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Getting Started with GIS has been the most popular Esri web course for several years. It's free and a great learning tool for those brand-new to GIS. You can use ArcGIS for Desktop trial software to complete the course exercises if you don't have access to a paid license.
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07-16-2014
03:31 PM
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This is the first installment in a three-part series on creating geoprocessing models in ArcGIS. In this post, learn the steps to build a simple model. ModelBuilder has been called a visual programming language or a tool to make "visual scripts." I like to think of ModelBuilder as a tool to map a workflow, and a model as a workflow map. Like a map: A model can be navigated (it has direction built in). A model uses shape, color, text, and symbols to represent and communicate about its features. A model reveals data relationships that can spark ideas and collaboration. Invaluable for conducting sophisticated spatial analyses, models are everyday workhorses too. If built with reuse in mind, they can be your go-to shortcuts to get a lot of work done. If you've never created a model in ArcGIS, here's what you need to know to get started. Take the five-step approach: Plan the workflow Create the model shell Add tools and specify parameters Validate the model Run the model 1. Plan the Workflow Obvious, but...before creating a model, know what you want it to do. List the data input, identify the required geoprocessing tools, and describe the desired output. If the workflow is simple, just think it through in your head. For more complicated workflows, you may want to sketch everything out on paper or a whiteboard. If you're not sure which tool to use or what a tool's required inputs are, check the geoprocessing tool reference. 2. Create the Model Shell In ArcGIS, a model has to be stored inside a toolbox. Creating a toolbox is simple. Right-click a folder in the ArcMap Catalog window and choose New > Toolbox. Right-click the new toolbox and choose New > Model. An empty model window opens. Now set some key model properties. Click the Model menu > Properties. In the General tab, check on the option to store relative path names. Using relative paths prevents headaches down the road if data gets moved around. Also, set these: Model name — the filename; no spaces allowed. Label — the plain-English name; displays in the ModelBuilder titlebar and in the Catalog window. Spaces are fine. Description — briefly explain what the model does. This will be a helpful reminder to you later and essential information if you share the model. 3. Add Tools and Specify Parameters With the basic setup done, now comes the fun part. You can't beat ModelBuilder for easy drag-and-drop building and tinkering. But hang on a sec, it's useful to understand some ModelBuilder vocabulary. A model consists of one or more processes. A process consists of three elements: input data, a tool, and the tool's output. Each output becomes input to the next process. Just like when you run a geoprocessing tool outside a model, if your input data has selected features or records, the tool processes only the selection. The output of each model process (except the last) is called intermediate data. When you run a model inside ModelBuilder, intermediate data is automatically saved. If you don't need it, you can delete it by clicking the Model menu > Delete Intermediate Data. When you add a tool to a model (by dragging/dropping from the Catalog window or using the Insert menu), its output element is also added and both elements are white. In model parlance, white means "not ready to run." You need to double-click the tool and set its parameters. Tip: In a tool dialog box, a green dot means the parameter is required. Once you set the tool parameters, the input element displays and the process is colored, Oz-like. As you add processes, the model window may fill up. Use the Full Extent button, followed by the Auto Layout button to see the big-picture view and zoom in and out as needed. Be sure to save the model periodically as you build it. To add the final model output as a layer to the map, right-click it and choose Add To Display. Otherwise, you'll have to manually add it to the map. 4. Validate the Model After you've added all the tools and set all their parameters, it's time to ensure the model will run properly. Validation is easy (click the Validate button or Model menu > Validate). During validation, if there's an error, processing will stop at the first process that requires a fix. Figure out what's wrong, make the fix, then validate again. Repeat if necessary, then save your work. 5. Run the Model You have two basic options to run a model: Within ModelBuilder (click the Run button or Model menu > Run) Outside of ModelBuilder as a tool or service Running a model as a tool or service has distinct advantages for collaboration and sharing. We'll cover model tools in the next post in this series. It's fun to run a model inside ModelBuilder. As the model progresses, each process turns red and then gets a drop shadow. The drop shadow indicates the process has completed correctly. If a process turns white, that means something needs to be fixed and the model stops running. If you've validated, this shouldn't happen. Maybe Run It Again A model's final output may raise a question. For example, suppose a model process created a 20-meter buffer around a feature. After examining the model output, you wonder what would result if you used a 50-meter buffer instead. To find out, simply open the buffer tool, enter the new distance value, and run the model again starting at the buffer process (right-click the buffer tool and choose Run). Because you're not altering preceding processes, you don't need to rerun the entire model. This is the beauty of a model. It's a perfect medium to explore and test what-if scenarios. Note: If you delete intermediate data before changing a parameter, you'll need to rerun the model from the beginning. Like scripts, models are encapsulated workflows. Once built, they can be reused as a fast alternative to manually performing a set of individual processes. You can build a model to automate any geoprocessing task or series of tasks, from the complex to the straightforward. Now that you've learned the steps to create a simple model, you may be ready to take it to the next level. In upcoming posts, we'll dive into more advanced modeling techniques. Related posts: ModelBuilder 220: Add Flexibility ModelBuilder 360: Amp Up the Automation Picture This: A Model for GIS Automation
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05-29-2014
05:32 AM
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Making a story map is an excellent opportunity to be creative, challenge your inner cartographer, and demonstrate GIS skills (and add pizzazz to your LinkedIn profile while you're at it). If you haven't yet made a story map, this four-step process may help you get started. Number 2 in the process is to plan and execute your data strategy. This step is critical but can get glossed over in the creative excitement to make a cool map. It's time to give it some time in the spotlight. A lot of story maps are focused narratives about geographic places, features, and current or historic events. When considering data to support a story map project, pay particular attention to three items. Locational Accuracy Currentness Understandableness Locational Accuracy The story map topic determines how locationally accurate your data needs to be. If you're making a map tour or shortlist, odds are you're showcasing point features. Depending on the real-world features represented by the points, map viewers may have accuracy expectations that you'll want to meet. Keep in mind that the prettiest, most topically engaging map is a dud if the features shown are far from their real-world locations. Suppose the topic is a local garden tour and the source data is a list of the participating homes' street addresses. The map is large-scale and uses a basemap that includes streets, parcels, and building footprints. In this case, map viewers will reasonably expect the house points to be on the correct city block and on the correct side of the street. If the points are not displayed at that level of accuracy, it detracts from the story map. If you don't know which side of the street point features fall on, let the ArcGIS Online map viewer's geocoder do the work for you. Save addresses, GPX coordinates, or lat-long coordinates in a text or CSV file, then upload the file to the map viewer. If you're making a map tour in which images and text are the meat of your story, you probably don't need submeter accuracy. It's perfectly fine to represent an entire street as a single point feature. As long as the points are reasonably close to the real-world locations, the story works. Currentness Unless you're presenting a historical topic or a temporal analysis of a current issue, seek out current data. You can find lots of up-to-date, authoritative maps and data on ArcGIS Online. If you use obsolete data to present a current topic, you run a high risk of creating a misleading or totally inaccurate story map. For example, using 1990 U.S. census data as the basis for a story map about current U.S. demographics is a do-not because more current census data is readily available. In this case, the 1990 data is obsolete. On the other hand, if the topic is how U.S. demographics have changed over the last 20 years, using 1990 census data in conjunction with 2000 and 2010 census data is the sound approach (and the Swipe or Map Series story map apps would work well). In this case, the data is old but not obsolete. Understandableness This possibly invented term relates to the usability index of your data, meaning can users interpret it at a glance or do they need to metaphorically lean in and squint? This item creeps into step 3 territory (create the web map), but an important part of planning your data strategy is thinking about the final presentation. Often, preprocessing data speeds up assembly of the end product. A story map is a focused narrative, so delete any fields or features that aren't relevant to that narrative. Conversely, if your data doesn't include all the detail you want to present, add one or more fields with the desired information (e.g., text descriptions, website URLs, image URLs, or category codes to base feature symbology on). You may need to split attributes stored in one field into separate fields to enhance usability of feature pop-ups. After you've finished preparing your data for story mapping, you're ready to add it to a web map, which you'll then share to become the foundation of a story map app. As mentioned previously, using the ArcGIS Online map viewer is an easy way to create a web map. You can upload a service, zipped shapefile, TXT file, GPX file, or CSV file. Note: When using an ArcGIS Online public account to create a story map, you can upload a maximum of 250 features at a time. If your dataset includes more than 250 features, reduce the number of features or split the dataset into multiple files and upload them separately (first plan out how to group the features into a logical set of map layers). If the data you want to use for a story map is stored in a geodatabase feature class and you aren't able to (or don't want to) create a service, it's easy to export the feature class to a shapefile. In the ArcMap Catalog window, right-click the feature class and click Export > To Shapefile. In the Feature Class to Feature Class dialog box, you can build a query to export only certain features and you can remove fields that you don't need. Shapefile text fields have a 254-character limit. If the source feature class has a text field that stores more than 254 characters, the text on the web map will be truncated. Always examine your source data carefully and make any necessary adjustments before exporting. Symbology plays a big role in data understandableness, particularly when it comes to quantitative (numeric) data. Exercise caution when mapping quantitative data—it's easy to unintentionally use symbology that turns perfectly accurate numbers into an inaccurate view of reality. For example, pie chart symbols are often used incorrectly to symbolize data that does not represent part of a whole. When presenting quantitative data, a good practice is to cite the data source. At a minimum, document who collected the data and when. You could add this information to the story map introduction panel, legend, feature pop-ups, or another appropriate text element. One final tip that has nothing to do with data: Be sure to add your byline and perhaps a custom logo to the story map. After all your hard work, you deserve the recognition and map viewers will appreciate knowing who created the story map. True beauty comes from the inside, so goes the saying. When it comes to maps, true beauty comes from accurately located, current data, presented understandably with valid symbology. Planning and executing your data strategy may take a little time and effort, but the reward is an authoritative map that will engage and educate. In other words, a story map that's beautiful both on the outside and on the inside. Related post: Four-Step Process to Make a Simple Story Map
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04-25-2014
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