编辑特征文件的工作原理
需具备 Spatial Analyst 许可方可使用。
编辑特征文件工具旨在修改现有的特征文件。 大多数情况下，此工具用于减少类的数量。 要确定应更改哪些类特征以生成更准确的分类，请使用树状图工具查看树状逻辑示意图。
示例
以下示例显示了如何将包含 14 个类的特征文件编辑为仅包含 7 个类。 这是通过删除不必要的类并合并同类类来完成的。 以下是将用于编辑特征文件的输入特征重映射文件。 它将 8 类和 21 类与 3 类合并、9 类与 1 类合并、14 类与 4 类合并、15 类与 7 类合并，以及 23 类与 6 类合并。 它还将删除 11 类。
8 : 3
9 : 1
11 : -9999
14 : 4
15 : 7
21 : 3
23 : 6
输出特征文件
以下列出了编辑特征文件生成的输出特征文件：
# Signatures Produced by ClassSig from Class-Grid zsamp12 and Stack redl123
# Number of selected grids
/* 3
# Layer-Number Grid-name
/* 1 redlands1
/* 2 redlands2
/* 3 redlands3
# Type Number of Classes Number of Layers Number of Parametric Layers
1 14 3 3
# ===============================================================
# Class ID Number of Cells Class Name
1 4493
# Layers 1 2 3
# Means
57.4801 55.1022 34.5615
# Covariance
1 755.8841 389.1188 165.2408
2 389.1188 451.9519 248.4967
3 165.2408 248.4967 163.7970
# -------------------------------------------------------
# Class ID Number of Cells Class Name
2 1464
# Layers 1 2 3
# Means
142.5451 48.3053 22.8818
# Covariance
1 301.2310 61.3188 -24.5077
2 61.3188 150.2574 102.7169
3 -24.5077 102.7169 103.9020
# ------------------------------------------------------
# Class ID Number of Cells Class Name
3 142
# Layers 1 2 3
# Means
226.2817 94.4225 25.4789
# Covariance
1 1250.7286 448.2489 -11.1146
2 448.2489 302.1464 75.3991
3 -11.1146 75.3991 67.7407
# ------------------------------------------------------
# Class ID Number of Cells Class Name
4 399
# Layers 1 2 3
# Means
161.6867 174.5113 177.4386
# Covariance
1 29.0699 23.6907 32.0523
2 23.6907 65.3359 38.7300
3 32.0523 38.7300 55.1061
# ------------------------------------------------------
# Class ID Number of Cells Class Name
5 1476
# Layers 1 2 3
# Means
0.0589 0.0976 1.2026
# Covariance
1 3.1321 2.4268 3.5081
2 2.4268 2.8922 3.9924
3 3.5081 3.9924 6.7094
# ------------------------------------------------------
# Class ID Number of Cells Class Name
6 225
# Layers 1 2 3
# Means
138.5378 140.1644 168.5600
# Covariance
1 151.4461 120.3978 142.3225
2 120.3978 142.5309 128.7914
3 142.3225 128.7914 149.9618
# ------------------------------------------------------
# Class ID Number of Cells Class Name
7 383
# Layers 1 2 3
# Means
129.2950 146.6136 97.0836
# Covariance
1 72.6745 21.6483 74.7947
2 21.6483 20.2377 38.7392
3 74.7947 38.7392 164.1239
# ------------------------------------------------------
# Class ID Number of Cells Class Name
8 948
# Layers 1 2 3
# Means
251.3091 76.7447 22.7795
# Covariance
1 49.3943 2.3736 -16.1440
2 2.3736 89.0773 13.2319
3 -16.1440 13.2319 12.8732
# -----------------------------------------------------
# Class ID Number of Cells Class Name
9 446
# Layers 1 2 3
# Means
100.0022 61.6861 39.1323
# Covariance
1 50.9685 3.0816 -2.7846
2 3.0816 81.6765 57.7427
3 -2.7846 57.7427 57.0229
# ------------------------------------------------------
# Class ID Number of Cells Class Name
11 244
# Layers 1 2 3
# Means
133.8402 85.3934 84.4672
# Covariance
1 78.2336 -1.2908 -20.0320
2 -1.2908 58.4454 29.1652
3 -20.0320 29.1652 77.5586
# -----------------------------------------------------
# Class ID Number of Cells Class Name
14 186
# Layers 1 2 3
# Means
159.5753 212.3172 163.9677
# Covariance
1 112.8186 197.4165 155.3484
2 197.4165 432.0772 319.2643
3 155.3484 319.2643 265.5773
# ------------------------------------------------------
# Class ID Number of Cells Class Name
15 149
# Layers 1 2 3
# Means
144.9262 154.2483 113.9262
# Covariance
1 191.0824 27.4239 137.5486
2 27.4239 81.4717 13.0252
3 137.5486 13.0252 114.0283
# -----------------------------------------------------
# Class ID Number of Cells Class Name
21 253
# Layers 1 2 3
# Means
235.0514 98.1107 32.6324
# Covariance
1 278.8188 81.3633 -12.5802
2 81.3633 132.3131 36.1639
3 -12.5802 36.1639 38.6699
# ----------------------------------------------------
# Class ID Number of Cells Class Name
23 121
# Layers 1 2 3
# Means
145.3223 143.9669 155.3058
# Covariance
1 21.4536 16.4524 24.5590
2 16.4524 43.2322 14.8685
3 24.5590 14.8685 79.9140