | Agriculture | 27.85 | 0.00 | 0.00 | 0.00 | 2.80 | 90.85 | 5.21 |
| Developed | 0.00 | 43.22 | 3.08 | 0.26 | 0.13 | 92.57 | 3.84 | |
| Forest | 1.09 | 33.74 | 16117.94 | 180.52 | 3013.37 | 83.31 | 0.27 | |
| Other | 0.00 | 3.67 | 91.31 | 13281.90 | 1108.48 | 91.69 | 0.23 | |
| Rangeland | 7.70 | 42.33 | 2742.14 | 1546.34 | 19792.43 | 82.02 | 0.25 | |
| Producers Acc | 76.00 | 35.15 | 85.04 | 88.49 | 82.75 | |||
| Producers SE | 7.05 | 4.31 | 0.26 | 0.26 | 0.24 |
Overall Accuracy: 83.77 +/- 0.06
Balanced Accuracy: 75.77 +/- 0.26
Kappa: 0.77
Users Accuracy (100%-Commission Error):
Agriculture: 76.91
Developed: 82.61
Forest: 89.25
Other: 81.13
Rangeland: 83.68
Users Error:
Agriculture: 0.14
Developed: 0.35
Forest: 0.09
Other: 0.37
Rangeland: 0.10
Producers Accuracy (100%-Omission Error):
Agriculture: 88.82
Developed: 55.34
Forest: 90.19
Other: 63.50
Rangeland: 81.02
Producers Error:
Agriculture: 0.11
Developed: 0.37
Forest: 0.09
Other: 0.40
Rangeland: 0.11
Number of Samples in each class:
Agriculture: 48716
Developed: 26149
Forest: 189082
Other: 23652
Rangeland: 65994
| Observed | ||||||||
|---|---|---|---|---|---|---|---|---|
| Agriculture | Developed | Forest | Other | Rangeland | Users Acc | Users SE | ||
| Predicted | Agriculture | 67955.48 | 2852.46 | 1922.19 | 836.30 | 14786.82 | 76.91 | 0.14 |
| Developed | 739.53 | 9776.93 | 684.30 | 38.23 | 595.35 | 82.61 | 0.35 | |
| Forest | 1294.89 | 2475.85 | 107691.93 | 1237.03 | 7968.07 | 89.25 | 0.09 | |
| Other | 44.39 | 112.00 | 323.48 | 9026.73 | 1619.71 | 81.13 | 0.37 | |
| Rangeland | 6476.29 | 2449.28 | 8780.10 | 3078.07 | 106592.36 | 83.68 | 0.1 | |
| Producers Acc | 88.82 | 55.34 | 90.19 | 63.50 | 81.02 | |||
| Producers SE | 0.11 | 0.37 | 0.09 | 0.40 | 0.11 |