“编辑特征”的工作原理

需要 Spatial Analyst 许可。

编辑特征工具用于修改现有特征文件。该工具最常见的用途在于减少类的数量。要确定应对哪些类特征进行更改以生成一个更精确的分类,可使用树状图工具查看树示意图。

示例

以下示例显示了如何对包含 14 个类的特征文件进行编辑以使其仅包含 7 个类。这可通过删除不需要的类和合并相似类来实现。以下是将用于编辑特征文件的输入特征重映射文件。该文件分别将类 8、21 和 3、9 和 1、14 和 4、15 和 7、23 和 6 进行合并,同时删除类 11。

 8 : 3  9 : 1 11 : -9999 14 : 4 15 : 7 21 : 3 23 : 6

输出特征文件

编辑特征工具生成的输出特征文件如下所示:

 # 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 

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