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tutorial:building_a_land-use_and_land-cover_change_simulation_model [2017/01/25 15:06] francisco [Fifth step: Setting up and running a LUCC simulation model] |
tutorial:building_a_land-use_and_land-cover_change_simulation_model [2017/10/17 03:23] (current) admin |
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| ==== Second step: Calculating ranges to categorize gray-tone variables ==== | ==== Second step: Calculating ranges to categorize gray-tone variables ==== | ||
| - | The Weights of Evidence method [[http://dx.doi.org/10.1016/0040-1951(93)90011-8|(Goodacre et al. 1993]] | + | The Weights of Evidence method [[http://dx.doi.org/10.1016/0040-1951(93)90011-8|(Goodacre et al. 1993]][[https://books.google.com/books?printsec=frontcover&vid=ISBN0080424201&vid=ISBN0080418678&vid=LCCN94028315#v=onepage&q&f=false|, Bonham-Carter 1994)]] is applied in Dinamica EGO to produce a transition probability map (fig. 3), which depicts the most favourable areas for a change [[http://dx.doi.org/10.1016/S0304-3800(02)00059-5|(Soares-Filho et al. 2002]][[http://dx.doi.org/ 10.1111/j.1529-8817.2003.00769.x|, 2004)]]. |
| - | [[http://www.rc.unesp.br/igce/geologia/GAA01048/papers/Bonham-Carter_Cap9.pdf|; Bonham-Carter, 1994)]] is applied in Dinamica EGO to produce a transition probability map (fig. 3), which depicts the most favourable areas for a change [[http://dx.doi.org/10.1016/S0304-3800(02)00059-5|(Soares-Filho et al. 2002]][[http://dx.doi.org/ 10.1111/j.1529-8817.2003.00769.x|, 2004)]]. | + | |
| Weights of Evidence consists of a Bayesian method, in which the effect of a spatial variable on a transition is calculated independently of a combined solution. The Weights of Evidence represent each variable’s influence on the spatial probability of a transition i-j and are calculated as follows. | Weights of Evidence consists of a Bayesian method, in which the effect of a spatial variable on a transition is calculated independently of a combined solution. The Weights of Evidence represent each variable’s influence on the spatial probability of a transition i-j and are calculated as follows. | ||
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| }}] | }}] | ||
| - | Since Weights of Evidence only applies to categorical data, it is necessary to categorize continuous gray-tone maps (quantitative data, such as distance maps, altitude, and slope). A key issue to any categorization process concerns the preservation of the data structure. The present method adapted from Agterberg & BonhamCarter (1990), calculates ranges according to the data structure by first establishing a minimum delta – specified as the increment in the graphical interface – (//Dx//) for a continuous gray-tone variable x that is used to build n incremental buffers (//Nx//) comprising intervals from //X<wrap lo>minimum</wrap>// to //X<wrap lo>minimum</wrap>// + //nDx//.Each //n// defines a threshold that divides the map into two classes: //(Nx)// and //(Nx2)//. //An// is the number of cells for a buffer (//Nx//) multiple of //n// and //dn// is the number of occurrences for the modeled event (//D//) within this buffer. The quantities An and dn are obtained for an ordered sequence of buffers //N(xminimum + nDx)//. Subsequently, values of //W+// for each buffer are calculated using equations 2 to 4. A sequence of quantities //An// is plotted against //An*exp(W+)//. Thereafter breaking points for this graph are determined by applying a line-generalizing algorithm (Intergraph, 1991) that contains three parameters: 1) minimum distance interval along //x, mindx//, 2) maximum distance interval along //x, maxdx//, and 3) tolerance angle //ft//. For //dx// (a distance between two points along x) between //mindx// and //maxdx//, a new breaking point is placed whenever //dx >= maxdx// (an angle between //v// and //v’//- vectors linking the current to the last point and the last point to its antecedent, respectively) exceeds the tolerance angle //ft//. Thus, the number of ranges decreases as a function of ft. The ranges are finally defined by linking the breaking points with straight lines. Note that //An// is practically error-free whereas //dn// is subject to a considerable amount of uncertainty because it is regarded as the realization of a random variable. Since small //An// can generate noisy values for //W+//, [[http://dx.doi.org/10.1016/0040-1951(93)90011-8|Goodacre et al. (1993)]] suggest that, instead of calculating it employing equations 2 and 4, one should estimate //W+// for each defined range through the following expression: | + | Since Weights of Evidence only applies to categorical data, it is necessary to categorize continuous gray-tone maps (quantitative data, such as distance maps, altitude, and slope). A key issue to any categorization process concerns the preservation of the data structure. The present method adapted from Agterberg & Bonham-Carter (1990), calculates ranges according to the data structure by first establishing a minimum delta – specified as the increment in the graphical interface – (//Dx//) for a continuous gray-tone variable x that is used to build n incremental buffers (//Nx//) comprising intervals from //X<wrap lo>minimum</wrap>// to //X<wrap lo>minimum</wrap>// + //nDx//.Each //n// defines a threshold that divides the map into two classes: //(Nx)// and //(Nx2)//. //An// is the number of cells for a buffer (//Nx//) multiple of //n// and //dn// is the number of occurrences for the modeled event (//D//) within this buffer. The quantities An and dn are obtained for an ordered sequence of buffers //N(xminimum + nDx)//. Subsequently, values of //W+// for each buffer are calculated using equations 2 to 4. A sequence of quantities //An// is plotted against //An*exp(W+)//. Thereafter breaking points for this graph are determined by applying a line-generalizing algorithm (Intergraph, 1991) that contains three parameters: 1) minimum distance interval along //x, mindx//, 2) maximum distance interval along //x, maxdx//, and 3) tolerance angle //ft//. For //dx// (a distance between two points along x) between //mindx// and //maxdx//, a new breaking point is placed whenever //dx >= maxdx// (an angle between //v// and //v’//- vectors linking the current to the last point and the last point to its antecedent, respectively) exceeds the tolerance angle //ft//. Thus, the number of ranges decreases as a function of ft. The ranges are finally defined by linking the breaking points with straight lines. Note that //An// is practically error-free whereas //dn// is subject to a considerable amount of uncertainty because it is regarded as the realization of a random variable. Since small //An// can generate noisy values for //W+//, [[http://dx.doi.org/10.1016/0040-1951(93)90011-8|Goodacre et al. (1993)]] suggest that, instead of calculating it employing equations 2 and 4, one should estimate //W+// for each defined range through the following expression: |
| {{:tutorial:lucc_11.jpg?200|}} (5) | {{:tutorial:lucc_11.jpg?200|}} (5) | ||
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| In addition to the initial and final landscape maps, this model receives a raster cube composed of a series of static maps, e.g. vegetation, soil, altitude (they are named so because they do not change during model iteration. A raster cube encompasses a set of co-registered map layers. | In addition to the initial and final landscape maps, this model receives a raster cube composed of a series of static maps, e.g. vegetation, soil, altitude (they are named so because they do not change during model iteration. A raster cube encompasses a set of co-registered map layers. | ||
| - | Open the file ''23267statics.ers'' from ''\setup_run_and_validate_a_lucc_model\originals'' on the Map Viewer. An option to select the layer will appear on the maps container, it has a combobox to select it into filed Layer of the Map Viewer. Change the layer to examine the other maps. <note tip>**TIP**: you can build a raster cube assembling a set of co-registered raster maps through the functor //[[:Create Cube Map]]// and extract a layer from the cube using the functor //[[:Extract Map Layer]]//. Cube raster data are only supported in ER format.</note> | + | Open the file ''23267statics.ers'' from ''\setup_run_and_validate_a_lucc_model\originals'' on the Map Viewer. An option to select the layer will appear on the Maps (right of window), it has a combobox into field Layer to select it. Change the layer to examine the other maps. <note tip>**TIP**: you can build a raster cube assembling a set of co-registered raster maps through the functor //[[:Create Cube Map]]// and extract a layer from the cube using the functor //[[:Extract Map Layer]]//. Cube raster data are only supported in ER format.</note> |
| Furthermore, Dinamica EGO can incorporate dynamic layers into the simulation, which are so-called because they are updated during model iteration. For this model you will include the variable "distance to previously deforested areas" as a dynamic map. For this purpose, the model employs the functor //[[:Calc Distance Map]]//. Open it with the Edit Functor Ports. | Furthermore, Dinamica EGO can incorporate dynamic layers into the simulation, which are so-called because they are updated during model iteration. For this model you will include the variable "distance to previously deforested areas" as a dynamic map. For this purpose, the model employs the functor //[[:Calc Distance Map]]//. Open it with the Edit Functor Ports. | ||
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| {{ :tutorial:lucc_16.jpg |}} | {{ :tutorial:lucc_16.jpg |}} | ||
| - | Instead of //[[:Number Map]]//, now you find //[[:Name Map]]// within this container. This functor is applied to containers that need a map name or alias to identify the maps passed to them. //[[:Name Map]]// is found in the Create Hook into container´s toolbar. This can be any name, but you must be consistent, therefore using the same names when setting the container internal parameters, as shown below. Examples of containers that need Name Map are //[[:Determine Weights Of Evidence Ranges]]//, //[[:Determine Weights Of Evidence Coefficients]]//, and //[[:calc_w._of_e._probability_map|Calc W. Of E. Probability Map]]//. | + | Instead of //[[:Number Map]]//, now you find //[[:Name Map]]// within this container. This functor is applied to containers that need a map name or alias to identify the maps passed to them. //[[:Name Map]]// is found in the Create Hook into container action bar. This can be any name, but you must be consistent, therefore using the same names when setting the container internal parameters, as shown below. Examples of containers that need Name Map are //[[:Determine Weights Of Evidence Ranges]]//, //[[:Determine Weights Of Evidence Coefficients]]//, and //[[:calc_w._of_e._probability_map|Calc W. Of E. Probability Map]]//. |
| There are two //[[:Name Map]]// functors within this container, one for the map ''23267statitcs.ers'' and another for the distance map output from the //[[:Calc Distance Map]]//. | There are two //[[:Name Map]]// functors within this container, one for the map ''23267statitcs.ers'' and another for the distance map output from the //[[:Calc Distance Map]]//. | ||
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| ==== Fourth step: Analyzing map correlation ==== | ==== Fourth step: Analyzing map correlation ==== | ||
| - | The only assumption for the Weights of Evidence method is that the input maps have to be spatially independent. A set of measures can be applied to assess this assumption, such as the Cramer test and the Joint-Uncertainty Information [[http://www.rc.unesp.br/igce/geologia/GAA01048/papers/Bonham-Carter_Cap9.pdf|( Bonham-Carter, 1994)]]. As a result, correlated variables must be disregarded or combined into a third that will replace the correlated pair in the model. | + | The only assumption for the Weights of Evidence method is that the input maps have to be spatially independent. A set of measures can be applied to assess this assumption, such as the Cramer test and the Joint-Uncertainty Information [[https://books.google.com/books?printsec=frontcover&vid=ISBN0080424201&vid=ISBN0080418678&vid=LCCN94028315#v=onepage&q&f=false|(Bonham-Carter, 1994)]]. As a result, correlated variables must be disregarded or combined into a third that will replace the correlated pair in the model. |
| Open model ''weights_of_evidence_correlation.egoml'' in ''setup_run_and_validate_a_lucc_ model\4_weights_of_evidence_correlation''. | Open model ''weights_of_evidence_correlation.egoml'' in ''setup_run_and_validate_a_lucc_ model\4_weights_of_evidence_correlation''. | ||
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| \\ | \\ | ||
| \\ | \\ | ||
| - | This model performs pairwise tests for categorical maps in order to test the independence assumption. Methods employed are the Chi^2, Crammers, the Contingency, the Entropy and the Uncertainty Joint Information [[http://www.rc.unesp.br/igce/geologia/GAA01048/papers/Bonham-Carter_Cap9.pdf|( Bonham-Carter, 1994)]]. In addition to the links to be connected, the only parameter to be set in the Determine Weights of Evidence Correlation is the transition as follows: | + | This model performs pairwise tests for categorical maps in order to test the independence assumption. Methods employed are the Chi^2, Cramer, the Contingency, the Entropy and the Uncertainty Joint Information [[https://books.google.com/books?printsec=frontcover&vid=ISBN0080424201&vid=ISBN0080418678&vid=LCCN94028315#v=onepage&q&f=false|(Bonham-Carter, 1994)]]. In addition to the links to be connected, the only parameter to be set in the Determine Weights of Evidence Correlation is the transition as follows: |
| {{ :tutorial:lucc_26.2.jpg |}}\\ | {{ :tutorial:lucc_26.2.jpg |}}\\ | ||
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| ==== Fifth step: Setting up and running a LUCC simulation model ==== | ==== Fifth step: Setting up and running a LUCC simulation model ==== | ||
| - | Let’s start setting up the deforestation simulation model by loading the input data. You will need //[[:Load Categorical Map]]// to load the initial landscape: ''original/23267_1997.ers'', //[[:Load Map]]// for ''originals/23267statics.ers'', //[[:Load Weights]]// for ''new_weights.dcf'', and //[[:Load Lookup Table]]// for the multi-step transition matrix: ''originals/multiple_steps.csv'' because you will run the model in annual time-steps. Add the following comments to each functor: | + | Let’s start setting up the deforestation simulation model by loading the input data. You will need //[[:Load Categorical Map]]// to load the initial landscape: ''originals/23267_1997.ers'', //[[:Load Map]]// for ''originals/23267statics.ers'', //[[:Load Weights]]// for ''new_weights.dcf'', and //[[:Load Lookup Table]]// for the multi-step transition matrix: ''originals/multiple_steps.csv'' because you will run the model in annual time-steps. Add the following comments to each functor: |
| {{ :tutorial:lucc_28.jpg |}} | {{ :tutorial:lucc_28.jpg |}} | ||
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| {{ :tutorial:lucc_56.jpg |}} | {{ :tutorial:lucc_56.jpg |}} | ||
| - | 5th Step------------------------------------------------------------------------23267_2000 --------------------------------------------------------This Step | + | 5th Step---------------------------------------------- 23267_2000 ----------------------------------------------This Step |
| Note that the simulated landscape from this step shows a landscape structure closer to that of the final historical landscape. Let’s now add the //[[:Expander]]// Functor to the simulation model. | Note that the simulated landscape from this step shows a landscape structure closer to that of the final historical landscape. Let’s now add the //[[:Expander]]// Functor to the simulation model. | ||