| Identification Information | |||
| Model Title | SLEUTH | ||
| Version of Model | 3.0 | ||
| Responsible Party of Model | Compound | ||
| Responsible Party Individual Name | Keith Clarke | ||
| Organization Affiliated with Responsible Party | University of California, Santa Barbara, Geography Department | ||
| Position Name of Responsible Party | Professor | ||
| Responsible Party Contact Information | Compound | ||
| Delivery Point | University of California, Santa Barbara | ||
| Ellison Hall 3611 | |||
| City | Santa Barbara | ||
| Administrative Area | CA | ||
| Postal Code | 93106-4060 | ||
| Country | Unites States of America | ||
| Electronic Mail Address | kclarke@geog.ucsb.edu | ||
| Telephone Number | (805) 893-7961 | ||
| Facsimile Number | (805) 893-3146 | ||
| Date of Creation | February, 2000 | ||
| Model Citation | Clarke, K., (2000) SLEUTH: Land Cover transition Model, version 3.0, http://www.ncgia.ucsb.edu/projects/gig/project_gig.htm | ||
| Intended Use | |||
| Application Purpose | 002 - Education | ||
| 004 - Public Administration | |||
| 099 - Other | |||
| Other Application Purpose | Urban Sprawl | ||
| Educational Level | 006 - Graduate Studies | ||
| Description | |||
| Conceptual Model Description | SLEUTH: land cover transition model is a cellular automata urban growth model which is intended to simulate urban growth ranging in spatial extent from individual metropolitan areas to national coverage in order to aid in understanding how expanding urban areas consume their surrounding land, and the environmental impact it has on the local environment. This model simulates the transition from non-urban to urban land-use using a grid of cells (cellular automata) and of whose land-use state is dependent upon local factors (e.g. roads, existing urban areas, topography), temporal factors, and random factors. The growth is based on four "growth rules" or types of growth which include Spontaneous Growth, Road Influence, New Spread Center, and Edge Growth. | ||
| The first in the time series of input data files act as the seed data on which these growth rules project the urbanization of the area. The modeler has influence over these growth rules through five coefficients. These coefficients include dispersion, breed, spread, slope and road gravity. These coefficients influence the rate of urbanization in a variety of methods. The subsequent input files affect the dynamic properties of the coefficients. | |||
| The Model Process includes three phases: Calibration, Prediction and Testing. The calibration mode is a process by which a set of best fit parameters are derived for a data set. There are three phases of calibration: coarse, fine and final. After parameter values have been selected these are used as input for urban and landcover prediction. The test mode has two functions. The first is testing and confirming the functions of the model. Test mode will take input named in the schedule files and perform a single run on the data. (e.g.; the excluded area is in fact not being urbanized.) | |||
| If the images do not make sense there is probably an error in the input data format. The second function of the test mode is creating animated frames to simulate historical growth or create a single projection of the future. Calibrate file options: (0) "existing" will execute the model with the calibrate file that was created last (1) "new" will create a new calibrate file and overwrite previously entered preferences (2) "crashed" will restart the model from the last set of coefficient parameters in the case of a run interruption. | |||
| Model Typology | 011 - Cellular Automata | ||
| Topic or Field of Study | 1205 - Urban Development | ||
| Related Model | Compound | ||
| Related Model Citation | Batty, M., (1995) "The Computable City," Keynote Address: Fourth International Conference on Computers in Urban Planning and Urban Management, Melbourne, Australia, July 11-14. http://www.geog.buffalo.edu/Geo666/batty/melbourne.html | ||
| Batty, M., Longley, P., (1994a) Fractal Cities. London: Academic Press. | |||
| Batty, M., Xie, Y., (1994b) "From Cells to Cities," Environment and Planning B vol. 21; S31-S48. | |||
| White, R., Engelen, G., (1992a) "Cellular dynamics and GIS: modelling spatial complexity," working paper no. 9263, Research Institute for Knowledge Systems (RIKS), Maastricht, The Netherlands. | |||
| White, R., Engelen, G., (1992b) "Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land use patterns," working paper no. 9264, Research Institute for Knowledge Systems (RIKS), Maastricht, The Netherlands. | |||
| Source of Additional Information | Compound | ||
| Additional Information Text | Additional information can be found at the project web site. | ||
| Additional Information URL Address | http://www.ncgia.ucsb.edu/projects/gig/project_gig.htm | ||
| Access and Availability | |||
| Access or Use Constraints | 001 - None: Public Domain | ||
| Other Constraints | None | ||
| Availability Contact | Compound | ||
| Availability Contact Individual Name | Keith Clarke | ||
| Organization Affiliated with Availability Contact | University of California, Santa Barbara, Geography Department | ||
| Position Name of Availability Contact | Professor | ||
| Availability Contact Information | Compound | ||
| Delivery Point | University of California, Santa Barbara | ||
| Ellison Hall 3611 | |||
| City | Santa Barbara | ||
| Administrative Area | CA | ||
| Postal Code | 93106-4060 | ||
| Country | Unites States of America | ||
| Electronic Mail Address | kclarke@geog.ucsb.edu | ||
| Telephone Number | (805) 893-7961 | ||
| Facsimile Number | (805) 893-3146 | ||
| Ordering or Access Procedure | The model can be downloaded directly from the following web site: http://www.ncgia.ucsb.edu/projects/gig/download.htm | ||
| System Requirements | |||
| Hardware Requirements | A PC workstation or mainframe | ||
| Software Requirements | X- Windows, (for dynamic output amnimations) whirlgif, C compiler | ||
| Operating System | Unix or Linux | ||
| Expertise Required | Compound | ||
| Expertise to Obtain | The model and associated files are available for download from a public HTML account. Knowledge required to download includes basic understanding of HTML navigation and zip file conversions. | ||
| Expertise to Run | The minimum required knowledge required to run the model includes: C programming language, geographic data and information systems, cellular automaton modeling, and land cover modeling, as well as covering the information available at the documenting web site: http://www.ncgia.ucsb.edu/projects/gig/v2/Imp/implement.htm | ||
| Input Data Requirements | |||
| Input Data Extent and Resolution | Compound | ||
| Spatial Resolution and Extent Explanation | The spatial scale and extent are user-defined, and, therefore, are variable. Although it has been used on a city to county scale, The model extent is being increased towards national and global scale. | ||
| Temporal Resolution | It is assumed that one monte carlo growth cycle represents a year of growth. | ||
| Temporal Extent | For statistical calibration of the model at least four urban time periods must be used, although a result can be obtained with only two. Also, for purposes of calibration, the roads must be represented in two or more time periods. The model requires two landuse layers for deltatron landuse modeling. The model can operate more then 100 years into the past and up to 50 years into the future. | ||
| Input Data File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/abData.htm; http://www.ncgia.ucsb.edu/projects/gig/v2/About/abGrowth.htm | ||
| Input Modeling Construct Description | Compound | ||
| Name of Construct | Slope | ||
| Construct Classification | 02 - adjustable static parameter | ||
| Construct Description | As a dataset member, values in each cell of the dataset .gif file represents the percentage of slope at that pixel address. | ||
| Construct Input Source | dataset member | ||
| Dataset | slope_data | ||
| Construct Type | integer in each cell of the dataset .gif file | ||
| Construct Units | percentage | ||
| Minimum Value | 0 | ||
| Maximum Value | 100 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | The slope is commonly derived from a digital elevation model (DEM), but other elevation source data may be used. Cell values must be in percent slope, not degree, which is a common default in some GIS software. | ||
| Name of Construct | Land Use | ||
| Construct Classification | 02 - adjustable static parameter | ||
| Construct Description | As a dataset member, values in each cell of the dataset .gif file represents the land use at that pixel address. | ||
| Construct Input Source | dataset member | ||
| Dataset | landuse_data | ||
| Construct Type | integer in each cell of the dataset .gif file | ||
| Construct Units | values vary depending on the land use of the cell location. Each cell value should represent a unique land class. These values can be based on such schaemas as the Anderson Classification System, which is used to classify land cover. | ||
| Minimum Value | 0 | ||
| Maximum Value | 255 | ||
| Construct Repeatability | 1 | ||
| Name of Construct | Excluded | ||
| Construct Classification | 02 - adjustable static parameter | ||
| Construct Description | As a dataset member, values in each cell of the dataset .gif file represents the presents or absence of excluded, or undevelopable, land at that pixel address. | ||
| Construct Input Source | dataset member | ||
| Dataset | excluded_data | ||
| Construct Type | integer in each cell of the dataset .gif file | ||
| Construct Units | Two options are available for this construct. The values can be based on a binary value (zero representing locations able to be urbanized), or can range between 0 - 100 based on the degree (based on percentage value) of existing or desired exclusion of that pixel location. For example, wetlands would be represented with a very low (percentage) value, based on the idea that the location is a desired area to preserve or that the water is difficult to divert in order to urbanize a location. | ||
| Minimum Value | 0 | ||
| Maximum Value | 100 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | Each pixel can be assigned a value between 0 - 255, however, values over 100 are read as 100. | ||
| Name of Construct | Urban | ||
| Construct Classification | 02 - adjustable static parameter | ||
| Construct Description | As a dataset member, values in each cell of the dataset .gif file represents a binary value or presence or absence of urban land use at that pixel address. The values can also be varied by the user to represent different urban land use practices at the pixel location. | ||
| Construct Input Source | dataset member | ||
| Dataset | urban_data | ||
| Construct Type | integer in each cell of the dataset .gif file | ||
| Construct Units | The definition of "urban extent" is at the discretion of the creator of the dataset. The model requires a simple binary classification of urban/non-urban. | ||
| Minimum Value | 0 | ||
| Maximum Value | 255 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | The urban extent for the start year, or seed, is used to initialize the model and is the basis for the CA driven urban growth. For calibration, the earliest urban year is used as the seed, and subsequent urban layers, or control years, are used to measure several statistical best fit values. For this reason, at least four urban layers are needed for calibration. | ||
| Name of Construct | Transportation | ||
| Construct Classification | 02 - adjustable static parameter | ||
| Construct Description | As a dataset member, values in each cell of the dataset .gif file represents the presence or absence of a road at that pixel address. The representation can be binary (road/no road) or can have a weighted, relative value depending on the accessibility or use of the road. | ||
| Construct Input Source | dataset member | ||
| Dataset | road_data | ||
| Construct Type | integer in each cell of the dataset .gif file | ||
| Construct Units | The value selected for roads can represent a a binary (road present / road not present) or can rank the accessibility or usage of the road based on the modelers' discresion. | ||
| Minimum Value | 0 | ||
| Maximum Value | 255 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | The road influenced growth dynamic included in SLEUTH simulates the tendency of urban development to be attracted to locations on increased accessibility. | ||
| Name of Construct | Hill Shade | ||
| Construct Classification | 02 - adjustable static parameter | ||
| Construct Description | As a dataset member, values in each cell of the dataset .gif file assumed hillshade image of the extent of the study area. The primary function of this dataset is assist in understanding the spatial context of the region. | ||
| Construct Input Source | dataset member | ||
| Dataset | background_data | ||
| Construct Type | integer in each cell of the dataset .gif file | ||
| Construct Units | The pixel values represent the hill shade of the image, based on the aspect and slope of the particular cell which is derived from the DEM or other digital elevation data. | ||
| Minimum Value | 0 | ||
| Maximum Value | 255 | ||
| Construct Repeatability | 1 | ||
| Name of Construct | Dispersion Coefficient | ||
| Construct Classification | 03 - adjustable dynamic parameter | ||
| Construct Description | The dispersion coefficient (previously referred to as diffusion coefficient) controls the number of times a pixel will be randomly selected for possible urbanization. | ||
| Construct Input Source | dataset member | ||
| Dataset | scenario | ||
| Construct Type | integer value | ||
| Construct Units | Percentage value based on the likelihood of dispersion | ||
| Minimum Value | 0 | ||
| Maximum Value | 100 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | Effects Spontaneous Growth and the search distance along the road network as part of the Road Influence Growth. | ||
| Name of Construct | Breed Coefficient | ||
| Construct Classification | 03 - adjustable dynamic parameter | ||
| Construct Description | The breed coefficient determines the probability of a spontaneous growth pixel becoming a new spreading center. The breed coefficient also determines the number of times a road trip will be taken. | ||
| Construct Input Source | dataset member | ||
| Dataset | scenario | ||
| Construct Type | integer value | ||
| Construct Units | A percentage value which determines the likelihood that cell neighboring a previously urbanized cell will also become urbanized. | ||
| Minimum Value | 0 | ||
| Maximum Value | 100 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | Influences the New Spread Center probability and affects the number of Road Influence Growth attempts. | ||
| Name of Construct | Spread Coefficient | ||
| Construct Classification | 03 - Adjustable Dynamic Parameter | ||
| Construct Description | The spread coefficient determines the probability that any pixel that is part of a spreading center (a cluster of urban pixels > 2) will generate an additional urban pixel in its neighborhood. | ||
| Construct Input Source | dataset member | ||
| Dataset | scenario | ||
| Construct Type | integer value | ||
| Construct Units | A percentage value which influences the likelihood of urban spread. | ||
| Minimum Value | 0 | ||
| Maximum Value | 100 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | The spread coefficient determines the probability of Organic Growth from established urban pixels occurring. | ||
| Name of Construct | Slope Coefficient | ||
| Construct Classification | 03 - Adjustable Dynamic Parameter | ||
| Construct Description | The slope_coefficient affects all growth rules in the same way: When a location is being tested for suitability for urbanization, the topography, or slope, at that location is considered. Instead of enforcing a simple linear relationship between slope and urban development, the slope_coefficient acts as a multiplier. If the slope coefficient is high, increasingly steeper slopes are less likely to urbanize. As the slope coefficient gets closer to zero, an increase in local slope has less affect on the likelihood of urbanization. | ||
| Construct Input Source | dataset member | ||
| Dataset | scenario | ||
| Construct Type | integer value | ||
| Construct Units | Percentage value influencing the development of urban areas on slopes. | ||
| Minimum Value | 0 | ||
| Maximum Value | 100 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | As value increases, the ability to urbanize steepening slopes decreases. | ||
| Name of Construct | Road Gravity Coefficient | ||
| Construct Classification | 03 - Adjustable Dynamic Parameter | ||
| Construct Description | The maximum search distance for a road from a pixel selected for a road trip is determined as some proportion of the image dimensions. | ||
| Construct Input Source | dataset member | ||
| Dataset | scenario | ||
| Construct Type | integer value | ||
| Construct Units | The value assigned to the road gravity coefficient influences the affect that roads have on urban development. The exact method is described below under "construct comments" | ||
| Minimum Value | 0 | ||
| Maximum Value | 100 | ||
| Construct Repeatability | 1 | ||
| Construct Comments | Applied value is derived from coefficient by: rg_value = (rg_coeff/MAX_ROAD_VALUE) * (row + col) where MAX_ROAD_COEFF_VALUE is defined as 100, and (row, col) are the row and column pixel counts, so that rg_value at its maximum (rg_coeff == 100) will be 1/16 of the image dimensions. If the rg_coeff value is less than 100, then the rg_value will be some proportion less than 1/16 of the image dimensions. rg_value is applied to spontaneous growth by: max_search_index = 4 * (rg_value * (1 + rg_value)) where rg_value defines maximum number of neighborhoods from selected newly urban pixel to search for a road. The first neighborhood (rg_value == 1) is made up of the selected urban pixel's adjacent 8 cells. The second neighborhood (rg_value == 2) would be the 16 pixels outwardly adjacent to the first neighborhood, etc. In this way the outward search for a road will continue until (a) a road is found, or (b) the search distance is greater than max_search_index. | ||
| Input Dataset Description | Compound | ||
| Name | slope_data | ||
| Input Dataset File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/dtInput.htm | ||
| Conceptual Data Structure | SLEUTH requires an input of grayscale .gif files. The model requires all input data layers to have a consistent number of rows and columns and be in the same projection. | ||
| Computational Representation | grayscale .gif image file | ||
| Dataset Repeatability | 1 | ||
| Name | landuse_data | ||
| Input Dataset File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/dtInput.htm | ||
| Conceptual Data Structure | SLEUTH requires an input of grayscale .gif files. The model requires all input data layers to have a consistent number of rows and columns and be in the same projection. | ||
| Computational Representation | grayscale .gif image file | ||
| Dataset Repeatability | 2+n | ||
| Name | excluded_data | ||
| Input Dataset File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/dtInput.htm | ||
| Conceptual Data Structure | SLEUTH requires an input of grayscale .gif files. The model requires all input data layers to have a consistent number of rows and columns and be in the same projection. | ||
| Computational Representation | grayscale .gif image file | ||
| Dataset Repeatability | 1+n | ||
| Name | urban_data | ||
| Input Dataset File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/dtInput.htm | ||
| Conceptual Data Structure | SLEUTH requires an input of grayscale .gif files. The model requires all input data layers to have a consistent number of rows and columns and be in the same projection. | ||
| Computational Representation | grayscale .gif image file | ||
| Dataset Repeatability | 4+n | ||
| Name | road_data | ||
| Input Dataset File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/dtInput.htm | ||
| Conceptual Data Structure | SLEUTH requires an input of grayscale .gif files. The model requires all input data layers to have a consistent number of rows and columns and be in the same projection. | ||
| Computational Representation | grayscale .gif image file | ||
| Dataset Repeatability | 1+n | ||
| Name | hillshade_data | ||
| Input Dataset File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/dtInput.htm | ||
| Conceptual Data Structure | SLEUTH requires an input of grayscale .gif files. The model requires all input data layers to have a consistent number of rows and columns and be in the same projection. | ||
| Computational Representation | grayscale .gif image file | ||
| Dataset Repeatability | 1 | ||
| Name | scenario | ||
| Input Dataset File | http://www.ncgia.ucsb.edu/projects/gig/v2/About/data_files/scenario_file.htm | ||
| Conceptual Data Structure | The scenario file consists of, in excess of 50 constructs, divided into 13 sections. These sections are: I: Path Name Variables; II: Running Status; III: Output ASCII Files; IV: Log File Preferences; V: Working Grids; VI: Random Number Seed; VII: Monte Carlo Iteration; VIII: Coefficients; IX: Prediction Date Range; X: Input Images; XI: Output Images; XII: Colortable Settings; XIII: Self Modified Parameters. The description of these constructs can be found in the input data file provided above. Only the 5 coefficients (sec. VIII) have been described in detail under "Input Modeling Construct Description." | ||
| Computational Representation | The scenario file is in an ASCII file format consisting of the formatted construct name followed by the desired value. | ||
| Dataset Repeatability | 1 | ||
| Data Processing | |||
| Programming Language | C program running under UNIX that uses the standard C compiler (cc). It can be formatted for any other standard C compiler. | ||
| Algorithmic Representation | Each coefficient has a different influence over the growth rules. Details about the influence of these coefficients can be found at the following file: http://www.ncgia.ucsb.edu/projects/gig/v2/About/gwRules.htm | ||
| Iterative Cycles | The model runs on a Monte Carlo iteration cycle. The number of cycles can be set by the modeler before the modeling process begins. The output files and data are in a different format from the input data files. | ||
| Model Output | |||
| Output Representation | Compound | ||
| Output Name | animated_urban.gif | ||
| Output Description | A GIF animation of the <location>_urban_{date}.gif files compiled by whirlgif | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not Numeric | ||
| Output Computational Representation | A series of .gif images constructed in whirlgif to be an animation. | ||
| Output Visualization | dynamic | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | Optional Output | ||
| Output Name | animated_land_n_urban.gif | ||
| Output Description | A GIF animation of the <location>land_n_urban_{date}.gif files compiled by whirlgif | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not Numeric | ||
| Output Computational Representation | A series of .gif images constructed in whirlgif to be an animation. | ||
| Output Visualization | dynamic | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | Optional Output | ||
| Output Name | animated_z_growth.gif | ||
| Output Description | A GIF animation of the z_growth_types_{run}_{monte carlo}_{date}.gif files compiled by whirlgif | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | A series of .gif images constructed in whirlgif to be an animation. | ||
| Output Visualization | dynamic | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Output Name | animated_deltron.gif | ||
| Output Description | A GIF animation of the deltatron_{run}_{monte carlo}_{date}.gif files compiled by whirlgif | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | A series of .gif images constructed in whirlgif to be an animation. | ||
| Output Visualization | dynamic | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Output Name | cumcolor_landuse.gif | ||
| Output Description | A GIF image map of modal or "winning" land classes across monte carlo iterations for the stop date. | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | standard output | ||
| Output Name | cumulate_urban.gif | ||
| Output Description | A non-classified GIF image map of urban probabilities for the stop date | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | standard output | ||
| Output Name | deltatron_{run}_{monte carlo}_{date}.gif | ||
| Output Description | GIF image maps of deltatrons color classified by age. Images are produced for run, monte carlo, and date range specified by the DELTATRON_TYPE_PRINT_WINDOW flag in the scenario file. | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Output Name | echo_of_<location>.{attribute}.gif | ||
| Output Description | duplication image of input data | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Output Name | key_{colormap_type}.gif | ||
| Output Description | A GIF image map of all color table settings except GRAYSCALE (which is automatically set to 0-255). The (row, col) image dimensions are (256, number_of_image_columns). | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Output Name | <location>_cumcolor_urban_<stop_date>.gif | ||
| Output Description | A GIF image map of color classified urban probabilities for the stop date If land use is not being modeled (urban only) this image is the same as the annual. The hillshade image is used in the background. | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | standard output | ||
| Output Name | <location>_land_n_urban_{date}.gif | ||
| Output Description | Annual GIF image maps of urban and land use change for the final monte carlo iteration | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | standard output | ||
| Output Name | <location>_urban_{date}.gif | ||
| Output Description | In predict mode: Annual GIF image maps of color classified urban probabilities across all monte carlo iterations. The initializing urban layer is placed upon the urban probabilities and is classified with the SEED_COLOR. The hillshade image is used in the background. In test mode: Annual GIF image maps of urban change. Urban extent is color classified with the SEED_COLOR. The hillshade image is used in the background. | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | standard output | ||
| Output Name | z_growth_types_{run}_{monte carlo}_{date}.gif | ||
| Output Description | GIF image maps of urban change color classified by growth type. Images are produced for run, monte carlo, and date range specified by the GROWTH_TYPE_PRINT_WINDOW flag in the scenario file. | ||
| Output Type | visualization | ||
| Output Symbolic Representation | not numeric | ||
| Output Computational Representation | a .gif image | ||
| Output Visualization | static | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Output Name | avg.log and std_dev.log | ||
| Output Description | Measurements of simulated data, such as number of urban edges, clusters and urban pixels, are saved in the avg.log file. If in test or calibrate mode, for every year that real data exists (a control year) SLEUTH writes out a grid of urban extent (and land cover). Values are calculated from these grids and at the end of a run (a run begins with a single set of coefficient values and is executed n MONTE CARLO ITERATIONS) these values for each year are then averaged over the number of monte carlo iterations, and the result is written to the corresponding run number in control_stats.log. The standard deviations of the averaged values are written to the std_dev.log file. If in test mode, this process is performed for every year, not just the control years. | ||
| Output Type | dataset | ||
| Output Symbolic Representation | numeric | ||
| Output Computational Representation | array of numeric values | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Output Name | control_stats.log | ||
| Output Description | Control_stats.log is generated in test or calibrate mode. It contains the r2 values of the simulated data (found in the avg.log file) compared to input urban (and land cover) data. The values for the input urban statistics can be written to the LOG# file by setting the LOG_BASE_STATISTICS flag in the scenario file to "YES". This is the primary file used to narrow coefficient ranges during calibration. | ||
| Output Type | dataset | ||
| Output Symbolic Representation | numeric | ||
| Output Computational Representation | array of numeric values | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | standard output | ||
| Output Name | coeff.log | ||
| Output Description | Due to SLEUTH's self-modification qualities, these values may be modified slightly after each growth cycle. The coeff.log file stores coefficient values for every run, monte carlo iteration and year. This data is can also be written to the avg.log file. This file is used in the final step of calibration to derive forecasting coefficients. | ||
| Output Type | dataset | ||
| Output Symbolic Representation | numeric | ||
| Output Computational Representation | array of numeric values | ||
| Output Modeling Construct Description | Compound | ||
| Output Construct Name | same as output name | ||
| Output Construct Description | same as output description | ||
| Output Construct Dataset | same as output name | ||
| Output Construct Type | see output representation | ||
| Output Construct Units | coded values dependent on specified output | ||
| Output Construct Repeatability | 1 | ||
| Output Construct Comments | the specified dataset only contains one construct | ||
| Output Optionally | optional output | ||
| Data Post-Processing Requirements | No post processing is required. The images can be introduced back into a GIS environment and used as data layers for further analysis in their spatial context. For ArcInfo (for example) -Convert images into Arc acceptable format (e.g.: TIFF) -Convert images into grids with Arc: IMAGEGRID -Georeference grids with Grid: CONTROLPOINTS | ||
| Output Documentation | http://www.ncgia.ucsb.edu/projects/gig/v2/About/abData.htm | ||
| Output Comment | The model provides versatile output data that can provide useful information for a variety of applications. This includes both numeric and graphic outputs. | ||
| Calibration Efforts and Validation | |||
| Confirmation Dataset | The downloadable model software is supplied with a test scenario titled: scenario.demo200_test file. | ||
| Calibration Efforts | The model is calibrated on the input data sets. The processes are found in the additional information. | ||
| Model Experiments and/or Case Studies | Compound | ||
| Model Experiment Description | Documentation of case studies are available through the model experiment URL address. | ||
| Model Experiment URL Address | http://www.ncgia.ucsb.edu/projects/gig/v2/Pubs/pbDynamics.htm | ||
| Expert or Peer Review | Leonard Gaydos, Chief (tested model), Research, Technology and Applications, USGS Western Mapping Center, 345 Middlefield Rd, MS 531, Phone: (650)329-4330, Fax: (650)329-4710, E-Mail: lgaydos@usgs.gov | ||
| Current Use or Application | As of July, 2001, national (48 contiguous states) and local (Santa Barbara County) data sets are being calibrated by the model. There have been two applications in Portugal. The model scale is being increased towards national and global scale. | ||
| Known Error | All known bugs are discussed and resolved at the "Discussion" web site and associated discussion board, both found at the following URL address: http://www.ncgia.ucsb.edu/projects/gig/v2/Discuss/discussion.htm | ||
| Metadata Source | |||
| Metadata Creation Date | 24-May-01 | ||
| Metadata Responsible Party | Compound | ||
| Metadata Responsible Party Individual Name | Scott J. Crosier | ||
| Organization Affiliated with Metadata Responsible Party | University of California, Santa Barbara | ||
| Position Name of Metadata Responsible Party | Graduate Student, Geography Dept. | ||
| Role of Responsible Party | Creator | ||
| Metadata Responsible Party Contact Information | Compound | ||
| Delivery Point | University of California, Santa Barbara | ||
| 3510 Phelps Hall | |||
| City | Santa Barbara | ||
| Administrative Area | CA | ||
| Postal Code | 93106-4060 | ||
| Country | Unites States of America | ||
| Electronic Mail Address | scott@geog.ucsb.edu | ||
| Telephone Number | (805) 893-2714 | ||
| Facsimile Number | (805) 893-8617 | ||
| Metadata Source of Information | Clarke, K., Project Gigalopolis, http://www.ncgia.ucsb.edu/projects/gig/project_gig.htm | ||
| Metadata Standard Name and Version | Alexandria Digital Earth Prototype, Metadata for Models Working Group, Content Standard for Computational Models, Version 1.0, May 21, 2001 Draft |