Metric  Definitions (from McGarigal and Marks, 1994 and McGarigal and Marks, 1995)

Class  Area (CA)

Sum  of areas of all patches belonging to a given class.

Example:  Conifer Class Area (CA) = 359047.844+......+65819.984

CA  = 69.6626 hectares

If  the map units are not specified (i.e., Data Frame properties; see Set map  units) and "State areas in Hectares" has not been selected in the  "Advanced Options" of the "Spatial Statistics" dialog  box, then the resulting statistics will be reported in native map units  (vector layers (themes) only).

In  the example; CA = 696626.012 (map units). This is the case for most  statistics.

Landscape  Area (TLA)

Sum  of areas of all patches in the landscape.

Example:  Landscape Area (TLA) = 46872.719 + 359047.844 +... + 62423.574

TLA  = 184.11 hectares

Percentage  of Landscape (ZLAND)

When  analyzing by class, ZLAND is the percentage of the total landscape made up of  the corresponding class (patch type).

Number  of Patches (NumP)

Total  number of patches in the landscape if "Analyze by Landscape" is  selected, or Number of Patches for each individual class, if "Analyze by  Class" is selected.

Example:  Class Level: Number of Patches (NumP)

Mixedwood  = 5, Conifer = 4, Deciduous = 5

Landscape  Level: Number of Patches (NumP) = 14

Patch  Richness (PR)

PR  is the number of different patch types within the landcape's boundary.

Patch  Richness Density (PRD)

PRD  is equal to PR divided by the total area of the landscape (metres squared)  multiplied by 10,000 and then 100 (to convert to hundreds of hectares).

Largest  Patch Index (LPI)

The  LPI is equal to the percent of the total landscape that is made up by the  largest patch.

When  the entire landscape is made up of a single patch, the LPI will equal 100. As  the size of the largest patch decreases, the LPI approaches 0.

Mean  Patch Size (MPS)

Average  patch size.

Example:  Mean Patch Size of Conifer Patches (Class Level)

MPS  = (359047.844 + 139531.484 ...+ 65819.984)/4

MPS  = 17.42 hectares

Example:  Mean Patch Size of Patches (Landscape Level)

MPS  = (46872.719 + 359047.844 + ... + 62432.574)/14

MPS  = 13.15 hectares

Median  Patch Size (MedPS)

The  middle patch size, or 50th percentile.

Example:  Median Patch size of Conifer Patches (Class Level)

MedPS  = 13.22 hectares

Example:  Median Patch size of all patches (Landscape Level)

MedPS  = 7.59 hectares

Patch  Size Standard Deviation (PSSD)

Standard  Deviation of patch areas.

Example:  Patch Size Standard Deviation of Conifer Patches (Class Level)

PSSD  = 11.05 hectares

Example:  Patch Size Standard Deviation of all patches (Landscape Level)

PSSD  = 9.51 hectares

Patch  Size Coefficient of Variance (PSCoV)

Coefficient  of variation of patches.

Example:  Coefficient of Variation of Conifer patches (Class Level)

PSCoV  = PSSD/MPS = (11.05 hectares / 17.42 hectares) *100 = 63

Example:  Coefficient of Variation of all patches (Landscape Level)

PSCoV  = (9.51 hectares / 13.15 hectares)*100 =72

Total  Edge (TE)

Perimeter  of patches.

Example:  Total Edge Conifer (Class Level)

TE  = Sum of perimeter of all conifer patches.

TE  = 10858.88 metres

Units  are expressed in native maps units.

Example:  Total Edge all patches (Landscape Level)

TE  = Sum of perimeter of all patches

TE  = 28607.27 metres

Important

In  the case of vector layers (themes), edge calculations include all the edge on  the landscape including boundary edge. The contrasted weighted edge feature  allows edge weight at the boundaries to be set to zero. In the case of raster  (grid) layers (themes), edge calculations do not include the edges that  surround the landscape boundary edge or any interior edges that include  pixels classified as No Data.

Edge  Density (ED)

Amount  of edge relative to the landscape area.

Example:  Edge Density Conifer (Class Level)

ED  = TE / TLA

ED  = 10858.88 metres/184.11 hectares = 58.98 metres/hectare

Example:  Edge Density of all Patches (Landscape Level)

ED  = 28607.27 metres/184.11 hectares = 155.38 metres/hectare

Mean  Patch Edge (MPE)

Average  amount of edge per patch.

Example:  Mean Patch Edge Conifer (Class Level)

MPE  = TE / NumP

MPE  = 10858.88 metres/4 patches = 2714.72 metres/patch

Example:  Mean Patch Edge all Patches (Landscape Level)

MPE  = TE / NumP

MPE  = 28607.27 metres/14 patches = 2043.38 metres/patch

Contrasted  Weighted Edge Density (CWED)

CWED  is a measure of density of edge in a landscape (metres per hectare) with a  user-specified contrast weight.

CWED  is equal to 0 when there is no edge in the landscape, in other words the  whole landscape and it's border are made up of a single patch. It's value  increases as the amount of edge in the landscape increases and/or as the user  increases the contrast weight.

Landscape  Shape Index (LSI)

LSI  is the total landscape boundary and all edge within the boundary divided by  the square root of the total landscape area (square metres) and adjusted by a  constant (circular standard for vector layers, square standard for rasters).  The LSI will increase with increasing landscape shape irregularity or  increasing amounts of edge within the landscape.

Double  Log Fractal Dimension (DLFD)

DLFD  is a measure of patch perimeter complexity. It nears 1 when patch shapes are  'simple', such as circles or squares and it approaches 2 as patch shape  perimeter complexity increases.

Mean  Perimeter-Area Ratio (MPAR)

Shape  Complexity.

Example:  Mean perimeter-area ratio Conifer (Class Level)

MPAR  = Sum of each patches perimeter/area ratio divided by number of patches.

MPAR  = (132 m/ha + 112 m/ha + 201 m/ha + 84 m/ha)/4 patches

MPAR  = 182 metres/hectare

Example:  Mean perimeter-area ratio all patches (Landscape Level)

MPAR  = (200 m/ha + 132 m/ha + ... + 175 m/ha)/14 patches

MPAR  = 185 metres/hectare

Mean  Shape Index (MSI)

Shape  Complexity.

MSI  is equal to 1 when all patches are circular (for polygons) or square (for  rasters (grids)) and it increases with increasing patch shape irregularity.

MSI  = sum of each patch's perimeter divided by the square root of patch area (in  hectares) for each class (when analyzing by class) or all patches (when  analyzing by landscape), and adjusted for circular standard ( for polygons),  or square standard (for rasters (grids)), divided by the number of patches.

Area  Weighted Mean Shape Index (AWMSI)

AWMSI  is equal to 1 when all patches are circular (for polygons) or square (for  rasters (grids)) and it increases with increasing patch shape irregularity.

AWMSI  equals the sum of each patch's perimeter, divided by the square root of patch  area (in hectares) for each class (when analyzing by class) or for all  patches (when analyzing by landscape), and adjusted for circular standard (  for polygons), or square standard (for rasters (grids)), divided by the  number of patches. It differs from the MSI in that it's weighted by patch  area so larger patches will weigh more than smaller ones.

Mean  Patch Fractal Dimension (MPFD)

Shape  Complexity.

Mean  patch fractal dimension (MPFD) is another measure of shape complexity. Mean  fractal dimension approaches one for shapes with simple perimeters and  approaches two when shapes are more complex.

Area  Weighted Mean Patch Fractal Dimension (AWMPFD)

Shape  Complexity adjusted for shape size.

Area  weighted mean patch fractal dimension is the same as mean patch fractal  dimension with the addition of individual patch area weighting applied to  each patch. Because larger patches tend to be more complex than smaller  patches, this has the effect of determining patch complexity independent of  its size. The unit of measure is the same as mean patch fractal dimension.

Mean  Nearest Neighbor (MNN)

Measure  of patch isolation.

The  nearest neighbor distance of an individual patch is the shortest distance to  a similar patch (edge to edge). The mean nearest neighbor distance is the  average of these distances (metres) for individual classes at the class level  and the mean of the class nearest neighbor distances at the landscape level.

Interspersion  Juxtaposition Index (IJI)

Measure  of patch adacency.

Approaches  zero when the distribution of unique patch adjacencies becomes uneven and 100  when all patch types are equally adjacent.

Interspersion  requires that the landscape be made up of a minimum of three classes. At the  class level interspersion is a measure of relative interspersion of each  class. At the landscape level it is a measure of the interspersion of the  each patch in the landscape.

Mean  Proximity Index (MPI)

Measure  of the degree of isolation and fragmentation.

Mean  proximity index is a measure of the degree of isolation and fragmentation of  a patch. MPI uses the nearest neighbor statistic. The distance threshold  default is 1,000,000. If MPI is required at specific distances, select Set  MPI Threshold from the main Patch pull-down menu and enter a threshold  distance.

Both  MNN and MPI use the nearest neighbor statistic of similar polygons in their  algorithm. Occasionally a blank or zero will be reported in MNN and MPI  fields. This happens when one polygon vertex touches another polygons border  but the two similar polygons do not share a common border. When this happens  a manual edit (move) of the touching vertex will correct the problem in the  layer (theme). This problem will not happen when analyzing raster (grid)  layers (themes).

Shannon's  Diversity Index (SDI)

Measure  of relative patch diversity.

Shannon's  diversity index is only available at the landscape level and is a relative  measure of patch diversity. The index will equal zero when there is only one  patch in the landscape and increases as the number of patch types or  proportional distribution of patch types increases.

Simpson's  Diversity Index (SIDI)

Measure  of relative patch diversity.

Simpson's  diversity index is only available at the landscape level and is a relative  measure of patch diversity. The index will equal zero when there is only one  patch in the landscape and increases as the number of patch types or  proportional distribution of patch types increases.

Shannon's  Evenness Index (SEI)

Measure  of patch distribution and abundance.

Shannon's  evenness index is equal to zero when the observed patch distribution is low  and approaches one when the distribution of patch types becomes more even.  Shannon's evenness index is only available at the landscape level.

Simpson's  Evenness Index (SIEI)

SIEI  is a measure of the distribution of area among patch types. It equals 1 when  the distribution of area among patches is exactly even. SIEI approaches 0 as  the distribution of area among the patches become more and more dominated by  one patch type.

Modified  Simpson's Diversity Index (MSIDI)

MSIDI  is a measure of patch diversity. It equals zero when there is only one patch  in the landscape and increases as the number of different patch types (PR)  increases and the area among patch types becomes more equal.

Modified  Simpson's Evenness Index (MSIEI)

MSIEI  is a measure of the distribution of area among patch types. It equals 1 when  the distribution of area among patches is exactly even. SIEI approaches 0 as  the distribution of area among the patches become more and more dominated by  one patch type. It differs from SIEI in that it is derived from the Modified  Simpson's Diversity Index (MSIDI) rather than the Simpson's Diversity Index  (SIDI).

Important

Direct  analyses of Core Area through the spatial statistics dialogue are only  available for raster (grid) layers (themes). If core area statistics are  required for vector layers (themes), first Create Core Areas (create a new  core area theme) from the Patch pull-down menu and then calculate statistics  for the new layer (theme) as you would for a normal vector layer (theme). The  results will be core area statistics.

Total  Core Area (CA)

The  total size of disjunct core patches.

The  total size of disjunct core area patches (hectares).

Mean  Core Area (MCA)

The  average size of disjunct core patches.

The  mean size of disjunct core area patches (hectares).

Number  of Core Areas (NCA)

The  total number of disjunct core areas within each patch of a corresponding  patch type (or class).

Mean  Core Area Index (MCAI)

MCAI  is the average percentage of a landscape patch that is core area. It will be  equal to 0 when there is no core area present in any patch in the landscape  and it increases (towards 100%) when patches contain mostly core area.

Core  Area Standard Deviation (CASD)

Measure  of variability in core area size.

The  standard deviation of disjunct core areas (hectares).

Core  Area Density (CAD)

The  relative number of disjunct core patches relative to the landscape area.

The  total number of all disjunct patches divided by the landscape area (number of  disjunct core patches/hectare).

Total  Core Area Index (TCAI)

Measure  of amount of core area in the landscape.

Total  core area index is a measure of the amount of core area in the landscape.  Total core area index is a proportion of core area in the entire landscape  and is equal to zero when no patches in the landscape contain core and  approaches one as the relative proportion of core area in the landscape  increases.

Core  Area Percentage of Land (C_LAND)

C_LAND  is the percentage of the total landscape which is made up of core area.

Mean  Core Area per Patch (MCA1)

MCA1  is the average core area per patch (as opposed to all distunct core areas).

It  equals the sum of the core areas of each patch or corresponding patch type,  divided by the number of total patches of the same type, divided by 10, 000  (to convert to hectares).

Core  Area Coefficient of Variance (CACOV)

CACOV  represents the variability in size of disjunct core areas in relation to the  mean core area.

Patch  Core Area Standard Deviation (CASD1)

Measure  of variability in patch core area size.

The  standard deviation of patch core areas (hectares).

Patch  Core Area Coefficient of Variation (CACV1)

The  standard deviation in core areas (CASD) divided by the mean core area per  patch (MCA) and multplied by 100 (%).

The  variablility in core area among patches relative to the mean core area.

度量定义（从McGarigal和标志，1995年，1994年和McGarigal和标记）

类区（CA）

属于一个给定的类的所有斑块的区域总和。

例如：针叶类区（CA）= 359047.844 + ......  65819.984

 CA =69.6626公顷的

如果不指定地图单位（即数据帧的属性，请参阅设置地图单位）和“国家公顷”没有被选中的“空间统计”对话框中的“高级选项”，然后将统计结果将报告在本机地图单位（矢量图层（主题））。

在本例中，CA = 696626.012（图）。这是对于大多数统计数据的情况下。



风景名胜区（TLA）

领域的所有斑块的景观总和。

例：风景名胜区（TLA）= 46872.719 359047.844  + ... + 62423.574

 TLA =184.11公顷的



百分比景观（ZLAND）

按类别分析时，ZLAND是由对应的类（贴片式）的总景观的百分比。

斑块（NUMP）

斑块总数的景观分析，如果“景观”，或为每个类的斑块数，如果选择“分析类”。

例：级别：号码修补程序（NUMP的）

 Mixedwood = 5，康= 4，落叶= 5

风景等级：斑块（NUMP）= 14



景观丰富度（PR）

公关是不同的斑块类型内的landcape的边界。



景观丰富度密度（PRD）

珠三角是等于PR除以景观总面积（米）的平方乘以10,000和100（转换为数百公顷）。



最大斑块指数（LPI）

 LPI是等于％]是由最大的斑块的总景观。

当整个景观是由一个单一的斑块，LPI等于100。的LPI作为最大斑块的大小减小，接近0。

平均斑块面积（MPS）

平均斑块大小。

例如：平均斑块面积针叶修补程序（级别）

 MPS =（359047.844  139531.484 ... 65819.984 +）/ 4

 MPS =17.42公顷的

例：斑块（景观的平均斑块面积）

（46872.719 + MPS =  359047.844 + ... + 62432.574）/ 14

 MPS =13.15公顷的



中位数斑块大小（MedPS）

中间的斑块大小，或第50百分位。

例如：平均斑块大小的康修补程序（级别）

 MedPS = 13.22公顷

例：中位数的所有斑块（斑块大小景观的）

 MedPS = 7.59公顷



斑块面积标准差（PSSD）

斑块面积的标准偏差。

例：斑块面积标准差针叶修补程序（级别）

 PSSD = 11.05公顷

例如：修补尺寸标准偏差的所有斑块（山水水平）

 PSSD = 9.51公顷



斑块大小变异系数（PSCoV）

变异系数的斑块。

例：康斑块的变异系数（职业等级）

 PSCoV = PSSD / MPS =（11.05公顷/17.42公顷的）* 100 = 63

例：变异系数的所有斑块（景观水平）

 PSCoV =（9.51公顷/13.15公顷的）* 100 = 72



总边缘（TE）

周边的斑块。

例：总边缘针叶树（级别）

 TE =总和，外围所有针叶树斑块的。

 TE =10858.88米的

单位表示在本机地图单位。

例：总边缘的修补程序（景观水平）

 TE =周长总和的所有斑块

 TE =28607.27米的



重要

在矢量图层（主题）的情况下，边缘计算包括所有的景观，包括边界边缘的边缘。对比的加权边缘特征的边界处的边的权重可以被设置为零。在栅格（网格）的层（主题）的情况下，边缘计算不包括的边缘周围的景观边界边缘或任何内部边缘，包括的像素分类为无资料。



边缘密度（ED）

金额相对于景观区的边缘。

举例：边缘密度针叶树（级别）

 ED = TE / TLA

 ED = 10858.88 metres/184.11公顷=58.98米的/公顷

举例：边缘密度的所有斑块（景观水平）

 ED = 28607.27 metres/184.11公顷=155.38米的/公顷



平均斑块边缘（MPE）

平均每块边缘。

例：平均斑块边缘康（级别）

 MPE = TE / NUMP的

 MPE =10858.88米/ 4斑块=2714.72米的/斑块

例：平均斑块边缘的修补程序（景观水平）

 MPE = TE / NUMP的

 MPE = 28607.27 metres/14斑块=2043.38米的/斑块



对比加权边缘密度（CWED）

 CWED边缘的密度是衡量在景观（米每公顷）与用户指定的对比度重量。

 CWED等于0时，有没有边缘的景观，换句话说，整个景观和它的边界是由一个单独的斑块。这是作为边缘的量的的景观增加和/或作为用户增加对比度重量的值增加。



景观形状指数（LSI）



 LSI是景观边界和边界内的总景观面积（平方米）的平方根，除以一个常数（圆形标准的矢量图层，栅格）的平方标准调整所有的边缘。 LSI将增加，增加景观的形状不规则或边缘内的景观越来越多。



双对数分形维数（DLFD）

 DLFD是斑块周长的复杂性的度量。接近1时，斑块形状是“简单”，如圆或正方形，它的大小接近2斑块形状边界复杂性的增加。

平均周长面积比（MPAR）

形状的复杂性。

例如：平均周长面积比针叶树（级别）

 MPAR每一个斑块的斑块数量除以周长/面积比的总和。

 132米/公顷+ 112米/公顷+ 201米/公顷+ 84米/公顷：MPAR =（）/ 4片

 MPAR = 182米/公顷

例：平均周长面积比所有的斑块（景观水平）

 MPAR =（200米/公顷+ 132米/公顷+ ... + 175米/公顷）/ 14斑块

 MPAR = 185米/公顷



平均形状指数（MSI）

形状的复杂性。

 MSI是等于1时所有斑块是圆形的（多边形）或正方形（光栅（栅极））和增加的增加斑块形状不规则。

 MSI =总和的每个斑块的边界划分斑块面积（公顷）的平方根为每类（当分析按类别）或所有斑块时分析的景观，并调整为圆形标准（多边形），或方标准栅格（网格），除以斑块的数量。



面积加权平均形状指数（AWMSI）

 AWMSI是等于1时所有斑块是圆形的（多边形）或正方形（光栅（栅极））和增加的增加斑块形状不规则。

 AWMSI等于每个斑块的周长总和，除以的平方根斑块面积（公顷）为每一个类（当分析按类别）或所有修补程序时分析的景观，并调整为圆形标准（多边形）或方形的标准栅格（网格），除以斑块的数量。它不同于MSI的，因为它的加权斑块面积较大的修补程序将重量超过规模较小的。



平均斑块分形维数（MPFD）

形状的复杂性。

平均斑块分形的尺寸（MPFD）的形状复杂的又一举措。平均分形维数接近一个简单的周边的形状和接近2时形状更复杂。



面积加权平均斑块分维数（AWMPFD）

调整形状大小形状的复杂性。

增加了单独的修补程序适用于每个斑块的面积加权平均斑块分形维数与面积加权平均斑块分形维数是相同的。由于较大的修补程序往往比较小的斑块是更复杂的，这具有对独立于它的大小的确定修补程序的复杂性的效果。平均斑块分形维数的度量单位是相同的。



平均近邻（MNN）

的斑块隔离措施。

近邻单个贴剂的距离是最短的距离到一个类似的斑块（边缘到边缘）。平均最近邻距离是个人类在类级别之类的最近邻距离在景观水平上，平均的平均距离（米）。



 Interspersion并列指数（IJI）

衡量斑块adacency。

独特的斑块相邻的分布变得不均匀，100所有修补程序的类型也同样相邻趋近于零。

 interspersion需要由一个最小的三个类，景观。在一流水平interspersion的是一个衡量的相对interspersion每类。在景观水平上，它是衡量的interspersion的每个斑块的景观。



平均接近指数（MPI）

测量的孤立和分散的程度。

平均接近指数是衡量一个斑块的孤立和分散的程度。 MPI使用最近的邻居统计。距离阈值的默认值是100万。，如果MPI是需要在特定的距离，从主程式的下拉菜单中选择“设置MPI阈值和输入阈值的距离。

 MNN和MPI都使用类似的多边形最近的邻居统计，在他们的算法。偶尔MNN和MPI领域的空白或零报告。发生这种情况时，一个多边形的顶点接触的另一个多边形的边界，但两个相似多边形不共享一个共同的边界。当这种情况发生的感人顶点手工编辑（移动），纠正问题层（主题）。分析光栅层（网格）（主题）时，这个问题就不会发生。



 Shannon多样性指数（SDI）

测量的相对斑块多样性。

 Shannon多样性指数仅可在景观水平和斑块多样性是一个相对的措施。时，只有一个修补程序的景观斑块类型的数量或斑块类型的分布比例增加，并且随着该指数将等于零。



辛普森多样性指数（SIDI）

测量的相对斑块多样性。

辛普森多样性指数仅可在景观水平和斑块多样性是一个相对的措施。时，只有一个修补程序的景观斑块类型的数量或斑块类型的分布比例增加，并且随着该指数将等于零。



香农均匀度指数（SEI）

测量斑块的分布和数量。

 Shannon的均匀性指数为等于0时，所观察到的斑块分发是低，接近1时的修补程序类型的分布变得更均匀。香农均匀度指数只适用于景观水平。



辛普森均匀度指数（SIEI）

 SIEI是斑块类型之间的区域的分布的量度。它等于1时的分布区域间的斑块甚至是完全的。 SIEI接近于0，作为修补程序之间的分布面积越来越由一个接插型为主。



改良Simpson多样性指数（MSIDI）

 MSIDI是衡量斑块多样性。它等于0时，只有一个修补程序的景观，并增加不同类型的斑块（PR）的数量增加，面积斑块类型之间变得更加平等的。



改良Simpson均匀度指数（MSIEI）

 MSIEI是斑块类型之间的区域的分布的量度。它等于1时的分布区域间的斑块正是甚至。 SIEI接近于0，作为修补程序之间的分布面积越来越由一个接插型为主。它不同于SIEI，因为它是从改良Simpson的多样性的指数（MSIDI），而不是辛普森多样性指数（SIDI）。





重要

仅适用于光栅层（网格）（主题）核心区通过直接分析的空间统计对话。如果核心区统计所需要的矢量图层（主题），第一个创建的修补程序的核心区（创建一个新的核心区域主题）下拉菜单中，然后计算统计的法向量，你会为新的层（主题）层（主题）。结果将是核心区的统计数据。



核心区（CA）

间断核心斑块的总大小。

间断核心区斑块的总规模（公顷）。

平均核心区（MCA）

间断核心斑块的平均规模。

平均粒径为间断核心区斑块（公顷）。



核心区（NCA）

间断核心区域内每一个相应的斑块打斑块的类型（或类）的总数。



平均核心面积指数（MCAI）

 MCAI的核心区域的景观斑块的平均百分比。这将是等于0时，有没有核心区目前任何斑块的景观中，它增加（实现100％）修补程序时，大多包含核心区。



核心区标准偏差（CASD）

测量核心区面积的变化。

间断核心区面积（公顷）的标准偏差。



核心区密度（CAD）

相对于景观区的的间断核心斑块的相对数量。

景观面积除以所有间断的修补程序的总数（间断核心斑块/公顷）。



总核心面积指数（TCAI）

测量核心区的景观。

总的核心面积指数是衡量核心区的景观。总核心面积指数的比例在整个景观的核心区，是等于零时没有斑块的景观核心和核心区的景观增加的相对比例接近1。



核心区土地比例（C_LAND）

 C_LAND是由核心区的总景观的百分比。



平均每块核心区（MCA1）

 MCA1是每块平均核心区（反对到所有distunct的核心区）。

这等于每个斑块或相应的斑块类型的核心领域，相同类型的斑块总额，除以10，000（转换公顷）的数量除以的总和。



核心区变异系数（CACOV）

 CACOV表示间断分布有关的平均的核心区的核心区的大小中的可变性。



修补核心区的标准偏差（CASD1）

测量的变异斑块核心区域的大小。

标准偏差的的斑块核心区面积（公顷）。

的斑块核心区的变异系数（CACV1）

在核心领域（CASD）的标准差除以平均每块核心区（MCA）和100（％）multplied。

 variablility的平均核心区核心区之间的斑块。