Tag: Best Practices

The Power of ArcGIS Through Business Analyst Online

You might have noticed the new Select tool in the map tool palette. What in the world is this? How is it going to be useful to me? What else can I do after bringing in a web map from ArcGIS Online? Continue reading to find out more…

As discussed in a previous blog post, you can bring in the maps created in ArcGIS Online into Business Analyst Online and make the maps more meaningful.  With the help of this new Select tool, you can make it even more powerful.   Here’s how… Continue reading

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Best practices for using layer definition queries while creating features

ArcGIS 10 introduced the concept of editing with feature templates, which define a new feature’s symbology and default attribute values, among other properties. Anytime I want to add a feature, I use the Create Features window, which displays a list of available feature templates and tools for creating new features.

Sometimes, though, I do not see the template I want to use in the Create Features window. This could be because there are no templates for the layer, but it could also be that the template exists but is being filtered out of the Create Features window. The underlying philosophy for determining whether ArcMap shows a feature template is that new features created with the template must be visible after creation. Therefore, templates are hidden whenever new features would immediately disappear and not be displayed on the map.

While a layer being turned off is one of the more obvious reasons why feature templates are not shown on the Create Features window, layer definition queries can be subtle causes. A definition query displays only the subset of features that match an attribute query defined on the Layer Properties dialog box; the remaining features are not drawn on the map or shown in the attributes table.

This post provides an overview of and best practices for the use of definition queries while creating features.

Continue reading

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December 5th Esri Mid-Atlantic Water/Wastewater Special Interest Group Meeting

On December 5th, 2011 the Esri Mid-Atlantic Water/Wastewater Special Interest Group will be meeting in Hunt Valley, Maryland.  This meeting is free to attend and is taking place the day before the Esri Mid-Atlantic User Group Conference.  We hope you’ll join us at the Special Interest Group meeting and then stay and attend the MUG Conference.  Lunch at the meeting is provided and graciously sponsored Platinum Esri Business Partner Azetca Systems and their Cityworks products.

The Esri Mid-Atlantic Water/Wastewater Special Interest Group is for the water, wastewater and stormwater ArcGIS user community in Pennsylvania, New Jersey, Maryland, Delaware, Washington D.C., West Virginia, New York City, Long Island and surrounding areas.

Space is limited, so sign up for the meeting here: http://events.esri.com/info/index.cfm?fuseaction=seminarRegForm&shownumber=15294

The full agenda for the meeting is:
9:30 am – Registration
10:00 am – Greetings & ArcGIS for Water Utilities, Esri
10:30 am – Public Facing Applications for Water and Wastewater Utility Stakeholder Engagement, Washington Suburban Sanitary Commission (WSSC)
11:00 am – County and Utility Collaborative GIS , Allegany County, Maryland
11:30 am – ArcGIS Online for Water, Sewer and Stormwater utilities, Esri
12:00 pm – Complimentary Lunch Sponsored By Cityworks
12:15 pm – GIS Centric Asset Management, Cityworks
1:00 pm – Water Resource Center to promote GIS dissemination, Harford County Maryland Public Works
1:30 pm – Roundtable Discussion & Closing Remarks
2:00 pm – Meeting Adjourn

We hope to see you at this meeting!

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Benefits of the Local Government Information Model for Water Utilities

Why should a water, wastewater or stormwater utility adopt the Local Government Information Model?

Easier Deployment

One of the biggest benefits of a water utility adopting the Local Government Information Model is that it makes deploying the ArcGIS for Water Utilities maps and apps easier, faster and cheaper.  The further you deviate from the Local Government Information Model, and in particular it’s geodatabase schema, the harder it will be for you to implement the maps and apps that are part of ArcGIS for Water Utilities. It will also be hard and time consuming to upgrade your ArcGIS for Water Utilities implementation when we release updates.

Changes you make to the Local Government Information Model schema may necessitate extensive modifications of the maps documents, and changes to apps (web apps, mobile apps, ArcGIS Desktop, etc.) that are part of ArcGIS for Water Utilities.  So the closer you stay to the core Local Government Information Model, the easier your initial deployment will be and the easier it will be to migrate your ArcGIS implementation to new releases or to deploy updates to the maps and apps.

It’s also important to note that when we say “adopt” the Local Government Information Model we don’t mean that you necessarily have to use it as is (or more appropriately – as downloaded).  You probably will need to configure the Local Government Information to meet the needs of your organization.   But the key thing to keep in mind is you should only be making changes to accommodate the true organizational needs of your utility. For example, instead of changing the field names to the field names you’d like to use in your organization, modify field and map layer aliases.   Bottom line, don’t reinvent the wheel, just make changes that are required to meet specific business needs in your organization.

At the very least you need to change the projection to the appropriate coordinate system and set up the domains to reflect the assets in use at your utility.  Small utilities or utilities that are new to GIS may choose to take the Local Government Information Model as is, while larger utilities, mature GIS implementations, or GIS implementations that are integrated with other enterprise system will undoubtedly need to make more significant configurations or extensions to the schema to reflect their organizational needs.  

Water, Sewer and Stormwater Data Modeling Best Practices

The Local Government Information Model incorporates many best practices for water utility GIS.  One of the most important best practices is how to represent a water, sewer or stormwater system in GIS.  

For years Esri had downloadable data models for water, wastewater and stormwater utility networks.  Those data models were the first freely available water utility GIS data models.  They were stewarded by Esri, but built by the user community and became the industry standard.  Globally thousands of water utilities have built their GIS around Esri’s free data models.  

The Local Government Informational Model is the next iteration of Esri’s water, sewer and stormwater data models.  In essence we’ve modernized the data models to reflect how water utilities have been deploying GIS over the past few years and we’ve also modified the schema to fit the requirements of the ArcGIS for Water Utilities maps and apps.  As water utility GIS continues to evolve Esri will regularly maintain the Local Government Information Model to keep introducing new best practices into the user community and functionality into our apps.

Comprehensive Data Model

There is no doubt Esri’s water, wastewater and stormwater data models were an incredibly valuable starting point for water utilities to get their utility networks into GIS.  Since the original data models focused primarily on a data structure for the assets that comprise utility networks, we received feedback that many utilities wanted more guidance on how to model operational data (workorders, service requests, customer complaints, main breaks, capital improvement projects, etc.) and base data (roads edge of pavement, road centerlines, elevation data, parcels, etc.) in their GIS.  The Local Government Data Model solves this problem because it includes a complete schema for typical water utility base data and operational data.  

Over the years, an observation we’ve made is that water utilities struggle with how to model and manage schemas for datasets that aren’t their utility networks or operational data – simply put managing base data can be a challenge for water utilities. For example we’ve seen a lot of utilities struggle with managing roads, parcel, buildings, etc. in their enterprise GIS, especially when these datasets are coming from other organizations or departments.

This is a particular issue for water utilities that serve multiple units of local government such as authorities, county wide utilities, state wide utilities and private companies.  A good example of this is a water authority whose service territory includes three counties.   The water authority needs parcel data that is maintained by the counties.  County A, County B and County C all use different schemas for their parcels.  So the water utility had two choices – leave the parcels in 3 different data layers and use them as is – which makes analysis, map creation and integration with other systems at the utility that need parcel data (such as a customer information system) difficult.  Or invest time to extract, transfer and load (ETL) the parcels into a common schema so they can be used as a single seamless layer across the service area.  The Local Government Information Model can now serve as the common schema in this example.
Easier Data Sharing

We describe the Local Government Information as a harmonized information model – meaning designed to accommodate typical GIS needs across local government.  If organizations that commonly share data all adopt the Local Government Information Model, it will greatly reduce the time and resources spent establishing a common schema and migrating data to these schemas – thus allowing water utilities to focus on the maintenance and management of their authoritative data.

For example a private water utility may serve two municipalities.  If the water utility and both municipalities all adopt the Local Government Information Model then they can all very easily exchange data.   When the water utility needs road centerline and edge of pavement layers from the municipalities than the utility can just import the new data without having to manipulate the schema and will have seamless layers for their service areas.  The same logic applies to the water utility sharing data with the municipalities – when the water utility updates the location of their upcoming capital projects, the utility can share that data back with the municipalities and the municipalities can use it without any schema manipulation.

Best Cartographic Practices for Water Utility Maps

As we’ve discussed in a previous blog, the Local Government Information Model includes geodatabase schema, map documents and specification for services necessary to deploy the ArcGIS for Water Utilities and ArcGIS for Local Government maps and apps.  

The map documents highlight
best practices for displaying water, wastewater and stormwater data in the context that each map is designed to be used.  For example the map documents included with the Mobile Map Template have best practice cartography for displaying water utility GIS data in the field in both a day and night time use map.  The same goes for the map document included with the Infrastructure Editing Template – this is a best practice map document for editing water utility data with ArcGIS Desktop.

Looking to the Future

The specification for the services (map, feature, geoprocessing, etc) necessary for the ArcGIS Water Utilities maps and apps are also part of the Local Government Information Model.  So if other local government entities in the service area of water utility embrace the Local Government Information Model, ArcGIS for Local Government and start to publish services, then water utilities can consume those services for their maps and apps.  In this scenario the water utility may no longer have to import some data into their own geodatabase and can just consume the services right from the organization that is the steward of the data.

We hope you’ve found this exploration of some of the benefits water, wastewater and stormwater utilities will experience when adopting the Local Government Information Model helpful.  We encourage your feedback on the information in this blog, the Local Government Information Model or ArcGIS for Water Utilities.

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Creating Map Books using Data Driven Pages

A few weeks ago, thousands watched a live training seminar on the new Data Driven Pages in ArcGIS 10.  If you missed this excellent live seminar you can watch it on demand from Esri Training.

Using the ArcGIS 10 Data Driven Pages feature, you can quickly and easily create a professional-quality map book from a single map document. This seminar teaches the workflow for using Data Driven Pages. The presenter also covers how to create an index layer from a feature layer and add dynamic text and locator maps to your map pages.

Who Should Attend
GIS professionals and cartographers working in utilities, transportation, public safety, and government mapping agencies and others who need to produce map books.

Key Points
The presenter discusses

  • Data Driven Pages, map books, index feature extents, and geoprocessing tools.
  • The process for building map books.
  • Updating, printing, and exporting map books.


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Labeling Parcel Lines with COGO Dimensions

A parcel map requirements for line dimensions used to be hard to achieve using only labels. This is the reason many user reverted to the use of annotation. But maintaining annotation is labor intensive, designed for a specific scale and prone to user error. Labels, on the other hand, are database driven, can be easily compared with the line’s geometry as part of the QA process and require no maintenance once configured. We spent a few hours configuring the labels for parcel lines and you can see the results below, which are just as good, if not better. This result could have never been achieved without the parcel fabric redundancy of lines and the concept of line-point.
This post can help you configure labels for parcel fabric lines using the standard label engine or the Maplex extension. Even if you are forced to use annotation, you can benefit from this configuration, as labels can easily be converted to annotation. Continue reading

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Editing tips and tricks: Part 1

At the 2011 Esri International User Conference, I presented a technical workshop about tips and tricks for editing in ArcGIS for Desktop 10 with Matthew Baker. In the session, we integrated time-saving hints into a demonstration of using the editing tools to transform a vacant tract of land into a design for a new city park. In this post, we incorporate some of the top pointers as we continue planning the park by creating and editing foot paths, vegetation, and other land uses.
1. Set layer properties before starting editing.
Prior to my first edit session, I review each layer’s Layer Properties dialog box because these settings determine how layers are displayed and provide properties for feature templates, which are created when I start editing. If I set up my layers ahead of time, it is easier to work with them in the editing environment and means less effort later when authoring feature templates and editing attributes. In particular, I use the Fields tab to turn off fields I don’t need to edit, set aliases, and reorder fields to promote the ones I want to edit first. Next, I look at the Symbology tab to make sure symbols are appropriate and any unique value category labels are descriptive, since feature templates are based on layer symbology. Finally, I go to the Display tab and make sure the display expression is correct, since it is used to represent a feature in the Attributes window, selection chip, table of contents, and other places in ArcGIS. 

One thing to note: if you are reusing this map for publishing with ArcGIS Server, leave the OBJECTID and SHAPE fields turned on because they are used to manage the features in the service.
2. Set a feature template’s default construction tool.
Before I start creating features, I open the Template Properties dialog box and check the default construction tool. Since I need to create curving foot paths through the park, I set the default construction tool to Freehand to make it automatically activate when I choose that feature template. The park needs about a dozen paths and trails created in it, so setting Freehand as the default tool can be a significant time-saver because it avoids the extra click to change from the Polygon tool. By the way, another tip when using the Freehand tool is to press the spacebar to snap to an existing feature.

3. Set a feature template’s default attribute values.
While in the Template Properties dialog box, I also set the default attribute values that will be assigned to the new features created with the template. Since my geodatabase has coded value domains, I can choose the attribute value from a drop-down list. Domains eliminate the need for repeatedly typing the same values (and possibly making a typographic error) and ensure the attribute values are always valid. For the foot path’s feature template, I set the value for the Material field to Wood Chips so features are automatically assigned a material of wood chips.
4. Use the TAB key to move the Feature Construction toolbar.
The Feature Construction mini toolbar is handy because it allows me to change segment types in a sketch, create parallel or perpendicular segments, undo edits, and finish the sketch without moving the mouse to the main Editor toolbar. Since the Feature Construction toolbar follows where I click the map, it can sometimes end up covering where I want to add the next vertex. I can press the TAB key to flip the location of the toolbar so it is out of my way.
5. Type a unit abbreviation to enter values not in map units.
My park data has map units of feet, but I need to enter a length for an athletic field in meters. By including the unit abbreviation of m after the length value, ArcMap knows the value is actually in meters and converts the distance for me behind the scenes. Unit abbreviations only work when the data frame uses a projected coordinate system rather than a geographic coordinate system.
Check back soon for tips 6-10 and for the full slides from this User Conference session click here.
Content provided by Rhonda from the Editing Team
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Sketching the design of a new park

Park analysis and design:  Sketching the design of a new park (part 4)

In my previous blog post, I used a voting application allowing citizens to vote on their favorite location for a park based on choices derived from a suitability analysis. Using ArcGIS Server, their choices went into a database and allowed the parks to be ranked based on their popularity. We have a winner, so now our task is to design the new park. Continue reading

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Voting on a new park location

Park analysis and design:  Voting on a new park location (part 3)

In my previous blog post, I determined suitable locations for a new park by analyzing a series of datasets provided by the City of Redlands. The final output showed a number of parcels that matched the standards established in the model. The next task is to seek feedback from the public. To do this, I’ll take advantage of a web application I developed using ArcGIS Server.

Preparing the data
The park suitability model resulted in an output of a feature class containing many multipart features. A multipart feature, as the name suggests, is a feature with multiple parts. Think of Hawaii as one feature (state) with multiple parts (islands). To break the suitable areas for parks into separate features, I’ll use a tool called Multipart To Singlepart.

With every parcel being its own feature, I can calculate the area for each potential site by creating a field and using Calculate Geometry in the attribute table. Once I have the area in acres, I need to convert all the polygons to points using the Feature to Point tool so I can represent each park as a point location in the web application.

The final dataset contains fields for the park’s area and an identification number, which I derived by copying the OBJECTID to a field called ParkID. This number is used to link the park feature to the voting results table, which also has a field for the ID named ParkIDVoted (so I can distinguish it in the Flex code).

Building the web service and application
I’m developing my application using the ArcGIS API for Flex, so I first check if there are any existing samples that I can use as a starting point to help me collect votes. I find the Editing a related table sample, which demonstrates a similar scenario that I can modify for the needs of my own project. This sample takes a set of incidents (stored as points) and allows the user to flag an incident as important. In the code, there’s a map service that holds the points, as well as a table to hold the results. In the geodatabase, these are linked using a relationship class. These datasets need to be in an ArcSDE geodatabase with feature access enabled to allow web editing. Accordingly, I can set up my data this way and publish it with ArcGIS Server, which makes the parks and the table become layers in a map service.

I need to change a few things in the sample to customize it for my own application: the URL of the parks layer and the URL of the table holding the votes. Some field names are different, but other than that, the logic of casting the vote is fairly straightforward.

In terms of the interface, the sample shows how to use the pop-up window (infoWindow) when a park is clicked. I used the same thumbs-up icon and added a bit more information to the information window. Additionally, I published the park access map and the final suitable parcels layers, which can be turned off and on in the application using simple Flex components.

Submitting a vote
When users find a park they are interested in, they click the icon on the map. This sends a query to the server using the x,y location of the map click, which also triggers a relationship query that gets the number of votes of the record in the related table. The infoWindow then displays the ID of the park that was clicked, the park size, and the total count of current records in the related table, which are votes in favor of this location.

To vote for this park, the user clicks the thumbs-up icon, which sends a message to the server (applyEdits) that puts the ID of the park, plus a value for “like” into the related table through the relationship class. The count is increased by one and the total vote count can be seen immediately.

Counting the results
On the server, the related table collects the votes. Each record in the table is a vote, which includes the Park ID the user clicked, an attribute for the vote (“true”), and the date of the vote.

When the voting period is over, I can run a summary on the final table using the Summary Statistics tool. This counts the number of records with the same ID and creates a table, which I can then build a report on using the new reporting tools in ArcGIS 10.

Now that I have a winner, the next task is to design the park using the sketching tools in ArcGIS 10. I will cover this in my next blog post.

Accessing the Data
The data, Flex source code, report template, and a few other parts of the workflow can be found here

The rest of the data and tools for this blog series can be found in the Park Analysis and Design group (make sure to filter by Show: All Content at the top of the page)

Content for the post from Matthew Baker


Part 1 – Park analysis and design – Measuring access to parks

Part 2 – Park analysis and design: Locating a park through suitability analysis

Part 3 – Park analysis and design:  Voting on a new park location

Part 4 – Park analysis and design:  Sketching the design of a new park

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Locating a park through suitability analysis

Park analysis and design: Locating a park through suitability analysis (part 2)

In my previous blog post, I analyzed park accessibility in the City of Redlands and discovered several areas of the city that were farther than one mile from an existing park along the walkable street network. Now, I want to determine where to best locate a new park within the areas I identified as being underserved by current parks.

To answer this question, I’ll conduct a suitability analysis to find parcels that are most appropriate for a new park.

There are two main types of suitability analysis: binary and weighted. Binary suitability analysis involves a binary final answer —1 or 0, or in our case, suitable and unsuitable. A weighted suitability analysis allows for a range of final answers, from 1 to 10, for example, and allows certain layers to have more influence (weight) on the result of the model. For this example, I’m going to create a binary suitability analysis model.

As with our park accessibility analysis, I’ll start with several datasets from the City of Redlands, including parks, schools, roads, trails (off-road and on), existing and proposed bicycle lanes, and vacant parcels. Before I construct a model, I should know the distances the new park should be from certain features. In most cases, I’m looking to be close to certain features, but in other cases, I want to make sure I’m far enough away, such as with highways and existing parks. 

Remember that any of these values can be changed to suit any criteria. ModelBuilder allows a workflow to be created, run, and then modified to suit different ideas of how far each feature should be from a new park.

Creating a data processing workflow
My analysis should read like a flowchart: buffer the schools, trails, and bicycle lanes to make the ‘good’ areas. Buffer the existing parks and highways to make the ‘bad’ areas. Then remove the bad areas from the good areas, and find the areas that are common to the vacant parcels.

Developing a suitability model
To use the data and tools found in ArcGIS to accomplish suitability analyses, I’ll develop a model using ModelBuilder. ModelBuilder acts much like a living flowchart, with data elements connecting to tools creating outputs just like the flow processing diagram. A model serves not only as an organizational tool for doing data processing, but the elements of the model store parameter values and data paths that can be changed, and the model itself can be shared and run on different data. For example, other users can change the input datasets to their own parks and street network to achieve the same analysis.

By definition, geoprocessing tools take one or more pieces of geographic data, run a process based on parameters I define, and create a new piece of data as the result. That first result can be fed into another tool which results in yet another piece of data. Once the new data has been created, the old result can be discarded. This data is called intermediate data. Each piece of intermediate data should be written to a scratch workspace, which is defined in the environment settings of the map or model.  Keeping intermediate data in a scratch workspace is a great way to ensure I don’t end up with random datasets all over my computer.

Tools for models can be found using the Search window. The Search window will allow me to type in the name of a tool, dataset, or script and show results across all types of data. To add a tool to a model, drag the tool by its name, and drop it on the model canvas. Model elements can be connected using the Connect tool from the model window. Double-clicking a tool or element will open a dialog box that allows me to ensure the settings are correct before I run the model. ModelBuilder will also check the inputs are valid before running, and I can check them all manually by clicking the Validate Entire Model tool from the ModelBuilder toolbar. I can save the model in a toolbox, which can be stored anywhere on disk or in a geodatabase, as I am doing.

When the model runs, a dialog box shows me the progress, notification that it is finished, and any messages, warnings, or errors that might have occurred. The Results window is the location to track the status of a model or other geoprocessing operation.

Reusing models as tools
Another nice feature of models is they can be used in other models as tools. Since I already proved the effectiveness of measuring distances along the road network versus straight-line buffers, I can take the method I developed and use it as a tool in my park suitability model. I’ll call the tool Buffer Along Roads and use it for the schools and existing parks, which are the only datasets that require travel to be measured along the road network.

My model tool will operate as any other tool: it requires an input point dataset and will create a polygon dataset containing buffers along the roads using the distances exposed in the reclassification scheme. Once I’ve created these distance polygons, I then choose the ones that meet my criteria—in this case those that are ½ mile from existing parks and within ½ mile of schools.  From there, the rest of my analysis can continue using straight-line buffers from bike lanes, trails, and highways.

Determining the final location
When the model is finished, I see that there is more than one suitable location for a new park. I then have some work to do to figure out the final parcel or location. For example, perhaps I’m looking for the area that is closest to downtown. Using my park access analysis as an example, converting the final suitable polygons to points and running them through a cost distance tool would be one method to use.

However, I want to allow the citizens to provide input. In the next entry in this series, I’ll use ArcGIS Server to collect volunteered geographic information, crowd-sourced, or user-generated content to allow users to vote on their favorite location for a new park. This concept is now being referred to as “participatory planning”.

Accessing the data and models
The data and models for this blog post can be found here
The rest of the data and tools for this blog series can be found in the Park Analysis and Design group here (make sure to filter by Show: All Content at the top of the page)


Part 1 – Park analysis and design – Measuring access to parks

Part 2 – Park analysis and design: Locating a park through suitability analysis

Part 3 – Park analysis and design:  Voting on a new park location

Part 4 – Park analysis and design:  Sketching the design of a new park

Content for the post from Matthew Baker

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