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Wednesday, July 24, 2013

Seafloor Mapping

Seafloor Mapping

Bob Embley
Geophysicist
NOAA, Pacific Marine Environmental Laboratory


Three-dimensional image of Nikko Submarine Volcano
Nikko submarine volcano has two summit cones within the remnant of a large circular caldera, which has been subsequently filled by eruptive material.
 

 

Producing maps of the seafloor has always been a particular challenge to humankind. The first primitive maps came from successions of single soundings produced by lowering weighted lines into the water and noting when the tension on the line slackened. By measuring the amount of line paid out, one could determine the depth. These early maps gave only the most general picture of the ocean floor, and only the larger features could be identified by looking for patterns in many such soundings. Most of these surveys were conducted to identify near- shore hazards to shipping. Only in the late nineteenth century did expeditions begin to take large numbers of soundings in deep water.

Single and multibeam sonar
 
Comparing single (left) and multibeam (right) echo sounding of the seafloor. The multibeam method is preferred because it measures an entire area rather than a single line of seafloor.
 


The first modern breakthrough in seafloor mapping came with the use of underwater sound projectors called “sonar,” which was first used in World War I. By the 1920s, the Coast and Geodetic Survey (the predecessor agency to NOAA’s National Ocean Service) was using sonar to map in deep water. The team of A. C. Veatch and P. A. Smith produced one of the first detailed maps of the ocean floor. This map showed that the canyons off the East Coast of the United States extended into very deep water.
During World War II, advances in sonar and electronics led to much improved systems that provided precisely timed measurements of the seafloor in great water depths. These systems provided the databases used to construct the first real maps of important features, such as the deep-sea trenches and mid-ocean ridges. The 1957 publication of Heezen and Tharp’s physiographic map of the North Atlantic was the first map of the seafloor that allowed the general public to begin to visualize the ocean floor. These early maps based on hundreds of thousands of hand-picked depths provided the context for the plate tectonics revolution in the 1960s that finally gave scientists satisfying explanations for the formation of mid-ocean ridges, trenches, mountain ranges and the “ring of fire” around the Pacific.

Heceta Bank Simrad EM 300 backscatter and topography
 
Heceta Bank Simrad EM 300 backscatter (left) and topography (right) on 10m grids. The backscatter image reveals seafloor physical properties and texture of the seabed. White areas depict cobble, boulder and sand areas. Black areas depict muddy areas.
 


Still, these systems only produced depth soundings immediately below the ship’s tracks. To produce maps of the shape of the seafloor, one had to laboriously “contour” an area by connecting lines of equal depth together. Although the advent of digital computers in the 1960s provided much needed automation for plotting data, the civilian scientific community was still using the same basic technology until the 1970s.
In the 1960s, the U. S. Navy began using a new technology of “multibeam sonar." Arrays of sonar projectors produced soundings not only along the track, but also for significant distances perpendicular to the ship’s track. Instead of lines of soundings, these new multibeam systems produced a swath of soundings. Combined with automated contouring, the ability to make detailed, complete maps of large areas of the seafloor became available to the scientific community for the first time in the late 1970s after the Navy declassified the technology. Since these first multibeam systems, this technology has steadily improved, and modern systems can map swaths up to several times the water depth. Combined with positional information gained by the geographic positioning navigation systems and advanced computer graphics, these systems now provide a whole new view of the seafloor.

Sidescan sonar towed instrument and the sidescan data
 
Schematic diagram of a sidescan sonar towed instrument scanning the seafloor (top) and the sidescan data record created (bottom).
 


Knowing the shape of the seafloor is critical to advancing our knowledge of the ocean. It is also critical that we map changes in the composition of the seafloor. However, whereas the depth can be measured using the timing of the signals going to and from the seafloor, a precise measurement of the “strength” of the sonar return is needed to determine the texture of the seafloor. For example, a sound pulse impinging on a mud seafloor will be mostly absorbed with only a small percentage returning to the receiver. But a rock bottom will absorb very little sound and return most of it. In this way, modern seafloor survey systems measure relative strength of signal return as well as the depth. The record that results consists of a pattern of variable strength signal returns that illustrate the seafloor’s composition.
An alternative method of mapping the texture of the seafloor is provided by a “sidescan sonar” system. These systems are towed on cables, and send and receive sound signals over a broad swath of seafloor. The sonar arrays are positioned in such as way that they project sound at low angles. The resulting record can detect very subtle features by the acoustic “shadows” that are cast. Depending on the pitch of the system (low pitch sound travels farthest), sidescan sonar can cover hundreds of meters to kilometers of seafloor.
Using a sonar array mounted on the hull of a research vessel to map the seafloor has advantages. The vessel can travel at about 10 knots (~18.5 km/hr). It is very stable, and the data is generated in near real time and can be processed into useable maps very quickly. However, as the water depth increases, the “footprint” of the beams generated by the sonar become larger, similar to the spreading out of the beam of a flashlight with distance. Because the sonar averages the echo return across each beam to generate a depth point, the spreading out of the beams decreases the resolution of the resulting map. With increasing depth, there is an another limitation as well. The higher frequency sound needed to generate very accurate maps increasingly loses energy (“attenuates”) as it passes through more and more water.

The MR1 towed a long-range sidescan sonar system
 
The MR1 towed long-range sidescan sonar system, which will be used to map the submarine volcanoes in the Marianas arc. Image courtesy of Hawaii Mapping Research Group. For more information about the MR1 system.
 


During the Submarine Ring of Fire project in 2003, we will be using a towed long-range sidescan sonar system called MR1 to map the submarine volcanoes in the Marianas arc. The MR1 sonar will be towed behind the ship at a depth of about 100 meters, while the ship travels forward at 9 knots. The MR1 data will help us understand the recent history of each volcano by revealing lava flows, landslides, and faults. MR1 is operated by the Hawaii Mapping Research Group at the University of Hawaii. While we are surveying with MR1, we will also be collecting bathymetric data with the R/V Thompson's EM300 multibeam sonar system. This bathymetry will show the shape and depth of each surveyed submarine volcano. It will be very important for conducting our CTD/plume-mapping operations this year and will help us plan our remotely operated vehicle dives to some of these volcanoes next year.

http://oceanexplorer.noaa.gov/explorations/03fire/background/mapping/mapping.html

Monday, July 22, 2013

Picturing science: Mapping the moon

Picturing science: Mapping the moon

Posted by 
Tuesday 11 June 2013 08.25 BST
 
A reproduction of a lunar map by H. Percy Wilkins, a "proto-Patrick Moore", is on display at the National Maritime Museum. It makes an interesting side-show to the new major exhibition, Visions of the Universe
Map of the Moon by H. Percy Wilkins
A sheet from the 1951 edition of H. Percy Wilkins' Map of the Moon. Source: National Maritime Museum
Given my recurring Picturing Science posts in this blog, I can't avoid mentioning the new exhibition that has opened at the National Maritime Museum, Visions of the Universe. (Full disclosure: I have not been involved with this exhibition at all.) It has been getting some really nice reviews and previews, and anyone with an interest in astronomy or photography should make the trip.
In this post, though, I want to highlight something else that is currently on view, within the main (free) museum. While the exhibition showcases what the space age has brought us, with extraordinary Hubble-type images and – the real hit, I think – a 13-metre long Mars Window, this other display offers the clearest possible reminder of how recently it is that any of this became possible.
Visions of the Universe exhibition at the National Maritime Museum Visions of the Universe: the new exhibition at the National Maritime Museum. Source: National Maritime Museum
In the NMM's Compass Lounge (at the rear left of the Museum's new entrance foyer), the several sheets of a 1951 map of the moon have been photographed and reproduced to show the complete 300-inch chart. It shows an extraordinary level of hand-drawn detail, achieved by its maker, H. Percy Wilkins (1896-1960), with the aid of distinctly earth-bound telescopes.
This map, versions of which he had been working on since the 1920s, was the largest-scale and most detailed of its time, combining Wilkins' personal observations with data from the drawings, photographs and measurements of other astronomers. As his Wikipedia entry says, it was "considered by some as the culmination of the art of selenography prior to the space age". Wilkins himself described it as "the World's greatest Moon Map".
The map was also, perhaps, one of the last productions of its kind. Not only was it published just on the cusp of the space age, but it was also the project of an amateur, working from his home near Bexleyheath with a 12½-inch, and later a 15½-inch, reflector. Wilkins did the work in his spare time, being employed first as a mechanical engineer and then a civil servant at the Ministry of Supply.
Title page of Wilkins' Map of the Moon The title page of Wilkins' Map of the Moon. Source: National Maritime Museum
Wilkins nevertheless found time to make telescopes, publish several works on popular astronomy and act as director of the British Astronomical Association's Lunar Section. As well as founding the Section's periodical The Moon, he was also, late in life, the first president of the International Lunar Society.
Two of Wilkins' books were co-authored with another selenographic authority, Patrick Moore, to whom the Visions of the Universe exhibition is dedicated. I found online a reminiscence of Wilkins by an acquaintance describing him as a "proto-Patrick Moore", but he was perhaps also a direct inspiration. In an obituary of his colleague, Moore wrote of the "prodigious amount of work" that went into the mapping project but, also, that "his personal enthusiasm was inspiring". Moore felt a "deep sense of personal loss".
Wilkins did not quite become the media star that Moore did, but he made "numerous broadcasts and television appearances". You can, for example, see him (his telescope, his map, and his daughter) here in a 1953 Pathé newsreel. Somewhat more infamously, he made the news in 1954 when he announced his observation of "the most extraordinary feature known on the moon today".
This was a curved shadow, already spotted and described as bridge-like by an American astronomer, John J. O'Neill. It was reported as a 20-mile arch, which can be seen clearly in the photographs reproduced in one of the newspaper reports, viewable at the bottom of the page here. It was, however, no more than a trick of the light, rather like the Face on Mars.
The episode seems to have damaged his credibility considerable and may be one of the reasons that he is less than well-remembered today. Part of the problem was that Wilkins spoke to the press and on the radio before submitting his, rather more cautious, observations to peer scrutiny, His case was not aided by his initially appearing to hint that the structure could be evidence of life on the moon: phrases like "looks artificial" and "almost like an engineering job" led some to leap to such conclusions, even if they were simply descriptive.
The "bridge" was not included in Wilkins' map, although it did incorporate some other erroneous details. Nevertheless, NASA purchased at least one, and possibly several, copies of the reduced reproduction of his lunar chart when preparing for the Apollo moon landings. His map was also used to help match up the first photographs of the far side of the moon, produced by a Lunar 3 in 1959, with features visible from Earth.
As well as the originals of three editions of the maps themselves, the Museum also received a number of notebooks, all kindly donated by Wilkins' daughter. The notebooks include formulae, photographs, newspaper cuttings, original drawings and observational notes, from Wilkins' Kentish observatory and visits to professional observatories in France and the US. They are testament to his years of dedicated work.
When you go (as you must) to see the images, the ingenuity and the leaps that have been made in professional and amateur astronomical imaging on display in the major exhibition, do also remember to pop over to see "the World's greatest Moon Map".

Navigating 18th-century science: Board of Longitude archive digitised

Navigating 18th-century science: Board of Longitude archive digitised

Posted by     Thursday 18 July 2013 07.47 BST

Today the complete archive of the Board of Longitude is being launched online, with stories of innovation, exploration and endeavour - and much more than just John Harrison
Design for a marine chair
Design for a marine chair submitted to the Board of Longitude. Source: Cambridge University Library
Today Lord Rees will be launching the digitised archive of the Board of Longitude at Cambridge University Library. Stuffed full of the correspondence and work of those who preceded him as Astronomer Royal, it also contains letters and papers of artisans, inventors, expeditionary astronomers and maritime explorers.
For those not familiar with the story of the 18th-century search for a means to determine longitude at sea, this video, gives an introduction to the project and the story.
  
From Cambridge University Library and the National Maritime Museum
The digitisation project is a collaboration between CUL and the National Maritime Museum, funded by JISC, and is closely allied to an AHRC-funded project on the history of the Board of Longitude that brings together researchers from the NMM and History and Philosophy of Science department in Cambridge.
This association has meant that as well as digitising 48,596 pages from the archives and libraries at Cambridge and NMM, the content is supported by links to relevant object records at the Museum, summaries of all and transcriptions of some of the files and essays on key figures, places, institutions, objects and events.
Written by the project researchers, there is enough text there for a couple of PhDs (at least) and a really useful resource for users of the site. I was the laggard who has only contributed one essay so far, on Astronomer Royal Nevil Maskelyne. He was, though, an extremely significant figure both for the longitude story and in this project, which also includes selections from Maskelyne's archive from the Royal Observatory and his personal papers held now at the NMM.
While historical researchers will undoubtedly find many ways to start digging into the archive, for those newer to the game there are, on top of the summaries and essays, resources for schools and some selected stories lifted from the archive. The content can take the reader to the observatory at Greenwich, meetings at the Admiralty, artisan workshops of London and the South Seas.
William Wales' map of Easter Island, from Cook's Second Voyage William Wales' map of Easter Island, from Cook's Second Voyage. Source: Cambridge University Library
Key Stage 2 pupils will, we hope, learn about Captain Cook's voyages and Key Stage 3 will be able to think about inventors and enterprise.
For those who feel they are familiar with the story of longitude, having read about John Harrison and his sea clocks in Dava Sobel's Longitude, they will find there is much more to explore. As my NMM colleague, Richard Dunn says,
The archive places the familiar story of Harrison in its richer context. He was a crucial figure but the story is much broader. It takes in the development of astronomy, exploration and technological innovation and creativity during the period of the Industrial Revolution, the work of the first government body devoted to scientific matters, and public reactions to a challenge many considered hopeless.
Simon Schaffer, who leads the research project, adds that
The longitude story is a spectacular example of expert disagreement and public participation. As well as attracting the greatest scientific minds of the day, the board enticed people who belong to one of the most important traditions in British society; the extreme eccentric.
Thus while there may be interest in reading the full story of the Board's dealings with Harrison, eyes are likely to be caught by what were damned by the archive's 19th-century compilers as "Impractical schemes". Some of these are real green ink stuff, with perpetual motion and squaring the circle bound into the seemingly intractable problem of finding longitude.
Scheme for dead reckoning Proposal for finding longitude by determining the ship's rate of sailing. Source: Cambridge University Library
However, there are many other schemes that, while they did not come to fruition, were based on sound ideas. These included improvements to dead reckoning - the educated estimate of position that was not displaced by chronometers until the 20th century - or ways to steady an observer sufficiently to allow them to use Jupiter's satellites as a celestial timekeeper (the standard means of determining longitude on land).
In its later life, the Board supported the two successful methods of finding longitude at sea - chronometer and lunar distance - and broadened its remit into other fields. Thus those who explore the digital archive will also land on geomagnetic research, pendulum experiments measuring gravity, the search for the North-West Passage and a young Michael Faraday pulled in to investigate ways to improve optical glass.
 

Wednesday, July 10, 2013

While Exporting from SDE, "Null Geometry" attack!

During exporting layers from SDE Database (ArcMap 10.1 SP1 for desktop (Build 3143)), to local file geodatabase, the records were exported fine (as I checked the tables) but on the map most of the points didn't appear, for some points are loosing the geometry.
The original layer appears normally on the ArcCatalog, but when exported the error happens.

- Check geometry tool results "null geometry” for the vanished points, "Repair Geometry" didn't solve it.
- Copying Features to a new layer on ArcMap, it copies the features with geometry & deletes the "null geometry".
- Copying the Layer to new file geodatabase (Copy/Paste) gave same error.
- Exporting to Shapefile also gave same error.
- Using XML Export/Import didn't manage the error.

I'm sure there is something related to database, or versioning.
Any suggestions?
Thanks




I got this info from ESRI Support:
Export the SDE layers as XML file, and import that XML file to the local file geodatabase.
Also please make sure you are not falling under following category.
http://support.esri.com/en/knowledgebase/techarticles/detail/41119

Technical Article   Bug:  NIM090672: Specific Microsoft updates may result in data corruption with file geodatabases or shapefiles created on a network share

Article ID:41119
Bug Id:NIM090672
Software: ArcGIS - ArcEditor 9.3.1, 10 ArcGIS - ArcInfo 9.3.1, 10 ArcGIS - ArcView 9.3.1, 10 ArcGIS for Desktop Advanced10.1 ArcGIS for Desktop Standard 10.1 ArcGIS for Desktop Basic 10.1
Platforms: Windows Windows 7, Server 2008 R2

Description

A recent Microsoft update (deployed as KB 2732673, KB 2775511, or KB 2824408) may result in data corruption when using ArcGIS on a Windows 7 system and writing data to remote data storage on a Windows Vista, Windows 7, or a Windows Server 2008/2008 R2 or 2012 system. This data corruption appears as truncation of a write request and has shown up in file geodatabases and shapefiles. 

Additional Information 

An error message referencing the ItemType appears when creating new datasets or items (tables, feature classes, feature datasets, raster datasets, and so forth) in a 10.x file geodatabase created on a network share. 

For example, the following message is displayed when creating a new feature class: 

"Failed to create feature class. 
The item was not found. [ItemType: 
{70737809-852C-4A03-9E22-2CECEA5B9BFA}]" 

File geodatabases created with ArcGIS 9.3.1 return the following error when creating new datasets or items, renaming the file geodatabase, or accessing the geodatabase properties. 

"Failed to connect to database. 
This release of the Geodatabase is either invalid or out of data. [Invalid Geodatabase release]"


Cause

Microsoft has acknowledged the problem, identified the affected component as RDBSS.sys, and provided further details in this Windows SDK Support Team Blog. 

Esri and Microsoft are working closely to understand what has changed in the RDBSS.sys component and how to resolve the problem. 

How Microsoft made these updates available 

KB 2732673 and KB 2824408 are hotfixes to address specific issues. The KB 2775511 update is a cumulative update that is available exclusively through the Windows Update Catalog. 

Because this update is available only through the Windows Update Catalog, the KB 2775511 update is not considered a security update by Microsoft and is not being deployed broadly.


Workaround

• If the patches listed above have not yet been installed, do not install them, per Microsoft's recommendation. 
• If the patches listed above have been installed, Microsoft recommends uninstalling them until a solution is found. 
• Create the file geodatabase or shapefile locally before copying it to the network share. Feature classes can then be created in the file geodatabase on the network share. Note that this is not applicable for raster datasets, attempting to create a raster dataset in the file geodatabase fails on the network share. 
• Create and work with file geodatabases locally. 

Additional Information and Updates 

• June 27, 2013: Microsoft posted an update today on their Windows SDK Support Team Blog. The update states "The hotfix is currently still under development with the update being in testing. The update is on track to be released within the next 60 days (August 2013)." 
• May 22, 2013: Microsoft is in regular communication with Esri and continues to have dedicated development staff working on the issue. A fix has not yet been identified. 
• May 13, 2013: Microsoft has isolated the cause of this issue to an RDBSS.SYS component that was updated by a specific hotfix which is included as part of the Microsoft hotfix rollup KB 2775511. Additional information, including possible workarounds, can be found in this Microsoft Windows SDK Support Team Blog. 
Esri and Microsoft continue to look for a solution to this issue. 
• May 13, 2013: We have confirmed that the same issue occurs when working with shapefiles and results in an error message such as: 
"Error opening feature class 
Number of shapes does not match the number of table records". 
• May 10, 2013: The specific Microsoft hotfix that exposed this issue has been identified. Esri and Microsoft are continuing to dedicate staff full-time to research the cause and provide a resolution as quickly as possible. 
• May 6, 2013: Esri and Microsoft continue to work on this issue with dedicated full-time staff who are in regular, daily communication. These groups are currently working together with a simplified reproducible case. 
• Our testing indicates that the behavior is reproducible with network shares created on Windows systems using the SMB 2.1 and SMB 3.0 protocols. 
• Network shares created on Windows XP (SMB 1.0) and Windows Server 2008 (SMB 2.0) do not encounter this issue. 
• The behavior is encountered when using a network share created on Windows 7 and Windows Server 2008 R2 machines. 
• The issue is also not reproducible when the file geodatabase is created using the file geodatabase API. 
Please contact Esri Support if other behaviors are noticed with new or existing file geodatabases after installing this specific Microsoft rollup.

Sunday, February 3, 2013

Where do smokers live?

Where do smokers live?

By Pam Allison on January 28th, 2013 |                     
According to the American Lung Association, tobacco-caused disease kills more than 392,000 people every year in the U.S., making it the leading cause of preventable death. Another 50,000 people die from exposure to secondhand smoke. The association also notes that in 2004, smoking cost the U.S. more than $193 billion, including $97 billion in lost productivity and $96 billion in direct health care expenditures, or an average of $4,260 per adult smoker. With the implementation of the Patient Protection and Affordable Care Act, states are beginning to address the implications of this important issue.
For example, concerned about projected increases of health care costs, particularly for smokers, Oklahoma State Sen. David Holt, a Republican, is proposing legislation that allows employers to fire cigarette smokers. Current state laws prohibit employers from discriminating against smokers. Holt believes that if people are concerned about losing their jobs, they will stop smoking. He also believes the law will increase productivity and reduce health care costs for people who no longer smoke.
Demographics of U.S. smokers
The CDC claims that in 2010, 19% of all U.S. adults smoked, most of whom smoke less than one pack a day. Where are they? Smokers live in all parts of the U.S. According to Esri, a geographic information systems company, people who smoke less than six packs of cigarettes a week are most likely to live in the Southern and Western U.S. and in Southern Texas.
Click on image to enlarge map.
Click on image to enlarge map.
People who smoke nine or more packs of cigarettes a week are most likely to live in the South.
Click on image to enlarge map.
Click on image to enlarge map.
What type of American is likely to smoke? What type of neighborhoods do they live in? Esri developed the Tapestry Segmentation system that classifies U.S. residential neighborhoods into 65 unique market segments based on socioeconomic and demographic characteristics.
The type of American who likely smokes less than six packs of cigarettes per week is much different from those who might smoke more than nine packs of cigarettes per week. The primary difference is the location of their neighborhoods — urban versus rural.
Residents of City Commons and Urban Rows neighborhoods are twice as likely as the average American to smoke less than six packs of cigarettes a week. City Commons neighborhoods are found primarily in large Southern and Midwestern metropolitan areas. Residents of these neighborhoods are young, single or single parents, live in high-rise apartment buildings, and may be unemployed or work part-time. Urban Rows neighborhoods are found primarily in large Northeastern port cities, with smaller concentrations in the South. Residents are often part of multigenerational households and live in row houses typically built before 1950.
Conversely, residents of Home Town, Rural Bypasses, and Southern Satellites neighborhoods are twice as likely as the average American to smoke nine or more packs of cigarettes a week. Home Town neighborhoods are a mix of singles and families. Residents of these settled, low-density communities are content to stay close to home, so their neighborhoods rarely change. Rural Bypasses neighborhoods are in small Southern towns along back country roads near open space, undeveloped land and farms. Located in the rural South, most of the households in Southern Satellites neighborhoods are comprised of married-couple families. They work in the manufacturing and service industries.
Oklahoma smokers
Holt’s bill is just for the state of Oklahoma. Where do smokers live in the state? If the bill passes, where would businesses and residents be affected the most? Smokers in neighborhoods around larger cities such as Tulsa and Oklahoma City might smoke fewer than six packs of cigarettes a week. Tapestry segments in many of these neighborhoods are City Commons and Modest Income Homes.
Click on image to enlarge map.
Click on image to enlarge map.
Residents of Oklahoma who smoke nine or more packs of cigarettes a week most likely live in rural areas in the eastern part of the state. Tapestry Segmentation classifies many of these neighborhoods as Rural Bypasses, Southern Satellites and Home Town.
Click on image to enlarge map.
Click on image to enlarge map.
Why does this matter?
Knowing where smokers live can help states to target non-smoking campaigns to people who need them the most. While it is unknown whether the proposed legislation will pass in Oklahoma, the desire to decrease smoking is a legitimate concern for all states and government-funded health care programs. Many smoke-related health problems are preventable when people stop smoking, lowering their smoke-related health care costs.
More information about Esri’s data can be found at www.esri.com/data, or to learn more about Esri in general, go to www.esri.com.
Pam Allison is a digital media, marketing strategist and location intelligence consultant. You can visit her blog at www.pamallison.com.

Saturday, February 2, 2013

Installing a new ESRI extension Failture (Registration Failed)

 Installing a new ESRI extension Failture (Registration Failed)

 
This error appear when installing a new extension on ArcGIS desktop environment 10.x.
To fix run as Administrator. 
 
 
If you are running ESRIRegAsm.exe manually, run the Command prompt (cmd) as administrator.

Executing tools in ModelBuilder

Executing tools in ModelBuilder
This tutorial takes you step-by-step through creating a model and executing tools in ModelBuilder. You start by adding a tool to ModelBuilder and supplying values for the tool's parameters. This constructs a process. A model is built by connecting processes.
This tutorial builds a very simple model that identifies the vegetation types near proposed roads. In the model, the roads are first buffered using values from a distance field in the roads attribute table. The output from the Buffer tool is used to clip the vegetation data to create a dataset of vegetation types within the buffer polygons.
The tutorial is composed of six broad steps:

Steps:
  1. Copy tutorial data
  2. Open the map document
  3. Create a new model
  4. Add tools and data to the model
  5. Fill in the tool parameters
  6. Run the model
  7. Save the model

1—Copying tutorial data

It is assumed that you have installed ArcGIS Desktop (ArcView, ArcEditor, or ArcInfo) before you begin this tutorial. The data required for this tutorial (included on the ArcGIS Desktop CD) by default is installed in C:\arcgis\ArcTutor. The tutorial scenario is fictitious, and the original data has been adapted for the tutorial.

Steps:
  1. To avoid corrupting the original data, copy the ModelBuilder folder from C:\arcgis\ArcTutor to the C drive on your computer. If you are copying the data to another drive or location, make sure to use that location for all the steps below.

2—Opening the map document

Browse to the C:\ModelBuilder folder in Windows Explorer and double click the Extract Vegetation.mxd. This will start ArcMap and open the map document, or

Steps:
  1. Start ArcMap by clicking Start > All Programs > ArcGIS > ArcMap 10.
  2. On the ArcMap - Getting Started dialog box, click Existing Maps > Browse for more.
    The Open ArcMap Document dialog box appears.
  3. Browse to C:\ModelBuilder folder, select Extract Vegetation.mxd, and click Open.
    This opens the Extract Vegetation.mxd.

3—Creating a new model

Steps:
  1. Click the ModelBuilder button ModelBuilder Window on the ArcMap Standard toolbar.
    This opens the ModelBuilder window for editing.
  2. You can also create a new model by right-clicking an existing toolbox and choosing New > Model. This creates a model in the toolbox with a default name and opens the model for editing.

4—Adding tools and data to a model

Now that the model is open for editing, you will add two tools using the Search window:

Steps:
  1. In ArcMap, click Geoprocessing > Search For Tools.
    This opens a Search window that you can dock anywhere in ArcMap.
    Opening Search window

  2. On the Search window, type Buffer, then click the Search button Search.
    The Buffer tool is listed along with other search items.
  3. Drag the search item Buffer (Analysis) (which represents the Buffer tool found in the Analysis toolbox) onto the ModelBuilder canvas in the white space.
    Adding tools from Search
    This adds the tool and the output data variable to the model. The output variable is connected to the tool by a connector. Both the tool and output data are empty (without color) as none of the tool parameters have been supplied.
  4. Search for and add the Clip tool in the Analysis toolbox in a similar manner. If the two tools overlap, click the Auto Layout button Auto Layout on the ModelBuilder toolbar to arrange the tools.
    Adding the Clip tool
  5. There are two other methods to add tools in a model that are not used in this tutorial, but have been listed to introduce you to them:
    • In the Catalog window, navigate to Toolboxes > System Toolboxes > Analysis Tools > Proximity. You can select Buffer and drag the tool onto the ModelBuilder canvas in the white space.
    • On the ModelBuilder Standard toolbar you can click the Add Data or Tool button Add Data or Tools, and navigate to Toolboxes > System Toolboxes > Analysis Tools > Proximity. Select the Buffer tool and click Add.

5—Filling in tool parameters

Now that the tools are added to the model, you will fill in the tool parameters.

Steps:
  1. In ModelBuilder, double-click the Buffer tool to open its tool dialog box.
  2. For the Input Features parameter, click the browse button Browse and navigate to the input geodatabase (C:\ModelBuilder\ToolData\Input.gdb).
  3. Choose the PlanA_Roads feature class and click Add.
  4. Once you fill in the input features, the Output Feature Class parameter is automatically generated and filled in for you. Replace this autogenerated output name by clicking the Browse button Browse for the Output Feature Class parameter. Navigate to the output geodatabase in the ModelBuilder folder (C:\ModelBuilder\Scratch\Output.gdb), type BufferedFC for the output name, then click Save.
  5. For the Distance parameter, choose the Field option and choose the Distance field from the drop-down list.
  6. Click OK. (You don't need to fill in any other parameters.)
    Filling in Buffer tool parameters
    The input data is added as a variable to the model (the blue oval in the above illustration) and is automatically connected to the Buffer. The input variable (the blue oval), the tool (the yellow rectangle), and the output variable (the green oval) change colors to indicate that all parameter values have been supplied and the tool is ready to run. Note that clicking OK on the tool dialog box does not execute the tool in ModelBuilder.
    When data or tools are added to a model, they are referred to as model elements. There are three basic types of elements: variables (such as datasets), tools, and connectors.
  7. Now double-click Clip to open its tool dialog box.
  8. For the Input Features parameter, click the Browse button Browse and navigate to the input geodatabase (C:\ModelBuilder\ToolData\Input.gdb).
  9. Choose the vegtype feature class and click Add.
  10. For the Clip Feature parameter, click the arrow and choose BufferedFC from the drop down list. The blue recycle symbol Model variable means that BufferedFC is a variable in the model. This variable was created in the model when you added the Buffer tool.
  11. Click the browse button Browse for the Output Feature Class parameter, navigate to the output geodatabase (C:\ModelBuilder\Scratch\Output.gdb), type ClippedFC for the dataset name, then click Save.
  12. Click OK on the Clip tool dialog box.
    The output variable of the Buffer tool is automatically connected (using a connector) as an input to Clip, as illustrated below.
    Filling in Clip tool parameters

6—Running the model

After all the parameters of the tools have been filled in, the model is ready to run.

Steps:
  1. Before you run the model, select the ClippedFC variable, right-click, then click the Add To Display option. Setting this option ensures that when the model is run from ModelBuilder, the output ClippedFC will be added to the display in ArcMap for quick viewing of the results.
  2. From the ModelBuilder menu, click Model > Run Entire Model.
    The model runs and the output is added to the display. After the model has finished running, both the tools (the yellow rectangles) and output variables (the green ovals) show a drop shadow around them indicating that these tools have been run.

Running the model on different roads

To run the model on different roads (such as PlanB or PlanC feature classes), you have two choices:
  1. Double-click Buffer and navigate to another feature class, or
  2. Drag the data from the Catalog window onto the ModelBuilder canvas to create a new data variable, then connect this variable to Buffer. Follow the steps below to see how this works.

Steps:
  1. On the ArcMap menu, select Geoprocessing > Geoprocessing Options.
    1. Ensure that the check box next to When connecting elements, display valid parameters when more than one is available is checked.
    2. Click OK.
  2. Navigate to the input geodatabase in the Catalog window.
  3. Choose the PlanB_Roads feature class and drag it onto the ModelBuilder canvas.
  4. Click the Connect button Add Connection, then do the following:
    1. Click the PlanB_Roads variable element.
    2. Click the Buffer tool element. A shortcut menu appears containing the choices of available parameters for the tool.
    3. Choose the Input Features parameter from the list.
    This connects the PlanB_Roads variable to Buffer and automatically disconnects the PlanA_Roads variable that was previously connected to the tool. The model elements lose their drop shadow, signifying that the model has not been run with the new variable you added.
  5. Double-click Buffer and choose the correct distance field from the PlanB_Roads feature class.
  6. Run the model with Model > Run Entire Model.
    The model runs and the output is added to the display. After the model has finished running, both the tools and output variables show a drop shadow around them indicating that these tools have been run. The existing output ClippedFC layer (from the previous run with PlanA_Roads) in the ArcMap table of contents is updated with the results from PlanB_Roads.

7—Saving a model

Saving is the last step for this tutorial. You will use the saved model in the Creating tools with ModelBuilder tutorial.

Steps:
  1. Click the Save tool Save on the ModelBuilder toolbar and navigate to C:\ModelBuilder.
  2. A model can only be saved in a toolbox. Click the New Toolbox icon New Toolbox on the navigation window.
    A toolbox with a default name is added in the workspace.
  3. Change the name to MyTools.tbx.
    Saving a model
  4. Select MyTools.tbx and click Save to save the model with the default name (Model).

Additional analysis

If you want to do some analysis with the model, you can add the Summary Statistics tool to get a summary table of affected area by vegetation type within the buffer polygons around the proposed roads.

Steps:
  1. Use PlanA_Roads as input in the Buffer tool for this analysis.
  2. Find the Summary Statistics tool in the Search window.
  3. Drag the tool into the model.
  4. Double-click the Summary Statistics element to open the tool dialog box.
  5. For the Input Table parameter, click the arrow and choose ClippedFC with a blue recycle icon Model Variable next to it from the drop down list. This recycle icon means it is a variable in the model.
  6. For the Output Table parameter, browse to the output geodatabase (C:\ModelBuilder\Scratch\Output.gdb), type AffectedVegetation for the name, then click Save.
  7. For the Statistic Field(s) parameter, choose Shape_Area from the list.
  8. Click the cell next to Shape_Area under Statistic Type and choose SUM from the drop down list.
  9. For the Case field parameter, choose VEG_TYPE from the list.
    The completed Summary Statistics dialog box is illustrated below.
    Using Summary Statistics tool
  10. Click OK.
  11. Confirm that the Add to Display option is checked for ClippedFC by right clicking it.
  12. Right click and check the Add to Display option for the AffectedVegetation variable. This will add the ouput to the display after the model runs.
  13. Run the model.
    The output ClippedFC and the AffectedVagetation table is added to display in the ArcMap table of contents.
  14. Open the table by right-clicking and clicking Open.
    The table shows a summary of area by vegetation type within the buffer polygons that will be affected by the proposed roads for plan A.


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