How To

Creating your own background map tile cache

In our last webinar the issue of the background tile cache came up.  One question was would it be possible to have the tile cache on a thumb drive so that it could easily be moved to another computer.  Currently if you go to the tools menu in Depiction and select settings and then the advanced tab.

You will see a display that shows the default location of the tile cache.  Currently you can not change this field and you would need to do this in order to place the tile cache in a different location such as a thumb drive.  We are exploring the possibility of letting you update this setting to the location of your choice.

If you are unfamiliar with the tile cache let me explain its use.  When you are viewing your story in Depiction the back ground map source can be a map or an aerial image.  Depending on which you have chosen the program goes out to the internet and finds the desired image tiles for that location and zoom level you have chosen. When it finds them it stores them on your disk in the directory specified in the settings above.  However, before Depiction goes to the internet to look for a particular tile or tiles it first looks in the cache directory to see if the tile is already there.  If it is then Depiction  takes the tile from there and doesn’t go to the internet.  The benefit of this is speed and also if the internet is down it is still possible to display the background tiles. The downside of this is that if the map tile has been updated then Depiction will continue to display the old tile.  You might particularly notice this if you happen to update an Open Street Map yourself and then don’t see the change you made.  To get around this on the Basic Settings screen there is a check box to Overwrite existing cache with new. If you check this box then Depiction will ignore the cache and go directly to the internet.  Normally you would want to keep this box unchecked.

So knowing how depiction works using the cached files it would be possible to create your own cached tiles from a map source other than those provided by Depiction.  We have one customer in Germany that did just that.  He has written a paper on how he achieved this.  It is fairly advanced but with his permission I am sharing it with those of you that have the skill set and maybe inclined to attempt this.  You can find the document here.

Live Reports and Gmail 10-12-15

If you use a Gmail account for your live reports email you may have had a frustrating experience of the Live-Reports giving you an error message.  Turns out Google has made a change and they won’t allow “unsecured” applications to log in unless you give your permission.

From Google’s website:

Allow less secure apps to access accounts

We have added a feature that allows you to block sign in attempts at the domain or Organizational Unit level from some apps or devices that do not use modern security standards.

See the Frequently Asked Questions section below for examples of apps that do not support the latest security standards.

Since these apps and devices are easier to break into, blocking them helps keep your users’ accounts safer.

Default less secure apps account access

Existing users with any programmatic login requests with plain passwords in the last 90 days will be able to use less secure apps by default. New Google Apps users and existing Google Apps users with no programmatic login requests with plain passwords in the last 90 days will not. Instead, by default, they will see a “Password incorrect” error when trying to sign in to less secure apps.

Enabling less secure apps to access accounts

  1. Sign in to the Google Admin console .
  2. Click Security > Basic settings.
    Where is it?
  3. Under Less secure apps, select Go to settings for less secure apps.
  4. In the subwindow, check Allow users to manage their access to less secure apps .

Once you’ve set Allow users to manage their access to less secure apps to on, affected users within the selected group or Organizational Unit will be able to toggle access for less secure apps on or off themselves.

In order to give it permission log into your Gmail account and choose Sign-in and Security.

scroll to the bottom of the page. Turn on “Allow less secure Apps”

Depiction and the National Grid

During our webinar today one of the participants asked if Depiction was compatible with the USNG.  At the time I wasn’t sure what he was referring to.  He was kind enough to have an expert in its use drop me a line and point me to some resources. So here is what I have found out so far.  USNG stands for US National Grid system.  You can find a very complete description here.

The USNG is a based on the UTM coordinate system.  Depiction does have the ability to display locations in the UTM format.

Tools-Settings MenuIf you go to the Tools menu and choose settings and then click on the Coordinate format.  The UTM format is the 5th one down.

There is a website called the US National Grid Information center where you can find shape files for download.  However what I discovered was that these downloads have lots of data in them and you can’t have a depiction boundary too large and load one of these shape files because it can bring Depiction to its knees.  A couple of them I checked out had around 65,000 shapes. When I tried to load one of these for a large area it brought Depiction to its knees.  However, for smaller areas you are able to import the file.

Depiction displaying the National Grid

This Depiction area is 65 x 39 miles and has about 6600 shape elements.  Depiction was able to read it and display it but I noticed the program was a little sluggish. Especially when it had to display all 6600 shapes.  If you turn off the display of the shapes and display the shapes in a smaller revealer you will get much better performance. It is having to redraw those 6600 shapes everytime that you do something that causes the program to slow down.

So in order to use this go to the US National Grid Info Center web site.

US National grid web site

Choose the region you are interested in.

Choose the zone that covers your area of interest. Click on it and will start a download. Choose a location were you want the file to be downloaded. Once it is downloaded open the zip file and do an “extract all” and place the results in  a folder of your choosing.  Then start a depiction, keeping the size to around 2500 square miles or less. Then go to the add menu and choose the file option and browse to your folder.  Choose the file with the .SHP extension and auto detect for element type and click add and it will bring the file in.  When the shapes come in they are assigned random colors but if you want no color then you can go to the manage menu.  Select all of the shapes and choose edit. That will bring up this screen.

Depiction Manage - Edit Properties menu

scroll down to the ZOI Fill field and click on it which will bring up the color palate.  In the bottom right there is an option for no color. Choose that say apply and the colors will disappear.

Hope that will help those of you interested in the national grid.

New easier to use 2010 Census data now available

One of the ongoing challenges of using census data with depiction in the past was that you first had to import the census tract shape file and then export it and rename the geoid to EID and then reimport it. Then you had to find the census data by tract and change the GEOID to EID and then import it to merge with the shapes.  This was a fairly complicated and at times messy process.  In looking at the current CENSUS.GOV website, I discovered a file that has the census tract shapes along with lots of data for each census tract.

The url for the website is https://www.census.gov/geo/maps-data/data/tiger-data.html

You will need to click on the + next to Demographic Profile 1 — Shapefile Format to see the dropdown choices.

Then if you choose the census tracts option that is highlighted to the left, it will download a zip file (Tract_2010Census_DP1.zip) that contains census tract shapes along with census data for the entire USA.  This is a large file 400mb.

You need to extract the file and when you get done you should have the following files in your chosen directory.

When you import this file into Depiction you want to choose the .shp file, the one that is 591mb!  Remember to chose the crop to boundary option.

If you don’t choose the crop to boundary box then you will be loading all 590mb of data and Depiction will crash.

For an experiment I loaded the file for the entire state of Washington which had about 1600+ census tracts and data. It took 1 minute and 8 seconds to load and display. However once it was loaded it was kind of sluggish and if you had other data as well, would be unpleasant to work with.  However, if you were working at a county or even several counties it should be OK.

This is what it looked like.

So the good news is that you can easily import this file for anywhere in the USA and get the census tract shapes as well as population data.  The bad news is that rather than have descriptive property names they chose to use codes.  They include a .xls file (DP_TableDescriptions.xls) that gives a legend for the codes.  It would be possible to export the file to a csv file and copy in the descriptive property names over the codes but would take a bit of effort.

However there is lots of data over 200 data elements.  I’m going to list this all at the end of this post for your information.

I haven’t fully explored the other files they list on the web site but it looks like there is lots of interesting data to be had, and I urge you to explore and see what you can find of interest.  If you find something of interest please share it on our support page.

Below are the data elements that are included in the file.

ITEM STUB
DPSF1.  SEX AND AGE [57]
Universe:  Total population
DP0010001 Total:
DP0010002 Under 5 years
DP0010003 5 to 9 years
DP0010004 10 to 14 years
DP0010005 15 to 19 years
DP0010006 20 to 24 years
DP0010007 25 to 29 years
DP0010008 30 to 34 years
DP0010009 35 to 39 years
DP0010010 40 to 44 years
DP0010011 45 to 49 years
DP0010012 50 to 54 years
DP0010013 55 to 59 years
DP0010014 60 to 64 years
DP0010015 65 to 69 years
DP0010016 70 to 74 years
DP0010017 75 to 79 years
DP0010018 80 to 84 years
DP0010019 85 years and over
DP0010020 Male:
DP0010021 Under 5 years
DP0010022 5 to 9 years
DP0010023 10 to 14 years
DP0010024 15 to 19 years
DP0010025 20 to 24 years
DP0010026 25 to 29 years
DP0010027 30 to 34 years
DP0010028 35 to 39 years
DP0010029 40 to 44 years
DP0010030 45 to 49 years
DP0010031 50 to 54 years
DP0010032 55 to 59 years
DP0010033 60 to 64 years
DP0010034 65 to 69 years
DP0010035 70 to 74 years
DP0010036 75 to 79 years
DP0010037 80 to 84 years
DP0010038 85 years and over
DP0010039 Female:
DP0010040 Under 5 years
DP0010041 5 to 9 years
DP0010042 10 to 14 years
DP0010043 15 to 19 years
DP0010044 20 to 24 years
DP0010045 25 to 29 years
DP0010046 30 to 34 years
DP0010047 35 to 39 years
DP0010048 40 to 44 years
DP0010049 45 to 49 years
DP0010050 50 to 54 years
DP0010051 55 to 59 years
DP0010052 60 to 64 years
DP0010053 65 to 69 years
DP0010054 70 to 74 years
DP0010055 75 to 79 years
DP0010056 80 to 84 years
DP0010057 85 years and over
DPSF2.  MEDIAN AGE BY SEX [3]  (1 expressed decimal)
Universe:  Total population
Median age-
DP0020001 Both sexes
DP0020002 Male
DP0020003 Female
DPSF3.  SEX FOR THE POPULATION 16 YEARS AND OVER [3]
Universe: Population 16 years and over
DP0030001 Total:
DP0030002 Male
DP0030003 Female
DPSF4.  SEX FOR THE POPULATION 18 YEARS AND OVER [3]
Universe:  Population 18 years and over
DP0040001 Total:
DP0040002 Male
DP0040003 Female
DPSF5.  SEX FOR THE POPULATION 21 YEARS AND OVER [3]
Universe:  Population 21 years and over
DP0050001 Total:
DP0050002 Male
DP0050003 Female
DPSF6.  SEX FOR THE POPULATION 62 YEARS AND OVER [3]
Universe:  Population 62 years and over
DP0060001 Total:
DP0060002 Male
DP0060003 Female
DPSF7.  SEX FOR THE POPULATION 65 YEARS AND OVER [3]
Universe:  Population 65 years and over
DP0070001 Total:
DP0070002 Male
DP0070003 Female
DPSF8.  RACE [24]
Universe:  Total population
DP0080001 Total:
DP0080002 Population of one race:
DP0080003 White
DP0080004 Black or African American
DP0080005 American Indian and Alaska Native
DP0080006 Asian:
DP0080007 Asian Indian
DP0080008 Chinese
DP0080009 Filipino
DP0080010 Japanese
DP0080011 Korean
DP0080012 Vietnamese
DP0080013 Other Asian
DP0080014 Native Hawaiian and Other Pacific Islander:
DP0080015 Native Hawaiian
DP0080016 Guamanian or Chamorro
DP0080017 Samoan
DP0080018 Other Pacific Islander
DP0080019 Some Other Race
DP0080020 Population of Two or More Races
DP0080021 White; American Indian and Alaska Native
DP0080022 White; Asian
DP0080023 White; Black or African American
DP0080024 White; Some Other Race
DPSF9.  RACE (TOTAL RACES TALLIED) [6]
Universe:  Total races tallied
DP0090001 White alone or in combination with one or more other races
DP0090002 Black or African American alone or in combination with one or more other races
DP0090003 American Indian and Alaska Native alone or in combination with one or more other races
DP0090004 Asian alone or in combination with one or more other races
DP0090005 Native Hawaiian and Other Pacific Islander alone or in combination with one or more other races
DP0090006 Some Other Race alone or in combination with one or more other races
DPSF10.  HISPANIC OR LATINO BY SPECIFIC ORIGIN [7]
Universe:  Total population
DP0100001 Total:
DP0100002 Hispanic or Latino (of any race):
DP0100003 Mexican
DP0100004 Puerto Rican
DP0100005 Cuban
DP0100006 Other Hispanic or Latino
DP0100007 Not Hispanic or Latino
DPSF11.  HISPANIC OR LATINO AND RACE [17]
Universe:  Total population
DP0110001 Total:
DP0110002 Hispanic or Latino:
DP0110003 White alone
DP0110004 Black or African American alone
DP0110005 American Indian and Alaska Native alone
DP0110006 Asian alone
DP0110007 Native Hawaiian and Other Pacific Islander alone
DP0110008 Some Other Race alone
DP0110009 Two or More Races
DP0110010 Not Hispanic or Latino:
DP0110011 White alone
DP0110012 Black or African American alone
DP0110013 American Indian and Alaska Native alone
DP0110014 Asian alone
DP0110015 Native Hawaiian and Other Pacific Islander alone
DP0110016 Some Other Race alone
DP0110017 Two or More Races
DPSF12.  RELATIONSHIP [20]
Universe:  Total population
DP0120001 Total:
DP0120002 In households:
DP0120003 Householder
DP0120004 Spouse
DP0120005 Child
DP0120006 Own child under 18 years
DP0120007 Other relatives
DP0120008 Under 18 years
DP0120009 65 years and over
DP0120010 Nonrelatives
DP0120011 Under 18 years
DP0120012 65 years and over
DP0120013 Unmarried partner
DP0120014 In group quarters:
DP0120015 Institutionalized population:
DP0120016 Male
DP0120017 Female
DP0120018 Noninstitutionalized population:
DP0120019 Male
DP0120020 Female
DPSF13.  HOUSEHOLDS BY TYPE [15]
Universe:  Households
DP0130001 Total:
DP0130002 Family households (families)
DP0130003 With own children under 18 years
DP0130004 Husband-wife family
DP0130005 With own children under 18 years
DP0130006 Male householder, no wife present
DP0130007 With own children under 18 years
DP0130008 Female householder, no husband present
DP0130009 With own children under 18 years
DP0130010 Nonfamily households
DP0130011 Householder living alone:
DP0130012 Male
DP0130013 65 years and over
DP0130014 Female
DP0130015 65 years and over
DPSF14.  HOUSEHOLDS WITH INDIVIDUALS UNDER 18 YEARS [1]
Universe:  Households with individuals under 18 years
DP0140001 Total
DPSF15.  HOUSEHOLDS WITH INDIVIDUALS 65 YEARS AND OVER [1]
Universe:  Households with individuals 65 years and over
DP0150001 Total
DPSF16.  AVERAGE HOUSEHOLD SIZE [1]  (2 expressed decimals)
Universe: Households
DP0160001 Average household size
DPSF17.  AVERAGE FAMILY SIZE [1]  (2 expressed decimals)
Universe:  Families
DP0170001 Average family size
DPSF18.  HOUSING OCCUPANCY [9]
Universe:  Total housing units
DP0180001 Total:
DP0180002 Occupied housing units
DP0180003 Vacant housing units:
DP0180004 For rent
DP0180005 Rented, not occupied
DP0180006 For sale only
DP0180007 Sold, not occupied
DP0180008 For seasonal, recreational, or occasional use
DP0180009 All other vacants
DPSF19.  HOMEOWNER VACANCY RATE [1] (1 expressed decimal)
Universe:  Owner-occupied, vacant for sale only, and vacant sold but not occupied housing units
DP0190001 Homeowner vacancy rate (percent)
DPSF20.  RENTAL VACANCY RATE [1] (1 expressed decimal)
Universe:  Renter-occupied, vacant for rent, and vacant rented but not occupied housing units
DP0200001 Rental vacancy rate (percent)
DPSF21.  HOUSING TENURE [3]
Universe:  Occupied housing units
DP0210001 Total:
DP0210002 Owner-occupied housing units
DP0210003 Renter-occupied housing units
DPSF22.  POPULATION IN OCCUPIED HOUSING UNITS BY TENURE [2]
Universe: Population in occupied housing units
DP0220001 Owner-occupied housing units
DP0220002 Renter-occupied housing units
DPSF23.  AVERAGE HOUSEHOLD SIZE OF OCCUPIED HOUSING UNITS BY TENURE [2]  (2 expressed decimals)
Universe: Occupied housing units
Average household size-
DP0230001 Owner occupied
DP0230002 Renter occupied

Tutorial on how to get and add 10 meter elevation data in to your Depiction Map

Kim Buike, Depiction Board Member and Instructor teaching an on-line Masters course on Depiction Mapping Software for California State University Long Beach, has prepared a tutorial for his class on how to find, download and import into Depiction 10 meter elevation data.  The elevation data currently available through the Depiction Quick Start is 30 meter data.  Having higher resolution elevation data will make the various simulations that Depiction can perform much more accurate.  You can find the tutorial here.

New User Manual for Version 1.4

We have posted a new version of the Depiction 1.4 User manual on the website.  It can be downloaded here.

Why export data to a CSV file.

In our recent Depiction 101 Q&A webinar  (http://www.depiction.com/101/QA/Jan12)one of our customers asked the question about why one would want to export data to a CSV file if they had already imported it.  It was a good question and I came up with at least 5 reasons one might want to do that:

  1. Backup your data in a pre-geocoded format.
  2. If you moved elements to their geographically correct location, to save them in case you have to reload the elements at some point.
  3. To more easily make mass changes to the elements.
  4. To backup a subset of a large shape file.
  5. To change a shape file property to EID in order to merge data with it.

I wanted to elaborate a bit more on those reasons.

1. Backup your data in a pre-geocoded format.

When you import a CSV file with addresses.  Depiction goes out to the USC geo-coder and gets the latitude and longitude for each address and places the appropriate icon at that location.  Once you have done this, if you export those elements to a CSV file then they will include the lat/long of each element.  This way if you ever have to reload those elements or want to share them with somebody else, then the file won’t have to be geo-coded the next time. If you have a large CSV file this can save some time. It helps us too because every time you geo-code an address it costs us a few cents.

2. If you moved elements to their geographically correct location, to save them in case you have to reload the elements at some point.

This second item is similar to the first but with a little twist.  When the geo-coder geo-codes an address it will usually get it to the right block but not necessarily on the right lot in the block.  The reason for this is that if you an address of lets say 2025 main st, the geo-coder thinks that the address range for that block is 2000 to 2099. It calculates that 25 is one fourth of 99 and so it places the icon 1/4 of the way down that block.  Where in reality the real address range may be 2000 to 2032 and so the icon really should be at 9/10’s of the way down the block.  So if it is important to you to have the icons in the exact location you will have to go in and move each one.  Now if for some reason you have to reload that original  file then you are going to have to move all of those icons again.  Unless you had first exported it to a CSV file, in which case the program would have saved the new lat/long for each element.  So if you have to move a lot of icons to their geographically correct locations then backing them up to a CSV file is a really good idea.

3. To more easily make mass changes to the elements.

If you are using Depiction as a data base manager and are storing a lot of data along with each element, sometimes it is easier to make changes to the data in a spreadsheet program. So if you export them to a CSV file you can edit them in the spreadsheet program and then reload them.

4. To backup a subset of a large shape file.

A fairly new feature to Depiction in the 1.3 series is the ability to export shape files to a csv file.  So to give a specific example of when you might use this.  I was working with a community that was attempting to do a community wide map your neighborhood exercise.  One person had the entire community and a shape file was loaded that had all of the parcel boundaries for the community.  Using the shape drawing tool, we drew the neighborhood boundaries for all of the neighborhoods.  Then using the select tool we selected all of parcel shapes that were in a particular neighborhood. Then using the export to CSV function we exported the selected shapes to a CSV file.  Then we could start a new Depiction story and import that CSV file and we would have a depiction for just that neighborhood.  That file could then be given to the neighborhood coordinator who could use DepictionPrep to load the file and then make the appropriate changes and maps for their neighborhood.

5. To change a shape file property to EID in order to merge data with it.

This is really a neat feature.  Before we could export shapes to a CSV file this particular task was fairly complicated.

So lets say you have a shape file of zip codes and you also have some tabular data based on zip codes. In this tabular data  file you have the zip code and lets say median income, population, etc.  You want to be able to colorize your zip codes based on this numeric data. But how do you get the tabular data into the zip code shape elements. Here is a step by step process:

  1. Import your shape file
  2. Delete unwanted shapes (if necessary)
  3. Export your shapes to a CSV file
  4. Open the CSV file
  5. Change the property name of your key field i.e. zip code to EID and save the file
  6. In your depiction delete the shapes
  7. Re-import your CSV file of shapes
  8. Open your spreadsheet of data that you wish to merge.
  9. In our example we are saying the key field is Zip Code so in this file change the name of the zip code field to EID.
  10. Delete any other properties that aren’t of interest and then save that file
  11. In your Depiction chose Add by File and chose your csv file
  12. Select import by EID and then select Import – the data in this file will now be merged with the data in the shape file based on zip code
  13. Now if you open a shape element you should see the data fields you just imported and you can now colorize the shapes based on those fields.

Here are view other tips when dealing with CSV files.

TIP #1 – When you export elements it is best to export just one kind of element to a CSV file.  If you export multiple element types at once then you will get all of the properties for all of the elements in your resulting file, which is OK. But when you go to re-import that file all of the elements will have all of the properties of all of the elements which is probably not what you wanted.

TIP #2 - When you export to CSV it includes all of the default properties, any properties you have added and a bunch of depiction descriptive fields.  If you want can delete all of the descriptive fields to make the file easier to work with. We are looking to add a feature in a later release that would allow you to not have these fields show up on the export.

TIP #3 - If you are exporting a shape file and the shape is a fairly complex polygon it is possible that the number of points in that polygon will exceed the total amount of characters allowed in a single cell. In this particular situation we don’t have a solution to this and that shape may not be able to be re-imported properly.

I hope you find this information useful and feel free to send me any questions you have on any of it.

DepictionPrep Tutorial Video Now Available

A new tutoral video on how to use DepictionPrep to prepare a personal preparedness plan is now available on our YouTube channel.  This video discusses the need for every family to have a personal preparedness plan and how one fictional family might prepare one. Please take a look.

YouTube Preview Image

National Preparedness Month: LANL uses Depiction

National Preparedness Month is observed each September in the US. It’s a time when Americans take simple steps to prepare for the unknown. Depiction is partaking in this year’s event by featuring Los Alamos National Laboratory (LANL) and how they use Depiction to prepare for such events as wild fire, potential security threats and scenarios on chemical leaks.

This webinar is free to attend! Alan Woodward, EOC Planning Sections Chief at LANL, will highlight several tabletop exercises, scenario simulations and take questions from attendees. This webinar is great for individuals, organizations and companies interested in preparedness planning and consequence assessment. Alan comments that LANL uses Depiction for its “ease of use, flat learning curve, professionalism and fast in-field collaboration capability”.

Attendees will learn how Depiction can be used to create simulations and facilitate ‘in the moment’ cooperation whether for a national laboratory, your neighborhood, fire department, police department, local government organizations or emergency field teams.

Alan Woodward joins us as our guest presenter September 22nd at 10:30am PST. He has worked in the Emergency Operations Division for 10 years as an analyst, emergency planner, and Section chief with over thirteen years experience developing geographic information systems (GIS) and GIS products. He holds a Bachelor of Science degree from Washington State University (in Physics) and a Master of Science degree from Oklahoma State University (in Plant and Soil Sciences). Currently, he is focused on developing GIS applications for emergency responders that can be used in an EOC or at the site of an emergency.

Also joining in to field questions and provide additional information are Rachel Hixson, Dave McClard and Bill Purtymun.

Rachel Hixson is a Geographic Information Systems (GIS) specialist with a Master of Arts degree in Geography from Arizona State University.  She is helping to develop the GIS capabilities of LANL’s Emergency Operations Center.  She has also been working on reverse plume modeling for a national bio-surveillance program at Los Alamos National Laboratory (LANL) for three years.

Dave McClard works in the EO-EM Group as an Emergency Manager. Current responsibilities: Focus on response management, Emergency Operations Center (EOC) operability, planning and preparedness activities, communication operations, aviation operations, and wildland fire operations. Dave began emergency management work in 1986 as a search and rescue (SAR) pilot and search and rescue trainer. His last five years were spent as the State Emergency Services Director and squadron commander for an auxiliary of the United States Air Force.

Bill Purtymun originally became involved in emergency management as a Firefighter III/ EMT Paramedic.   He graduated from New Mexico Institute of Mining and Technology with a BS in Geology. He has been employed at Los Alamos National Laboratory since 1989, initially as a Site Safety Officer for a non-reactor nuclear facility.  In the mid 1990’s he became a LANL Emergency Manager and Incident Commander for the Emergency Operations Division.  For the past several years he has worked in Hazard and Consequence Assessment at the LANL Emergency Operations Center.  In his spare time he volunteers with the local ski and mountain bike patrol and is a Nationally Registered Paramedic.   He is currently working on his masters in Emergency Management through Arizona State University.

Join us on September 22nd at 10:30am PST to learn more about how your organization can be better prepared, cross collaborate more efficiently and benefit from the Depiction software platform.