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geodma:features [2014/06/20 16:09]
tkorting
geodma:features [2017/07/18 11:56] (current)
tkorting
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-====== GeoDMA Features ======+====== GeoDMA ​0.2 Features ======
  
 GeoDMA has metrics integrating Polygons, Cells, and Images. Through image segmentation,​ GeoDMA creates Polygons. ​ GeoDMA has metrics integrating Polygons, Cells, and Images. Through image segmentation,​ GeoDMA creates Polygons. ​
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 ===== Segmentation-based spectral features ===== ===== Segmentation-based spectral features =====
  
-All spectral metrics are calculated inside a polygon, when _X p_, or inside a cell, when _X C_ The spectral channel is defined by _B_+All spectral metrics are calculated inside a polygon, when $X p$, or inside a cell, when $X C$ The spectral channel is defined by $B$
  
-Some of the following equations describe features based on the Gray-Level Cooccurrence Matrix - GLCM. The term &​lt;​math&​gt;​p_{ij}&​lt;/​math&​gt; ​is the normalized frequency in which two neighboring cells separated by a fixed shift occur on the image, one with gray tone &​lt;​math&​gt;​i&​lt;/​math&​gt; ​and the other with gray tone &​lt;​math&​gt;​j&​lt;/​math&​gt;​. The constant ​&​lt;​math&​gt;​D&​lt;/​math&​gt; ​is the dimension of the GLCM, which has the same gray value range of the original image. ​+Some of the following equations describe features based on the Gray-Level Cooccurrence Matrix - GLCM. The term $p_{ij}is the normalized frequency in which two neighboring cells separated by a fixed shift occur on the image, one with gray tone $iand the other with gray tone $j$. The constant ​$Dis the dimension of the GLCM, which has the same gray value range of the original image. ​
  
-Name  Description ​ Formula ​ Range  Units +Name Description ​Formula ​Range Units 
 +| rX_amplitude_B | Defines the amplitude of the pixels inside the object. The amplitude means the maximum pixel value minus the minimum pixel value. | $px_{max} - px_{min}$ | $\geq 0$ | $px$ | 
 +| rX_dissimilarity_B | Measures how different the elements of the GLCM are from each other and it is high when the local region has a high contrast. | $i - j$ | $\geq 0$ | - | 
 +| rX_entropy_B | Measures the disorder in an image. When the image is not uniform, many GLCM elements have small values, resulting in large entropy. | $-\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} p_{ij} . \log{p_{ij}}$ | $\geq 0$ | - | 
 +| rX_homogeneity_B | Assumes higher values for smaller differences in the GLCM. | $\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} \frac{p_{ij}}{1 + (i - j)^2}$ | $\geq 0$ | - | 
 +| rX_mean_B | Returns the average value for all $N$ pixels inside the object. | $ \frac{\sum_{i=1}^N px_i}{N}$ | $\geq 0$ | $px$ |  
 +| rX_mode_B | Returns the most occurring value (mode) for all $N$ pixels inside the object. When the object is multimodal, the first value is assumed. | | $\geq 0$ | $px$ | 
 +| rX_std_B | Returns the standard deviation of all $N$ pixels ($\mu$ is the mean value). | $\sqrt{\frac{1}{N-1}\sum_{i=1}^N \left(px_i - \mu \right)^2}$ | $\geq 0$ | $px$ |
  
-rX_amplitude_B ​ 
-Defines the amplitude of the pixels inside the object. The amplitude means the maximum pixel value minus the minimum pixel value. ​ 
-&​lt;​math&​gt;​px_{max} - px_{min}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
- 
-rX_dissimilarity_B ​ 
-Measures how different the elements of the GLCM are from each other and it is high when the local region has a high contrast. ​ 
-i - j|$&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-\-  
- 
-rX_entropy_B ​ 
-Measures the disorder in an image. When the image is not uniform, many GLCM elements have small values, resulting in large entropy. ​ 
-&​lt;​math&​gt;​-\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} p_{ij} . \log{p_{ij}}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-\-  
- 
-rX_homogeneity_B ​ 
-Assumes higher values for smaller differences in the GLCM.  
-&​lt;​math&​gt;​\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} \frac{p_{ij}}{1 + (i - j)^2}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-\-  
- 
-rX_mean_B ​ 
-Returns the average value for all $N$ pixels inside the object. ​ 
-&​lt;​math&​gt;​ \frac{\sum_{i=1}^N px_i}{N}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
- 
-rX_mode_B ​ 
-Returns the most occurring value (mode) for all &​lt;​math&​gt;​N&​lt;/​math&​gt;​ pixels inside the object. When the object is multimodal, the first value is assumed. ​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
- 
-rX_std_B ​ 
-Returns the standard deviation of all &​lt;​math&​gt;​N&​lt;/​math&​gt;​ pixels (&​lt;​math&​gt;​\mu&​lt;/​math&​gt;​ is the mean value). ​ 
-&​lt;​math&​gt;​\sqrt{\frac{1}{N-1}\sum_{i=1}^N \left(px_i - \mu \right)^2}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
  
 ===== Segmentation-based spatial features ===== ===== Segmentation-based spatial features =====
  
-Name  Description ​ Formula ​ Range  Units +Name Description ​Formula ​Range Units 
 +| p_angle | Represents the main angle of an object. It is obtained by computing the minimum circumscribing ellipse, and the angle of the biggest radius of the ellipse suits to the object'​s angle. | | $\left[0, \pi\right]$ | $rad$ | 
 +| p_area | Returns the area of the object. When measured in pixels is equal to $N$. | | $\geq 0$ | $px^2$ | 
 +| p_box_area | Returns the bounding box area of an object, measured in pixels. | | $\geq 0$ | $px^2$ |  
 +| p_circle | Relates the areas of the object and the smallest circumscribing circle around the object. In the equation, $R$ is the maximum distance between the centroid and all vertices. | $1 - \frac{N}{\pi R^2}$ | $[0, 1)$ | $px^2$ | 
 +| p_elliptic_fit | Finds the minimum circumscribing ellipse to the object and returns the ratio between the object'​s area and the ellipse area. | | $\left[0, 1\right]$ | - | 
 +| p_fractal_dimension | Returns the fractal dimension of an object. | $2 \frac{\log {\frac{\textit{perimeter}}{4}} }{\log N}$ | $[1, 2]$ | - | 
 +| p_gyration_radius | This feature equals the average distance between each pixel position in one object and the object'​s centroid. The more similar to a circle is the object, the more likely the centroid will be inside it, and therefore this feature will be closer to 0. | $\textit{pos}_i - \textit{pos}_C|}{N}$ | $\geq 0$ | $px$ | 
 +| p_length | It is the height of the object'​s bounding box. | | $\geq 0$ | $px$ | 
 +| p_perimeter | It is the amount of pixels in the object'​s border. | | $\geq 0$ | $px$ | 
 +| p_perimeter_area_ratio | Calculates the ratio between the perimeter and the area of an object. | $\frac{\textit{perimeter}}{N}$ | $\geq 0$ | $px^{-1}$ | 
 +| p_rectangular_fit | This feature fits a minimum rectangle outside the object and calculates the ratio between its area and the area of this rectangle. The closer to $1$ is this feature, the most similar to a rectangle. | | $\left[0, 1\right]$ | - | 
 +| p_width | It is the width of the object'​s bounding box. | | $\geq 0$ | $px$ |
  
-p_angle ​ 
-Represents the main angle of an object. It is obtained by computing the minimum circumscribing ellipse, and the angle of the biggest radius of the ellipse suits to the object'​s angle. ​ 
-&​lt;​math&​gt;​\left[0,​ \pi\right]&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​rad&​lt;/​math&​gt;​ 
- 
-p_area ​ 
-Returns the area of the object. When measured in pixels is equal to &​lt;​math&​gt;​N&​lt;/​math&​gt;​. ​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px^2&​lt;/​math&​gt;​ 
- 
-p_box_area ​ 
-Returns the bounding box area of an object, measured in pixels. ​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px^2&​lt;/​math&​gt;​ 
- 
-p_circle ​ 
-Relates the areas of the object and the smallest circumscribing circle around the object. In the equation, &​lt;​math&​gt;​R&​lt;/​math&​gt;​ is the maximum distance between the centroid and all vertices. ​ 
-&​lt;​math&​gt;​1 - \frac{N}{\pi R^2}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​[0,​ 1)&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px^2&​lt;/​math&​gt;​ 
- 
-p_elliptic_fit ​ 
-Finds the minimum circumscribing ellipse to the object and returns the ratio between the object'​s area and the ellipse area.  
-&​lt;​math&​gt;​\left[0,​ 1\right]&​lt;/​math&​gt;​ 
-\-  
- 
-p_fractal_dimension ​ 
-Returns the fractal dimension of an object. ​ 
-&​lt;​math&​gt;​2 \frac{\log {\frac{\textit{perimeter}}{4}} }{\log N}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​[1,​ 2]&​lt;/​math&​gt;​ 
-\-  
- 
-p_gyration_radius ​ 
-This feature equals the average distance between each pixel position in one object and the object'​s centroid. The more similar to a circle is the object, the more likely the centroid will be inside it, and therefore this feature will be closer to 0.  
-\textit{pos}_i - \textit{pos}_C|}{N}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
- 
-p_length ​ 
-It is the height of the object'​s bounding box.  
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
- 
-p_perimeter ​ 
-It is the amount of pixels in the object'​s border. ​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
- 
-p_perimeter_area_ratio ​ 
-Calculates the ratio between the perimeter and the area of an object. ​ 
-&​lt;​math&​gt;​\frac{\textit{perimeter}}{N}&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px^{-1}&​lt;/​math&​gt;​ 
- 
-p_rectangular_fit ​ 
-This feature fits a minimum rectangle outside the object and calculates the ratio between its area and the area of this rectangle. The closer to &​lt;​math&​gt;​1&​lt;/​math&​gt;​ is this feature, the most similar to a rectangle. ​ 
-&​lt;​math&​gt;​\left[0,​ 1\right]&​lt;/​math&​gt;​ 
-\-  
- 
-p_width ​ 
-It is the width of the object'​s bounding box.  
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ 
-&​lt;​math&​gt;​px&​lt;/​math&​gt;​ 
  
 =====  Landscape-based features ===== =====  Landscape-based features =====
  
-When the unit is hectares, the value is divided by &​lt;​math&​gt;​10^4&​lt;/​math&​gt;​ +When the unit is hectares, the value is divided by $10^4$Please note that most of the following features are based on [[http://www.umass.edu/landeco/research/fragstats|Fragstats software]].
- +
-Name  Description ​ Formula ​ Range  Units  +
- +
-c_ca  +
-Class Area means the sum of areas of a cell.  +
-&​lt;​math&​gt;​\sum_{j=1}^n a_j&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​ha&​lt;/​math&​gt;​ +
- +
-c_percentland  +
-&​lt;​math&​gt;​\%Land&​lt;/​math&​gt;​ equals ​the sum of the areas (&​lt;​math&​gt;​m^2&​lt;/​math&​gt;​) of all patches of the corresponding patch type, divided by total landscape area (&​lt;​math&​gt;​m^2&​lt;/​math&​gt;​). &​lt;​math&​gt;​\%Land&​lt;/​math&​gt;​ equals the percentage the landscape comprised of the corresponding patch type.  +
-&​lt;​math&​gt;​\frac{\sum_{j=1}^n a_j}{A} \times 100&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\left[0, 100\right]&​lt;​/math&​gt;​ +
-&​lt;​math&​gt;​\%&​lt;​/math&​gt;​ +
- +
-c_pd  +
-Patch Density equals the number of patches of the corresponding patch type divided by total landscape area +
-&​lt;​math&​gt;​\frac{n}{A}&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ +
-Patches  +
- +
-c_mps  +
-Mean Patch Size equals the sum of the areas (&​lt;​math&​gt;​m^2&​lt;/​math&​gt;​) of all patches of the corresponding patch type, divided by the number of patches of the same type +
-&​lt;​math&​gt;​\frac{\sum_{j=1}^n a_j}{n} 10^{-4}&​lt;​/math&​gt;​ +
-&​lt;​math&​gt;​\geq 0</math&​gt;​ +
-&​lt;​math&​gt;​ha&​lt;​/math&​gt;​ +
- +
-c_pssd  +
-Patch Size Std is the root mean squared error (deviation from the mean) in patch size. This is the population standard deviation, not the sample standard deviation.  +
-&​lt;​math&​gt;​\sqrt{\frac{\sum_{j=1}^n \left(a_j - MPS \right)^2}{n}} 10^{-4}&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​ha&​lt;/​math&​gt;​ +
- +
-c_lsi  +
-Landscape Shape Index equals the sum of the landscape boundary and all edge segments (&​lt;​math&​gt;​m&​lt;/​math&​gt;​) within the boundary. This sum involves the corresponding patch type (including borders), divided by the square root of the total landscape area (&​lt;​math&​gt;​m^2&​lt;/​math&​gt;​).  +
-&​lt;​math&​gt;​\frac{\sum_{j=1}^n e_j}{2\sqrt{\pi \times A}}&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 1&​lt;/​math&​gt;​ +
-\-  +
- +
-c_msi  +
-Mean Shape Index equals the sum of the patch perimeter (&​lt;​math&​gt;​m&​lt;/​math&​gt;​) divided by the square root of patch area (&​lt;​math&​gt;​m^2&​lt;/​math&​gt;​) for each patch of the corresponding patch type.  +
-&​lt;​math&​gt;​\frac{\sum_{j=1}^n \frac{j}{2\sqrt{\pi \times a_j}}}{n}&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 1&​lt;/​math&​gt;​ +
-\-  +
- +
-c_awmsi  +
-Area-Weighted MSI equals the sum, across all patches of the corresponding patch type, of each patch perimeter (&​lt;​math&​gt;​m&​lt;/​math&​gt;​) divided by the square root of patch area (&​lt;​math&​gt;​m^2&​lt;/​math&​gt;​).  +
-&​lt;​math&​gt;​\sum_{j=1}^n \left[ \frac{j}{2 \sqrt{\pi \times a_j}} \times \frac{a_j}{\sum_{j=1}^n a_j} \right]&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 1&​lt;/​math&​gt;​ +
-\-  +
- +
-c_mpfd  +
-\-  +
- +
-c_awmpfd  +
-\-  +
- +
-c_ed  +
-Edge Density equals the sum of the lengths (&​lt;​math&​gt;​m&​lt;/​math&​gt;​) of all edge segments involving the corresponding patch type, divided by the total landscape area (&​lt;​math&​gt;​m^2&​lt;/​math&​gt;​) +
-&​lt;​math&​gt;​\frac{\sum_{j=1}^m e_j}{A} 10^{-4}&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​m/​ha&​lt;/​math&​gt;​ +
- +
-c_mpar  +
-Mean Perimeter Area Ratio equals the sum of ratios between perimeters and areas, divided by the number of patches of the same type.  +
-&​lt;​math&​gt;​\frac{ \sum_{j=1}^n \frac{j}{a_j}}{n}&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​m^{-1}&​lt;/​math&​gt;​ +
- +
-c_pscov  +
-Patch Size Coefficient of Variation calculates the ratio between the features _c_pssd_ and _c_mps_.  +
-&​lt;​math&​gt;​\frac{PSSD}{MPS} \times 100&​lt;/​math&​gt;​ +
-&​lt;​math&​gt;​\geq 0&​lt;/​math&​gt;​ +
-\-  +
- +
-c_np  +
-\-  +
- +
-c_te  +
-\-  +
- +
-c_iji  +
-\- +
  
 +| Name | Description | Formula | Range | Units |
 +| c_ca | Class Area means the sum of areas of a cell. | $\sum_{j=1}^n a_j$ | $\geq 0$ | $ha$ |
 +| c_percentland | $\%Land$ equals the sum of the areas ($m^2$) of all patches of the corresponding patch type, divided by total landscape area ($m^2$). $\%Land$ equals the percentage the landscape comprised of the corresponding patch type. | $\frac{\sum_{j=1}^n a_j}{A} \times 100$ | $\left[0, 100\right]$ | $\%$ |
 +| c_pd | Patch Density equals the number of patches of the corresponding patch type divided by total landscape area. | $\frac{n}{A}$ | $\geq 0$ | Patches |
 +| c_mps | Mean Patch Size equals the sum of the areas ($m^2$) of all patches of the corresponding patch type, divided by the number of patches of the same type. | $\frac{\sum_{j=1}^n a_j}{n} 10^{-4}$ | $\geq 0$| $ha$ |
 +| c_pssd | Patch Size Std is the root mean squared error (deviation from the mean) in patch size. This is the population standard deviation, not the sample standard deviation. | $\sqrt{\frac{\sum_{j=1}^n \left(a_j - MPS \right)^2}{n}} 10^{-4}$ | $\geq 0$| $ha$ |
 +| c_lsi | Landscape Shape Index equals the sum of the landscape boundary and all edge segments ($m$) within the boundary. This sum involves the corresponding patch type (including borders), divided by the square root of the total landscape area ($m^2$). | $\frac{\sum_{j=1}^n e_j}{2\sqrt{\pi \times A}}$| $\geq 1$| - |
 +| c_msi | Mean Shape Index equals the sum of the patch perimeter ($m$) divided by the square root of patch area ($m^2$) for each patch of the corresponding patch type. | $\frac{\sum_{j=1}^n \frac{j}{2\sqrt{\pi \times a_j}}}{n}$| $\geq 1$| - |
 +| c_awmsi | Area-Weighted MSI equals the sum, across all patches of the corresponding patch type, of each patch perimeter ($m$) divided by the square root of patch area ($m^2$). | $\sum_{j=1}^n \left[ \frac{j}{2 \sqrt{\pi \times a_j}} \times \frac{a_j}{\sum_{j=1}^n a_j} \right]$| $\geq 1$| - |
 +| c_mpfd | MPFD stands for the Mean Patch Fractal Dimension. | | | |
 +| c_awmpfd| AWMPFD stands for Area-weighted Mean Patch Fractal Dimension. | | | |
 +| c_ed | Edge Density equals the sum of the lengths ($m$) of all edge segments involving the corresponding patch type, divided by the total landscape area ($m^2$). | $\frac{\sum_{j=1}^m e_j}{A} 10^{-4}$| $\geq 0$| $m/ha$ |
 +| c_mpar | Mean Perimeter Area Ratio equals the sum of ratios between perimeters and areas, divided by the number of patches of the same type. | $\frac{ \sum_{j=1}^n \frac{j}{a_j}}{n}$| $\geq 0$| $m^{-1}$ |
 +| c_pscov | Patch Size Coefficient of Variation calculates the ratio between the features _c_pssd_ and _c_mps_. | $\frac{PSSD}{MPS} \times 100$| $\geq 0$| - |
 +| c_np | NP equals the number of patches inside a particular landsacape. | $n$ | $\geq 0$ | - |
 +| c_te | TE equals the total size of the edge. | $\sum_{j=0}^n e_j$| $\geq 0$ | $ha$ |
 +| c_iji | IJI stands for Interspersion and Juxtaposition Index. ​ The observed interspersion over the maximum possible interspersion for the given number of patch types. | $\frac{-\sum_{j=1}^n e_j \ln(e_j)}{\ln(n - 1)}$ | $[0, 100]$ | $\%$ |

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