New Version of Google Maps For Your Apps! E-Learning Course Released

GeoSpatial Training Services has released an update to it’s popular Google Maps For Your Apps! e-learning course. This course is designed to enable you to take advantage of Google Maps for your website. You will learn how to create maps, add map controls for user interactions (zooming, and panning), programmatically alter the map extent, add points of interest to the map, add custom icons, geocode addresses on the fly, read addresses from a database or XML file, display aerial photography, import KML files to the Google Maps display, integrate the new Google Earth API for 3D display of GMaps data in a web browser, and integrate local search.

Summary of New Content:

• Integration with the new Google Earth API for embedding Google Earth in a browser application
• Import KML files into Google Maps with the GGeoXML class
• Driving Directions, Traffic Conditions, and Street View
• Integration of Google Local Search into Google Maps applications
• An 8 step exercise designed to reinforce the concepts you learn in the lecture portion of the class

Course Modules:

• Module 1: Introduction to Google Maps
• Module 2: Google Maps Programming Basics
• Geocoding with the Google Maps API
• Reading XML Files (including KML) and Databases
• Traffic Conditions, Driving Directions, and Street View
• Google Earth Integration
• Local Search

During our 3rd Year Anniversary you can purchase this course for $45/e-delivery or $55/mail delivery. Other Google Maps and Google Earth bundles from GeoSpatial Training Services are available including the following:

• Google Earth and Google Maps Bundle
• Google Maps Developer Bundle
• Google Earth Developer Bundle
• Mastering KML in Google Earth
• Creating Mapplets with Google Gadgets
• Building Web Based Google Earth Applications
• Creating Dynamic Google Earth Applications

Display KML Files in Google Maps with GGeoXML

I just wanted to share a cool way that you can display your existing KML files inside a Google Maps application using the GGeoXML class from the Maps API. Many organizations have pre-existing KML files that were created for use within Google Earth, and the GGeoXml Maps API class provides a really simple means for also displaying this data in Google Maps as a GOverlay. Although we are specifically using this class to read a KML file in this example it is worth noting that this class can be used to read any XML file.

In this example, we’re displaying an auto-updating KML file containing Global MODIS Hotspots provided by the Fire Information for Resource Management System (FIRMS) at the University of Maryland. FIRMS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource manager and other stakeholders around the world. FIRMS is funded by NASA and builds on Web Fire Mapper, a web mapping interface that displays hotspots/fires detected by the MODIS Rapid Response System and delivers near real-time hotspot/fire information to international users.

FIRMS provides several auto-updating KML files for regions around the world. Any of these files can be loaded into Google Earth. What I’ve done is take the Continental USA KML file which is updated every four hours (as are the other files) and dynamically loaded the file into a simple Google Maps application using the GGeoXML class in the Maps API.

Take a look at this example and then I’ll describe how this is done within Google Maps.

From a code standpoint, the Maps API makes this a really easy task which can be done with only a few lines of code. To see the full code for this simple Maps application you can simply right click the web page and click View –> Source. I’ve posted the relevant code below. The initialize function is called when the web page loads. We create a new instance of the GGeoXML class and pass in a parameter to the constructor which contains a pointer to a KML file located on a remote web server. In this case we’re pointing to the Continental USA KML file located on the FIRMS web server. Once we’ve created an instance of GGeoXML we then add it to the map using the addOverlay( ) method on the GMap2 class. In between we have some additional Maps API code which creates the underlying map, centers the map, and adds the map controls.

As you can see, using the GGeoXML class to add pre-existing KML files to your Google Maps application is quite simple and very useful. Even the descriptive balloons contained within the KML file have been ported to info windows in Google Earth. Click one of the fire locations to return specific information about a particular fire.

For more information on the Google Maps API or GeoSpatial Training Services please see our e-learning course entitled “Google Maps For Your Apps” or our “Google Maps Developer Bundle” which is currently on sale as part of our 3rd Year Anniversary Sale.

Benefit from GIS E-Learning Opportunities

Introduction
In recent years there has been a large movement towards e-learning in many industries, and GIS is no exception. Although computers will never completely eliminate the need and desire for human interaction between instructor and student, the many benefits it offers far outweigh the limitations of the medium. In this post we will examine the benefits, drawbacks, availability, and types of e-learning currently available to GIS professionals.

Features Unique to E-Learning
Knowing a little bit about learning styles can help you determine if e-learning is for you. The interaction and delivery methods used in online classes are dramatically different from traditional classes, so understanding how you learn is a good part of the decision-making process. The three predominant learning styles are visual, auditory, and tactile/kinesthetic. Visual and auditory learning styles fall into the category of passive learning modes while the tactile/kinesthetic learning style is an active learning mode. An active learning mode implies that learning is accomplished by doing or practicing a task and/or speaking about what we learn. Most people tend to fall into this category. However, some people learn best through a passive learning mode which is done through seeing and reading.

Like no other training form, e-learning promises to provide a single experience that accommodates the three distinct learning styles of auditory learners, visual learners, and kinesthetic learners. Other advantages created by the advent and development of e-learning are more efficient training of a globally dispersed audience; reduced publishing and distribution costs as Web-based training becomes a standard; and decreased costs of training from a travel and training materials standpoint.

E-learning also offers individualized instruction, which print media cannot provide, and instructor-led courses allow clumsily and at great cost. In conjunction with assessing needs, e-learning can target specific needs. And by using learning style tests, e-learning can locate and target individual learning preferences.

Additionally, synchronous e-learning is self-paced. Advanced learners are allowed to speed through or bypass instruction that is redundant while novices slow their own progress through content, eliminating frustration with themselves, their fellow learners, and the course.

In these ways, e-learning is inclusive of a maximum number of participants with a maximum range of learning styles, preferences, and needs.

Benefits
Some of the advantages to the learner include:

• Reduced cost
  This is the single most influential factor in adopting e-learning. The elimination of costs associated with student travel, lodging, and meals are directly quantifiable. With the cost of gasoline now reaching over $4.00/gallon and airfare costs increasing weekly this adds up to big savings. The reduction of time spent away from the job by employees may be the most positive offshoot.
• Learning times reduced
  An average of 40 to 60 percent, as found by Brandon Hall (Web-based Training Cookbook, 1997, p. 108).
• Increased retention
  Retention averages an increase of 25 percent over traditional methods, according to an independent study by J.D. Fletcher (Multimedia Review, Spring 1991, pp.33-42).
• On-demand availability
  Enables students to complete training conveniently at off-hours or from home.
• Self-pacing
  For slow or quick learners reduces stress and increases satisfaction.
• Interactivity
  Engages users, pushing them rather than pulling them through training.
• Confidence
  Responsibility of mastery is reduced since materials are available as a refresher or quick reference materials.

Drawbacks
The ways in which e-learning may not excel over other training include:

• Technology issues
  Some learners are fearful or intimidated by technology or the technology is unavailable for use.
• Portability
  E-Learning is not as portable as printed workbooks or reference material, but the limitations of portability have been greatly reduced through wireless connections, network links, notebook computers, PDAs and mobile phones.
• Reduced interaction
  Social and cultural interaction can be a drawback. The impersonality, suppression of communication mechanisms such as body language, and elimination of peer-to-peer learning that are part of this potential disadvantage are lessening with advances in communications technologies.

Types of E-Learning and Delivery Methods
E-learning takes many forms including the following:

• Web based (Blackboard, Moodle, WebCT)
• Computer-based (CD-ROM)
• Blended learning – combination of online and face to face
• Video/audio
• Blogs, Chat, and Discussion Forums
• Hard-copy Workbooks
• Videoconferencing and/or Teleconferencing

It is not uncommon for more than one of these delivery formats to be used in the same course of study to supplement the learning experience.

Availability of GIS E-Learning Opportunities
A number of GIS e-learning opportunities exist from commercial and academic institutions. We don’t have room in this article to highlight all the available distance learning programs offered by colleges and universities so we have highlighted a few of the better known options.

Non-Academic

• GeoSpatial Training Services
  Our company, GeoSpatial Training Services, provides both web-based and computer-based e-learning opportunities focusing primarily on Google Earth, Google Maps, and ESRI technologies.
• ESRI Virtual Campus
  The ESRI Virtual Campus hosts a number of self study courses through their virtual campus.
• New Urban Research
  New Urban Research offers twelve advanced topic ArcGIS Tele-Classes.

University Distance Learning Programs

• UNIGIS International
  UNIGIS is a worldwide network of educational institutions which offer distance learning courses in GIS. Institutions within the UNIGIS network offer internationally recognized qualifications for GIS professionals and those seeking to enter the field.
• Penn State University
  Penn State offers a Masters Degree in GIS through their World Campus program.
• Institute for Advanced Education in Geospatial Sciences
  IAEGS was established as a collaborative course development center, based at the University of Mississippi in Oxford, Mississippi and hosts a number of courses on topics such as remote sensing, photogrammetry and digital image processing, and other geospatial technology topics.
• University of Southern California
  USC offers both a Master of Science + Technology degree along with a GIST certificate program.
• Elmhurst College
• University of Denver

GeoSpatial Training Services: Our Approach to GIS E-Learning
At GeoSpatial Training Services, we focus on the development of Internet based and computer based (CD-ROM) courses for the geospatial industry and we focus heavily on Google Earth, Google Maps, and ESRI technologies. Through our Virtual GIS Classroom we offer Internet based courses such as “GIS Programming 101: Mastering Python for Geoprocessing in ArcGIS” and will soon have additional offerings. In addition, we offer a wide array of computer based GIS training options available by e-delivery (download) or traditional via traditional CD-ROM. Furthermore, we develop custom training solutions for geospatial custom off-the shelf products (COTS) and organizations and conversion of instructor led training materials to various e-learning formats.

Controlling the Google Earth Camera

The <Camera> element, new to KML 2.2, provides a way to define your observer’s viewpoint in terms of position and viewing direction, and is a child element of any <Feature>.  Features can include Placemark, NetworkLink, Folder, Document, PhotoOverlay, ScreenOverlay, and GroundOverlay.  In previous KML versions (2.1 and earlier) a similar element, <LookAt> was used to define the placement and orientation of the camera. 

Differences Between <Camera> and <LookAt>
Let’s take a look at these two elements to determine how they differ.

As you can see from these figures the two elements look quite similar, but they have some fundamental differences.  Let’s start with the <longitude> and <latitude> child elements.  In <LookAt>, these elements refer to the point the camera is looking at, whereas in <Camera> these elements refer to the virtual camera (eye point).  This is an important distinction.  <LookAt> specifies the view in terms of the point of interest while <Camera> specifies the view in terms of the viewer’s position and orientation.  Similarly, the <altitude> element refers to the altitude of the point of interest for <LookAt> whereas it refers to the distance of the camera from the earth’s surface for <Camera>. 

There are some additional differences between the two elements.  For instance, <LookAt> contains a <range> child element that specifies the distance in meters from the point of interest specified by <longitude>, <latitude>, and <altitude> to the LookAt position.  The <Camera> element does not contain this particular element.  In addition, the <Camera> element also provides additional functionality for controlling the tilt of the camera view.  The <tilt> element in <Camera> can be any value between 0 and 180 which gives you the ability to tilt the camera above the horizon into the sky, whereas in <LookAt> you are limited to a value between 0 and 90.  In either element, a value of 0 indicates that viewing is from directly above, while a value of 90 indicates viewing along the horizon.  Because <LookAt> can contain only values between 0 and 90 you are limited to viewing from directly above through a horizontal view.  As I mentioned above, the <tilt> values for <Camera> can range from 0 to 180 with values greater than 90 indicating a view that is pointed above the horizon toward the sky.  Finally, the <roll> element on Camera gives you the ability to rotate the camera around the Z axis and can contain any value between -180 and +180 degrees.

Examples
Now we’ll take a look at a few examples that illustrate different <Camera> settings taken from the San Diego Convention Center and Petco Park.  You can download the file containing all examples here.  You’ll want to make sure you turn on the 3D buildings in the Google Earth layers panel before opening the file.

Heading
This first example shows a <Camera> with a heading of 90 degree (East) and a tilt of 90 degrees (toward horizon).  Remember that headings can be any value between 0 (north) and 360.  The default is 0 or north.  The Camera in this case is placed at an altitude of 100 meters. 

Tilt
In the next example, we set the <tilt> value to 0 which will set the camera to look straight down toward the earth.  We’re also setting the <heading> to north and the <altitude> to 500 meters.

 Now let’s try something a little different.  In this next example, we’re going to take a look inside Petco Park from the viewpoint of a major league baseball platter in the batter’s box.  In this case we are setting the <tilt> to 110 which points slightly up into the sky.  We’re also setting the altitude to slightly above sea level.

Roll
Finally, we’ll examine the <roll> element which rotates the camera around the Z axis with values ranging from -180 to +180.  Sticking with our Petco Park example, assume that the pitcher has thrown a wild pitch and hit the batter!  The batter has subsequently fall down.  Ouch!  Using the <roll> element with a value of 45 which will roll the camera to the left we can simulate the viewpoint of the batter who is now lying on the ground.

 Hopefully these examples have helped illustrate how you can use the Google Earth <Camera> element to control the user viewport and using your imagination you can come up with some creative ways to use these features in your analysis of geographic data.

More Information
For detailed information about KML, Google Earth, or Google Maps please see the following e-learning courses provided by GeoSpatial Training Services.

• Mastering KML in Google Earth
• Dynamic Google Earth Applications
• Google Maps For Your Apps
• Google Earth for ArcGIS Users
  

During the month of May you can get $20.00 off our Google Maps and Google Earth Bundle by entering the discount code SAVEONBUNDLE when purchasing through our website.

Creating Compelling Google Earth Description Balloons

In this post I’m going to cover the topic of creating compelling Google Earth description balloons for your placemarks. These descriptive balloons are a fantastic way of communicating information to your users, and can include HTML, text, images, videos, hyperlinks, and pretty much anything else that you would like to portray to users. Because of the diversity of content that can be included in a description balloon, they tend to make excellent teaching tools, and have been used as such by National Geographic, Greenpeace, Global Heritage Fund, Earthwatch, and many others.

KML for Balloons
We’ll start with some basic information about how these balloons are created in KML. Descriptive balloons are attached to Placemarks in Google Earth, and are displayed when clicked. The creation of a description balloon for a placemark is accomplished with the use of the <BalloonStyle> KML element. A <BalloonStyle> is a ‘type of’ or child of the <Style> element so it is common practice to define a balloon style within the context of a <Style>. Therefore, you could have something like this:

Notice that we are assigning an id of ‘sn_ywl-blank’ to the <Style> element. This is just a descriptive name that we’ll user later to refer back to this content. Inside <Style> we have our <BalloonStyle> element which contains the details of our balloon. For simplicity, we are only using the <text> element in this case. Now let’s cover the details of what can be included inside <BalloonStyle>.

The <BalloonStyle> element has a number of child elements that are used to control the content and display characteristics of the items including in our descriptive balloon. The background color <bgColor>, text color <textColor>, text <text>, and display mode <displayMode> can be used within <BalloonStyle>. The background color and text color elements are self explanatory, but the <text> element in particular deserves more attention.

The <text> element contains the content that will be displayed in the balloon. In the event that you do not specify any text, Google Earth will draw a default balloon with the feature name, feature description, links for driving directions, a white background, and a tail that is attached to the point coordinates of the feature. But we’re really not interested in the default behavior since we are pursuing the creation of informative, compelling description balloons.

Inside the <text> element you can embed HTML along with various entities that are used refer to a child element of the placemark. These entities include $[name], $[description], $[address], $[id], $[Snippet], and $[geDirections]. An example is in order here to more clearly explain this. In the code example below you’ll notice that the <text> element contains a $[description] entity.

What this means is that the description contained within the <description> element of a placemark will be substituted in this place and thus allowing for unique content associated with each placemark. This description can contain HTML, hyperlinks, images, and videos.

For example, in the image below I’ve right clicked on a placemark and selected Properties. The Description tab displays the content of the <description> tag inside a placemark. Click here to see the actual file. What you’re looking for is the <description> tag inside the <Placemark> element. You should also look for the <styleUrl> element toward the bottom of the file. This element contains the text ‘#sn_ylw-blank’ which is used to point back to the <Style> element that we defined earlier.

As I mentioned above, there are a number of other entities that you can add to the <text> element. The same concept applies for these entities. Each of these entities can be used to obtain the information stored in the corresponding element found on the placemark.

One other point should be made here. When embedding HTML inside the <text> element you can use a CDATA section to ensure that the parser will ignore your markup characters. Between the start and end of a CDATA section, all character data is passed directly to the application without interpretation as you can see in the example below.

Templates
At this point we’ve covered the basic elements that you’ll use to create descriptive balloons. However, if you’re like me and have little to no graphic design skills you’re probably wondering how to go about creating attractive content for your balloons. Fortunately, Google has provided a number of templates that we can use as a starting point. You can make copies from these templates and then add in your own text, images, and other content.

You can’t update the content of your description balloons in Google Earth so you’ll need to use a text editor or an HTML editor such as Dreamweaver or NVU. You can copy the HTML from the templates into your favorite editor, edit the content as necessary, and then replace the existing template code.

Other Cool Stuff – Adding YouTube Videos
In addition to being able to customize your description balloons by adding text, images, and hyperlinks you can also embed a YouTube video into your balloon. This Google Outreach tutorial will walk you through the process of adding YouTube videos to your descriptive placemark balloons.

Examples
The Global Awareness folder inside the Layer panel contains many examples of compelling placemark balloons that you can use as a guide when you begin developing your own content.

More Information
For detailed information about KML, Google Earth, or Google Maps please see the following e-learning courses provided by GeoSpatial Training Services.

Mastering KML in Google Earth
Dynamic Google Earth Applications
Google Maps for Your Apps!
Google Earth for ArcGIS Users

During the month of May you can get $20.00 off our Google Maps and Google Earth Bundle by entering the discount code SAVEONBUNDLE when purchasing through our website.

Using Spreadsheet Mapper 2.0 with Google Earth & Google Maps

Over the next few weeks I’m going to be writing a series of posts on some of the lesser know tools provided by Google for creating data layers in Google Earth and Google Maps.  The Google Earth Outreach program provides a number of these tools.  According to a press release from early last summer, Google Earth Outreach is “designed to help nonprofit organizations around the world leverage the power of Google Earth to illustrate and advocate the important work they do.”  The program includes comprehensive online guides, video tutorials, and case studies about using Google Earth specifically targeted to the needs of nonprofit organizations.  In addition, organizations can also apply for a Google Earth Pro grant ($400 value). 

In this initial post we’ll take a look at the Spreadsheet Mapper 2.0 tool created by the Outreach team for creating Google Earth and Google Maps placemark layers using Google Docs.  Google Docs is a great way to create, share and collaborate on documents, spreadsheets and presentations online.  Spreadsheet Mapper takes advantage of this online, collaborative environment by allowing you to create placemark layers for display in Google Earth and Google Maps through a spreadsheet created in Google Docs.  Because Google Docs is a collaborative tool, members of your team can simultaneously enter data and instantly publish updates to GE and GMaps.  So, let’s take a look at how this is done through a basic example.

In this example we’re going to create a placemark KML file containing existing Starbucks locations. The Starbucks data contains a unique identifer for each location along with the latitude, longitude coordinate pair and a physical address.  This data is contained within the “Starbucks No Linefeeds.csv” file which was last updated in January 2008. This file contains almost 9,000 Starbucks locations.  Since there are so many locations I’m only going to use a sample area for this example. The download also contains a Starbucks.bmp image which we’ll use in our next post in the series which covers Spreadsheet Mapper templates for styling icons and information balloons.  Let’s get started.  By default, Spreadsheet Mapper will use various templates to create some sample data.  We’ll do this first and then replace the sample data with our own Starbucks location data.

1. Open the starter spreadsheet.  If you haven’t already done so you’ll need to login to your Google account or create one if necessary.
2. Select File –> Rename and give you spreadsheet a name (”Starbucks Locations”).
3. Fill in the “Author’s Information” and “About your KML Document” sections.
   
4. Optional Parameters
   • Enable “Google Maps Compatibility” if you want the layer to work in Google Maps
   • Access the “Advanced/Optional Settings” by clicking the tab indicated on the left to un-hide rows
5. Click the Publish tab and select Publish Now.  This step will publish the document to the web at the URL listed.
   
6. Copy the publisher URL and paste it into the white cell provided under “Publish spreadsheet”.
   
7. Copy the “Network Link KML” cell that you see below, open Google Earth, select My Places, then right-click and paste.
   Network Links capability in Google Earth provides for the delivery of dynamic data to your users.  We are using a Google Docs spreadsheet which can be edited by multiple users simultaneously.  Network Links in Google Earth are a perfect complement to a Google Docs spreadsheet since they can automatically refresh the Google Earth display to reflect updated data from a spreadsheet.  Get more information on Network Links in our “Mastering KML in Google Earth” e-learning course.So, at this point we’ve copied the sample data contained in the template into Google Earth.  You will notice a variety of folders, placemark icons and information balloons which have been created based on parameters found in the templates contained within Spreadsheet Mapper.
   
   The Spreadsheet Mapper comes with six templates that can be used to control icon and balloon styles.  Click any of the links at the bottom of the spreadsheet to get more information about each of these templates.  We’ll cover detailed information about the templates in a coming slide, but for now you can get an idea of how they are structured.
   
8. At this point you’d want to prepare your template values.  However, as I mentioned above I’m going to save the details of altering the template values for another post since it really deserves a thorough explanation. 
9. Now let’s add in the Starbucks data.  Open the “Starbucks No Linefeeds” Excel spreadsheet which contains the latitude,longitude, identification, and address values for each Starbucks location.  Due to the large size of the file I’m only going to add in Starbucks locations for my city, San Antonio.  Go to the PlacemarkData link at the bottom of the spreadsheet.
   • The Folder Name is optional, but in this case we’re going to define the folder name as “Starbucks” for each placemark instance.  What this will do is group the placemarks under the same Folder in Google Earth.  This would be helpful if you’d like to group Starbucks locations by city (i.e. San Antonio, Dallas, Houston, Austin). 
   • For the Placemark Name column I’m going to add in the unique identifier for each location based on the information pulled from the Excel spreadsheet we downloaded.  You should be able to copy and paste the data from MS Excel to the Google Docs spreadsheet to save time.
   • We’ll also enter the latitude, longitude values for each Starbucks location, also pulled from the Excel spreadsheet we downloaded.  If you don’t have coordinate values for each placemark you can enter an address which can be used to generate the placemark. 
   • Finally, we specify a template (#5 in this case) to define our icon and balloon styles.  The spreadsheet should look something like you see below.
10.  Click Publish –> Re-publish document in your Google Docs spreadsheet.  Then refresh your network link in Google Earth by right clicking on “Link to - Spreadsheet” in the Places panel and selecting Refresh.  This should refresh the Google Earth display with the new Starbucks locations we entered in the Google Docs spreadsheet.

 

In our next post we’ll cover the templates provides by Spreadsheet Mapper and also take a look at how you can create your own templates.

March Sale on Google Earth and Google Maps E-Learning Courses

During the month of March we are offering a 15% discount on our “Google Earth and Google Maps Bundle” e-learning set.  Sale price is $170.00 (e-delivery), $210.00 (mail delivery).  This bundle is composed of 5 e-learning courses with over 450 pages of instruction.  Courses include:

• Mastering KML in Google Earth
• Google Maps For Your Apps
• Google Earth for ArcGIS Users
• Arc2Earth for ArcGIS Users
• Dynamic Google Earth Applications (in development)

GeoSpatial Training Services - March 2008 Update

GIS Programming 101 Course
Our GIS Programming 101 course scheduled for March 24th - April 18th is almost full.  We still have one seat available so if you’re interested please let us know ASAP.  Because the demand for this course has been so high we will be offering a second section of this course in the May-June timeframe.  The exact timing of the course has not been determined as of yet, but we will let everyone know as soon as we have the dates. 

This is an instructor guided course taught in a Virtual GIS Classroom using the same technologies implemented by colleges and universities around the world to deliver Internet based courses. Our new Virtual GIS Classroom blends the best of instructor led and e-learning formats into a new instructor led web based format that allows for more interactivity between the instructor and student, and between students.

GIS Programming 101: Mastering Python for Geoprocessing in ArcGIS is designed to teach the fundamental programming constructs of the Python language and how it can be integrated with ArcGIS Desktop to automate geoprocessing tasks.  Course participants will be led through a series of 13 modules described below.
Module 1:  Getting Started with Python in ArcGIS
Module 2:  The Geoprocessor ArcObject
Module 3:  Basic Python Language Features
Module 4:  Obtaining Descriptive Information About ArcGIS Data
Module 5: Using Cursor Objects to Select, Edit, and Add Records to Tables and Feature Classes
Module 6:  Enumeration Objects for Listing ArcGIS Data
Module 7:  Miscellaneous Objects
Module 8:  Dynamic Scripts
Module 9:  Integrating Python Scripts with ArcToolbox
Module 10:  Geoprocessing Tools
Module 11: Scheduling Geoprocessing Tasks
Module 12:  Messaging and Error Handling
Module 13:  Final Project

March Sale on Google Earth and Google Maps E-Learning Courses
During the month of March we are offering a 15% discount on our “Google Maps and Google Earth Bundle“.  Regular price is $200.00 (e-delivery), $250.00 (mail delivery), but during the month of March you can purchase this bundle for $170.00 (e-delivery), $210.00 (mail delivery). This bundle is composed of 5 e-learning courses with over 450 pages of instruction.  The five courses are as follows:

Mastering KML in Google Earth
Google Earth for ArcGIS Users
Google Maps for Your Apps!
Arc2Earth for ArcGIS Users
Dynamic Google Earth Applications (in development scheduled for March release)

See more information on these courses.

As always we offer an additional 15% discount on any course to all educational, non-profit, local, state, and federal government organizations.  Please contact sales at geospatialtraining.com to take advantage of this discount.

Mapping Saudi Oil Production with Google Earth

Just wanted to pass along a link to an interesting blog that I ran across.  Satellite O’er the Desert, the unofficial web companion to the book Twilight in the Desert by Matt Simmons. 

The blogs purpose according to the author: 
“This blog presents satellite imagery and analysis pertinent to the energy infrastructure of Saudi Arabia. It uses the book Twilight in the Desert by Matt Simmons as a guide to the rather secretive doings of Saudi Aramco, the state-owned petroleum company. Because Saudi Arabia is home to the world’s most productive oil fields, it has attained an almost mythical status in its ability to delivery increasing amounts of energy now as well as in the future. In his book, Matt Simmons has presented a comprehensive overview of the history, current state, and future prospects for oil production by Saudi Arabia. Rather than trying to duplicate this work, I will use it as a rough outline and reference to a more visual exploration of this desert kingdom.”

Whatever your thoughts may be concerning the concept of peak oil I think you’ll find this to be an interesting use of Google Earth for analyzing potential oil production in this critical oil producing area.

Creating KML Regions from ArcGIS Data Using Arc2Earth

Our previous posts on basic and advanced KML Region concepts gave you some background on how this functionality can be used allow you to stream your data in pieces instead of as a whole making it possible to deliver large datasets to the Google Earth viewer.  In this post you will discover how to use Arc2Earth with your existing ArcGIS data to create these powerful features.

 Arc2Earth can be used to create Google Earth Regions through the Regions tab with the Publisher version of Arc2Earth.  The General Options button displays the Region Options dialog which can be used to set the fade effects and level of detail (LOD) for the region.  You must also select a region level which is basically a course grain level similar to the levels of map tiles used in Google Maps or MS Virtual Earth.  Each level represents an approximate map scale.  The Visualize button displays a map window with the grid showing the regions for your export along with your layer data. 

The Visualize window is particularly helpful in allowing you to see the extent of the Regions that will be created along with your data.  The red lines displayed in the viewer indicate how your data will be regionalized.  You can also dynamically reset the region level through this window to see the effect this will have on the size of the Regions.  Map navigations tools are also provided.

Demonstration
Click here to see a demonstration of using Arc2Earth to export parcel and floodplain data as KML Regions.

More Information
GeoSpatial Training Services provides e-learning courses for GIS users.  If you would like more information on Regions and other KML elements please see our “Mastering KML in Google Earth” e-learning course.  Other related courses include “Google Earth for ArcGIS Users“, “Google Maps For Your Apps“, “Arc2Earth for ArcGIS users“, and our “Google Bundle” which combines all these courses into one package at a significant discount.

Advanced KML Region Concepts (Altitude, Fade Extent, Nested Regions)

In our last post on KML Regions we covered some background information on KML Regions and the various ways in which they can be used in Google Earth to display large GIS datasets.  In this post we are going cover additional Region subjects including altitude, fade extent, and nested regions.

Bounding Box 
As we mentioned in our previous post, the bounding box and level of detail (LOD) are two of the basic, key concepts in creating Regions.  A bounding box, defined by the <LatLongAltBox> element, describes an area of interest defined by geographic coordinates and altitudes.  This element contains the child elements <north>, <south>, <east>, and <west> that define the boundaries of the Region.  A Region is considered “active” or visible when the bounding box is within the display and the level of detail requirements are met. 

Level of Detail 
The Level of Detail (LOD) is defined with the <Lod> child element of <Region>.  It defines a range, specified by <minLodPixels> and <maxLodPixels> that determines the visibility of data within a Region.  This ensures that large amounts of data are only loaded when enough pixels are available to display the data adequately.  When the Region takes up a relatively small percentage of the screen, the LOD allows you to specify a dataset with a lower resolution.  The <Lod> value units are defined by square pixels.  Data must occupy an area greater than <minLodPixels> and less than <maxLodPixels> to be visible. 

 There are a number of other Region concepts that you need to be familiar including altitude, fade extent, and nesting regions. 

Altitude
The <LatLonAltBox> element can contain child elements which control the minimum <minAltitude> and maximum altitudes <maxAltitude> at which a Region will display.  Notice in the figure below that the minimum altitude at which the Region will display is 10000 meters and the maximum altitude is 50000 meters.  These child elements are containing within the <LatLonAltBox> element. 

Fade Extent
By setting a fade extent for a Region, you can enable your objects to transition seamlessly from transparent to opaque, and back again.  You do need to be careful when setting a fade extent for a Region because they are computationally expensive, and should only be used with vector data such as LineStrings, Polygons, and Points, but not with imagery data.  Fade extents are set with the <minFadeExtent> and <maxFadeExtent> child elements of <Lod>.  These are set as pixel values similar to the values you set for <minLodPixels> and <maxLodPixels>, and are used in conjunction similar to the code you see below.

The <maxFadeExtent> is used to determine the ramp from fully transparent to fully opaque when the Region is at its maximum visible size.  The <minFadeExtent> element is used to determine the fade ramp when the Region is at its minimum visible size. 

Nesting Regions
Regions can be nested so that smaller, increasingly finer levels of detail are shown as the user zooms in on the display.  Previously loaded coarse levels of detail are gradually replaced with these more detailed Regions. 

<LatLonAltBox> elements in a child Region should be wholly contained within the <LatLonAltBox> of its parent Region. 

In our next post we’ll show you how to use Arc2Earth to create Regions from your ArcGIS data.

More Information
GeoSpatial Training Services provides e-learning courses for GIS users.  If you would like more information on Regions and other KML elements please see our “Mastering KML in Google Earth” e-learning course.  Other related courses include “Google Earth for ArcGIS Users“, “Google Maps For Your Apps“, “Arc2Earth for ArcGIS users“, and our “Google Bundle” which combines all these courses into one package at a significant discount.