THE CONSERVATION LANDSCAPE CONTEXT TOOLBOX: A Custom ESRI ArcToolbox for the Stewardship of Conservation Lands in Rhode Island

Transcription

1 THE CONSERVATION LANDSCAPE CONTEXT TOOLBOX: A Custom ESRI ArcToolbox for the Stewardship of Conservation Lands in Rhode Island Ann Borowik M.E.S.M. Research Project University of Rhode Island May 2008

2 Conservation Landscape Context Toolbox 2 OVERVIEW OF THE TOOLBOX In the state of Rhode Island there are over 7000 individual parcels of land that have been conserved by some means for the protection of natural areas, covering nearly 22% of the state. These lands have 291 different owners, including Rhode Island Department of Environmental Management, The Audubon Society, The Nature Conservancy, The National Park Service, U.S. Fish and Wildlife Service, town governments, and local land trusts to name just a few. The properties have been acquired to protect various species and ecosystems within the state, and considerable money has been spent to acquire them. However, many of the organizations and institutions that own the lands, or their easements, dedicate the majority of their funds to acquisition, leaving little to monitor and steward properties. Even if funds exist for these activities, the stakeholders often have inadequate staff, knowledge, or technology for the necessary stewardship activities. Furthermore, in Rhode Island there is no established universal protocol to guide the stakeholders on where to concentrate their efforts. Most stakeholders within the state recognize that stewardship is necessary for the viability of the conservation lands, but with no resources, had few options. In 2007, The Conservation Stewardship Collaborative (CSC) was established, along with the Conservation Stewardship Endowment Fund, in order to help protect and steward the conservation areas of Rhode Island by providing funding, expertise, and technology. The CSC also provides an opportunity for the stakeholders within the conservation community to share resources and insight. The Conservation Landscape Context Toolbox is a geospatial analysis tool that was developed in order to support the needs of the CSC and the individual conservation landowners. The CSC states the viability of any single parcel of land to support healthy populations of native plants and animals is a function of the condition of the parcel (sitescale) and the condition of the land around it (landscape-scale) (Coit et al., 2006). There are many threats to the integrity that can affect the condition of these lands at both the site and landscape scale, including invasive species, degrading human activities, fragmentation of habitat, and loss of water quality and quantity. This toolbox contains three example indices that measure potential threats at the landscape scale; the

3 Conservation Landscape Context Toolbox 3 landscape is defined as the area surrounding the individual conservation parcels extending out to a user-determined distance. The Land Use Index The Land Use Index calculates the proportion (in percent of total area) of each Land Use class within the landscape surrounding each of the conservation lands. For test analyses, land uses were reclassified into two classes: natural and unnatural uses. Measuring the proportional amount of land uses in the landscape is indicative of several potential threats to the conservation land, including development pressure, pollution, and other harmful human activities. Also, the existing of complementary habitat types or undisturbed areas adjacent to or near a conservation parcel can be beneficial to maintaining the integrity of the land. The Neighboring Conservation Lands Index The Neighboring Conservation Lands Index calculates the percentage of the landscape surrounding each of the conservation lands that is comprised of other conservation lands. The absence or existence of neighboring habitats that have also been protected for conservation is a measure of the fragmentation or connectivity of habitat patches, which is essential for the viability of natural areas. Protected areas cannot be sustained without a connected network of suitable habitats to allow for ecological flows throughout the greater landscape. The Road Density Index The Road Density Index calculates the amount of roads within the landscape surrounding each of the conservation lands, in the unit of road length per unit area (km/km 2 ). Measuring the road density in the landscape surrounding a conservation parcel is indicative of habitat fragmentation, access of invasive species, mortality for certain species of animals such as amphibians, and pollution.

4 Conservation Landscape Context Toolbox 4 HOW THE INDICES WERE CREATED The Basic Model The Conservation Landscape Context Toolbox was created in ESRI s ArcToolbox using Modelbuilder to develop the individual index components. Within the toolbox there are three toolsets, each containing the two models that comprise the corresponding index, along with any supporting models. Each index was created using the same general concepts and sequence of geoprocessing tools, but with different variables and tools as needed to customize the specific model. Each Index consists of two models: the parent index model with an imbedded iteration model. The index model gathers the input parameters, performs any additional data preparation, and feeds the data into the iteration model, which performs the feature by feature analysis. Each index requires a set of input parameters, including the conservation land input data, the buffer distance from the conservation parcel used to define the landscape extent, and the file directory where the output data will be stored. Each index begins with creating a feature class that will be the output of the index (see A of the figure below). This feature class must be created using an existing feature class as a template to preset the fields in the attribute table. This template feature class is necessary because the second part of the index, the iteration model, utilizes the append function which requires the datasets that are being combined to have the same schema. The newly created feature class is then fed into the iteration model along with the other data inputs, including the Row Count value which tells the iteration model how many times to iterate (see B of the figure above). The iteration model performs a string of processes to calculate the index value for each conservation land, but does so by

5 Conservation Landscape Context Toolbox 5 analyzing one record of the conservation land input shapefile at a time. The model is iterated for each record in this feature class, and with each iteration performs the following processes: 1. selects one record from the conservation land input feature class, 2. buffers the selected feature using the designated landscape extent distance, 3. creates and calculates a static area field based on the existing area field that is automatically created for geodatabase feature classes 4. combines the input datasets either by intersect or clip and spatial join, 5. dissolves data for unique cons_id, and class type if applicable, 6. calculates the proportion of total area or density, 7. appends the results to the output feature class. The output of this model and the index as a whole is a single feature class or table with the calculated index reported for each record in the conservation land input. It is necessary to have this second portion of the index in a separate model because this type of Modelbuilder iteration is an Iteration using Series, which executes the entire model for each model iteration. Therefore, a separate model had to be created for just the processes that needed to be iterated, and a separate model. Model Iterations A model that iterates, or loops, can be created in Modelbuilder in several ways. The iteration models within the Conservation Landscape Context Toolbox are created with the series variable method. To create an iteration model with the series method, the following steps must be taken: Declare a variable as a series variable, meaning it contains more than one value. In the models in the Conservation Landscape Context Toolbox, the Conservation Land Input Feature is the series variable and each of the record is a value. To create a series variable, rightclick a variable and click Properties. In the Properties window, click A series of values.

6 Conservation Landscape Context Toolbox 6 Next, connect a Get Count tool to the series variable. This tool is located in the Table toolset of the Data Management Toolbox. This tool produces a Row Count variable that tells the model how many rows, or records, are in the series variable Lastly, define the model as an iterating model. To do this, select Model Properties from the Model menu in Modelbuilder and click the Iteration tab. Ensure that the Run the model the following number of times: radio button is selected and specify Row Count as the variable from which to get the iteration count. Please refer to ArcGIS Desktop Help for any further assistance with these and other topics regarding model concepts and terms. Flexibility The tools in this toolset were created to allow levels of flexibility to the user. Each input feature class has been defined as a variable so that the user may choose the exact dataset to be used. Also, the landscape extent, or buffer distance, is also defined by the user, allowing for a customized analysis of the landscape. With these options, the user can easily conduct an analysis that is meaningful to his study or research. For example, by changing the data inputs the user can perform a change analysis between two land use datasets from different years. Also, the user can compare how the results from the same dataset change when the landscape extent is increased. Furthermore, the indices have been shared in their original geoprocessing model format to facilitate sharing, collaboration, and further development between the original developer and users. See the Customization of the Models section.

7 Conservation Landscape Context Toolbox 7 Data Used These models were created using the following datasets available on the RIGIS ( website. These data are included in the file geodatabase accompanying the Conservation Landscape Context Toolbox: Rhode Island Local & NGO Conservation and Park Lands Rhode Island State Conservation and Park Lands Rhode Island Land Use 2003/2004 Rhode Island RIDOT 1:5000 Roads Rhode Island State Boundary INSTALLATION INSTRUCTIONS The files contained in the Conservation Land Context compressed file (.zip) include: 1. the Conservation Land Context Tools toolbox (.tbx) 2. the User s Guide (.pdf) 3. and a file geodatabase including sample and template data (data.gdb) The Toolbox The conservation landscape context models are in the form of an ESRI Toolbox for use in ArcMap or ArcCatalog. These instructions are similar to the addition of any toolbox to the ESRI ArcToolbox. 1. Extract the.tbx file and save it to the following directory: C:\Program Files\ArcGIS\ArcToolbox\Toolboxes. 2. Open ArcMap or ArcCatalog and add ArcToolbox to the window if it does not automatically appear. (ArcToolbox can be added by selecting ArcToolbox from the Window menu.) 3. In the Favorites tab of ArcToolbox, right-click on ArcToolbox and select Add Toolbox from the menu. 4. Navigate to the directory where the toolbox is saved. Highlight the toolbox and click Open. 5. The toolbox will now appear in your list of favorites under the name Conservation Landscape Context Tools. The User s Guide The user s guide is in portable document format (pdf) and can be viewed using Adobe Reader or Adobe Acrobat. The Geodatabase Accompanying the toolbox is a file geodatabase including the template feature classes needed to successfully run the indices and models, along with all the data used during the creation of this toolbox. These files should only be viewed and otherwise

8 Conservation Landscape Context Toolbox 8 managed using ESRI ArcCatalog and never in Windows Explorer in order to avoid corruption. Also, the sample data included here can be used within the models, but it is recommended that they be converted to shapefile format first due to Modelbuilder s occasional rejection of geodatabase feature classes as inputs. USING THE TOOLBOX This toolbox was created for users that have a working knowledge of ESRI ArcGIS, ArcToolbox geoprocessing tools, and Modelbuilder. Before you run the individual models Within the toolbox there are several tools, or models, that are organized into toolsets. Each toolset includes the corresponding index and iteration models along with any supporting models. There are several options to consider before you use the toolbox indices. Before you run any of the models, you must consider: 1. Data Format 2. How to Run the Models 3. Intermediate Data 4. Workspaces 5. Schema Templates 6. Conversion to Script Format 1. Data Format It is recommended that the geospatial data inputs be shapefiles as Modelbuilder tools sometimes reject geodatabase feature classes as inputs. Also, several of the inputs require some attribute preparation. For example, the conservation land input must have a unique identifier within an attribute text field named cons_id and the land use input must be previously reclassified into the desired generalized classes within an attribute text field named LU_type. It is also recommended that the land use input be generalized, or dissolved, by the LU_type class to reduce the total number of features and complexity; this step will help reduce the processing time. 2. How to Run the Models The user can run models in the toolbox in two ways, either within the Modelbuilder interface or by opening the tool s dialog in ArcToolbox. Running the tool from ArcToolbox is the simpler method, providing a user-friendly dialog box with the available variables

9 Conservation Landscape Context Toolbox 9 listed, and their values easily changed, as well as Help documentation and diagrams. To run the model is this way, simply double-click on the tool name in ArcToolbox, change the variables as desired in the dialog, and click OK. However, by running the model within the Modelbuilder interface, the user has much more control over how the model is run. The user can choose to run only specific processes, (s)he can visually observe the model running process by process, and also view the log file as the model is running. To run the model within Modelbuilder, right-click on the tool name in ArcToolbox and select Edit from the menu. This opens the Modelbuilder window and displays the inputs, processes, and outputs that make up the tool. Variables are noted by a P and their values can be changed by double-clicking on the variable to open a dialog box. To run the model, select Run or Run Entire Model from the Model menu on the toolbar. Please refer to ArcGIS Desktop Help for any further assistance with these and other topics regarding model concepts and terms. 3. Intermediate Data Intermediate data are the output data for each process in the model that are of no use after the model has run since they are only created to connect to another process that creates new output. The models are set to delete intermediate data at the completion of the index, but this setting can be easily changed. To retain all intermediate data upon completion of the index, open the iteration model in the Modelbuilder interface by rightclicking on the model in ArcToolbox and selecting Edit. The green ovals represent the output data created at each process step, some of which will be intermediate data. The data need to be individually preserved by right-clicking on the variable and clicking Intermediate to remove the checkmark. The intermediate option if unavailable if the data variable is a model parameter or represents previous intermediate data that is not a new derived output. If the intermediate data are preserved, they will be placed in the scratch workspace so that the user can access them if needed and easily delete the data when desired. 4. Workspaces A workspace is a directory where data can be stored, such as a folder or geodatabase. The user will have to define two workspaces when running the indices in either of the two discussed methods: the Output Workspace and the Scratch Workspaces. The Output Workspace is the folder or geodatabase the houses the Output Features and Tables of the indices. The Scratch Workspace is where the models will place all intermediate data. When running the tool through the ArcToolbox dialog, the current and scratch workspaces will appear as parameters that can be set by navigating to a desired directory. When running the tool through the Modelbuilder interface, the current and scratch workspaces will be model parameters in the diagram that can be set by doubleclicking on them and navigating to the desired directory. 5. Schema Templates Each index model creates a new empty feature class to which the index value for each conservation feature will be appended. This feature class must be created using an

10 Conservation Landscape Context Toolbox 10 existing feature class as a template to preset the fields in the attribute table. This template feature class is necessary because the second part of the index, the iteration model, utilizes the append function in the iteration model requires the datasets that are being combined to have the same schema. This template feature class is defined as the variable Output Schema Template that the user must specify. The user is advised to use the provided template data in the Data geodatabase that is supplied with the model. If the model is altered, specifically if the field names or characteristics of the output attribute table are altered, a new feature class may be required to serve as the template. This can usually be accomplished by running the altered model until an error pertaining to the template schema is received, then use the intermediate dataset created by the last successful process in the first model run as the template, renaming it to the same name as the original template. Please refer to the ESRI ArcGIS Help documentation for additional assistance with schema templates. 6. Conversion to Script Format Through the development of the Conservation Landscape Context Toolbox, the I have noted both the benefits and limitations of Modelbuilder. Modelbuilder is an extremely useful tool for the creation of automated geoprocessing flows at a previously unachievable level for the non-programmer. However, it also has some strong limitations and flaws. Most importantly, Modelbuilder models easily become corrupted or broken, particularly if they include many parameters that are used with many changing inputs. This is an unfortunate characteristic, especially in regards to this toolbox and its intended function. The user can take several steps to avoid corruption of models in the Conservation Landscape Context Toolbox: Leave the original models intact and makes copies for uses with different inputs. Convert the models to a script format, such as Python, and run the analysis using the script. (This should also reduce the processing time). Models can be converted to Python and run using the following steps: In the Model menu of Modelbuilder, choose Export > To Script > Python, Choose the file name and directory in which to save the script, Navigate to the selected directory in Windows Explorer,

11 Conservation Landscape Context Toolbox 11 Right-click on the script and select Edit with IDLE, In the script window (not the shell window) select Run Module from the Run Menu. The Land Use Toolset The Land Use Toolset is comprised of four tools: the Land Use Index, Land Use Iteration, Reclassification Example 1, and Reclassification Example 2. The Reclassification Example tools supply the user with two models for reclassifying Land Use data that are in an Anderson Classification Scheme into two different example sets of generalized classes: Anderson Level 1 classes and Natural/Unnatural classes. The Iteration model, as discussed earlier, is a component of the Land Use Index tool used to perform the looping functions on the conservation features. This tool is not intended to be used as a standalone tool and should only be altered as instructed or if the user wants to customize the portions of the Land Use Index that are located within this model. Further help documentation is not provided for these three tools. The Land Use Index calculates the proportion (in percent of total area) of each Land Use class within the landscape surrounding each of the conservation lands. To use this model, run it according to one of the methods described in Before you run the models and set the variables as needed. The variables associated with this tool and their descriptions are as follows: Conservation Lands Input: The shapefile containing polygons of the conservation areas to be analyzed. Each conservation site needs to have a unique identifier in an attribute text field named cons_id. Sites consisting of more than one polygon are acceptable as long as the polygons are aggregated as a multi-part feature with only one record in the attribute table. It is recommended that a shapefile be used for this input rather than a geodatabase feature class. Land Use Input: The land use dataset of choice. Must be reclassified into more general classes beforehand, if desired. It is recommended that a shapefile be used for this input rather than a geodatabase feature class. Landscape Extent: The distance from the boundary of the conservation polygon(s) used to define the radius of the landscape extent. Output Feature Class: Name of the feature class to be created.

12 Conservation Landscape Context Toolbox 12 Template Feature Class: The feature class that is used as a template for the attribute field names and types of the Output Feature Class. While the dialog claims it is optional, the model will not complete successfully without it. Output Feature Table: The location and name of the model tabular data output to be created. Output Workspace: The directory where the Output Feature Class will be placed. Scratch Workspace: The directory where the intermediate data will be placed. The model has two outputs, a polygon feature class and a table. The feature class is the product of the intersection between the buffer feature, or landscape, and the land use features. The attribute table of this feature class contains the proportion, in percent of total area, that each land use class contributes to the landscape. The features have been dissolved by land use class, so there is only one record per class for each conservation ID. For example, for conservation ID in the figure below, there is one record for each of the two different land use classes that appears within the landscape of conservation feature that includes the area of that class (LU_area field) and what percentage that area is of the total landscape area (LU_percent field). The sum of the area percent value for each land use class within the target conservation parcel s landscape may not add up 100 if the parcel is on or near the shoreline causing a portion of its landscape to be off land. The table output includes the same information as the feature class attribute table, but in a different format. The table includes a field for each land use class, so for each conservation land (with a unique cons_id) the proportion values of each land use class are listed as attributes under the corresponding class field, as you can see in the figure to the right. Either output table can be easily joined or related to the original conservation lands input using the cons_id field.

13 Conservation Landscape Context Toolbox 13 The Neighboring Lands Toolset The Neighboring Lands Toolset is comprised of two models: the Neighboring Lands Index and the Neighboring Lands Iteration. Similarly to the Land Use Toolset, the Iteration Tool within this toolset is the component of the Neighboring Lands Index that performs the looping function. This tool is not intended to be used as a standalone tool and should only be altered as instructed or if the user wants to customize the portions of the Neighboring Lands Index that are located within this model. The Neighboring Lands Index calculates the percentage of the landscape surrounding each of the conservation lands that is comprised of other conservation lands. To use this model, run it according to one of the methods described in Before you run the models and set the variables as needed. The variables associated with this tool and their descriptions are as follows: Conservation Lands Input: The shapefile containing polygons of the conservation areas to be analyzed. Each conservation site needs to have a unique identifier in an attribute text field named cons_id. Sites consisting of more than one polygon are acceptable as long as the polygons are aggregated as a multipart feature with only one record in the attribute table. It is recommended that a shapefile be used for this input rather than a geodatabase feature class. Land Boundary Input: A polygon shapefile of the land boundary of the analysis. It is recommended that a shapefile be used for this input rather than a geodatabase feature class. Landscape Extent: The distance from the boundary of the conservation polygon(s) used to define the radius of the landscape extent. Output Feature Class: Name of the feature class to be created. Template Feature Class: The feature class that is used as a template for the attribute field names and types of the Output Feature Class. While the dialog claims it is optional, the model will not complete successfully without it. Output Workspace: The directory where the Output Feature Class will be placed. Scratch Workspace: The directory where the intermediate data will be placed. The index model output is a polygon feature class that is the product of the intersection between the buffer feature, or landscape, and the conservation land features. The attribute table of this feature class contains the summed area of all the other conservation lands within the landscape extent of each individual conservation feature (nbr_area field),

14 Conservation Landscape Context Toolbox 14 as well as the percentage of the total landscape area that is comprised of these neighboring conservation lands (nbr_percent field). If there were no neighboring conservation lands in an individual parcel s landscape, there will be no record.

15 Conservation Landscape Context Toolbox 15 The Road Density Toolset The Road Density Toolset is comprised of two models: the Road Density Index and the Road Density Iteration. Similarly to the two previous toolsets, the Iteration Tool within this toolset is the component of the Road Density Index that performs the looping function. This tool is not intended to be used as a standalone tool and should only be altered as instructed or if the user wants to customize the portions of the Road Density Index that are located within this model. The Road Density Index calculates the amount of roads within the landscape surrounding each of the conservation, in the unit of road length per unit area (km/km 2 ). To use this model, run it according to one of the methods described in Before you run the models and set the variables as needed. The variables associated with this tool and their descriptions are as follows: Conservation Lands Input: The shapefile containing polygons of the conservation areas to be analyzed. Each conservation site needs to have a unique identifier in an attribute text field named cons_id. Sites consisting of more than one polygon are acceptable as long as the polygons are aggregated as a multi-part feature with only one record in the attribute table. It is recommended that a shapefile be used for this input rather than a geodatabase feature class. Roads Input: The line feature class containing roads. Landscape Extent: The distance from the boundary of the conservation polygon(s) used to define the radius of the landscape extent. Output Feature Class: Name of the feature class to be created. Template Feature Class: The feature class that is used as a template for the attribute field names and types of the Output Feature Class. While the dialog claims it is optional, the model will not complete successfully without it. Output Workspace: The directory where the Output Feature Class will be placed. Scratch Workspace: The directory where the intermediate data will be placed. The index model output is a line feature class that is the product of the road features that are clipped by the buffer feature. The attribute table of this feature class contains

16 Conservation Landscape Context Toolbox 16 the road density for each conservation parcel s landscape, reported in km/km 2 (field rd_dens_km).

17 Conservation Landscape Context Toolbox 17 CUSTOMIZATION OF THE MODELS The indices in the Conservation Landscape Context Toolbox measure meaningful characteristics of the landscape, but they were also designed to serve as a template for measuring any characteristic needed by the user. These individual models have been created in a way that allows for flexibility and easy customization. In basic terms, the models calculate characteristics of three categories of feature types as they exist with in the landscape, or buffered area: 1. Density of line features (Road Density Index) 2. Density of polygon features of a single class (Neighboring Lands Index) 3. Density of polygon features consisting of multiple classes (Land Use Index) The only category missing is the measurement of point features, which can easily be created using the general string of processes of existing models as a guide for creating a new custom model. A simple way to customize the models to meet the specifications and needs of the user is to use different input data into the preexisting models to measure a different phenomenon without altering the model processes at all. For example, a river feature class can easily be used as the data input for the Road Density Index to measure river density without changing the model processes. The models themselves can also be altered within Modelbuilder by changing the various processes, parameters, inputs, and values. Additionally, any of the models can be exported to a scripting language, such as Python, for further customization. When altering these models, note that the original models rely on the automatically created and recalculated area and length fields within geodatabase feature classes, and thus require that all intermediate data within the models be in this format. Sharing and development of these indices and models is desired and encouraged by the developer, especially within the conservation community. Hopefully these tools will not only be useful for the stewardship of Rhode Island s conservation lands, but also serve as templates for new, more sophisticated stewardship tools.

18 Conservation Landscape Context Toolbox 18 REFERENCES Coit, Janet, David Gregg, and Peter August Conservation Land Stewardship in Rhode Island: A Vision for the Future. Conservation Stewardship Collaborative Memorandum of Understanding. Rhode Island Conservation Stewardship Collaborative