Geographic Resource Solutions

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GRS Presentation at IGTF2016 Conference: Ken Stumpf Wants "No Nuts" in His Landsat Imagery

April 15, 2016 - For Immediate Release  -  GRS Starts Petition at Change.org to Reinstate Option to Use Nearest Neighbor Resampling Algorithm During Terrain Correction

Ken Stumpf of Geographic Resource Solutions started his presentation by comparing the Free Landsat Imagery currently available from the EROS Data Center with Free Ice Cream. 

Stumpf said "Imagine you really like ice cream and a new ice cream store opened in your town that advertised FREE ICE CREAM, as much as you can eat."

If you were me, you would say “WOW that’s great,” and go to the ice cream store to get some.

But when you got there and surveyed the menu you found that every flavor of the free ice cream contained NUTS – Lots of NUTS … and you don’t like NUTS!

It turned out that the FREE ICE CREAM was not so great a deal after all.

That’s sort of the problem Stumpf has with this free Landsat imagery being distributed by the EROS Data Center.   What are these "nuts" in the imagery?

Download this presentation which includes notes to see Ken's complete presentation.

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This download reprents the materials that were presented during Workshop #23 presented by Ken Stumpf and Sage Romberg at the IGTF2016 Conference in Fort Worth, Texas on April 11, 2016.

Please contact either Ken or Sage if you have any questions about this material.

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This presentation was made at the Eastern Oregon AgriculturalResearch Center in Burns, OR on December 8, 2015 based on preliminary inventory and mapping efforts by Ken Stumpf and Sage Romberg in the vicinity of Montrose, CO.  Stumpf presents some of the preliminary results that include type (Alliance) level mapping, individual sage and non-sage species mapping, and the development of vegetation/habitat "states" based on the species/landscape-specific attributes that were mapped.

Stumpf discusses the field data that supported the mapping efforts, sample stratification, and the basic components of GRS's Discrete Classification Mapping Methodology that was used to develop the spectral relationships necessary to develop this type of comprehensive natural resource inventory.  Such inventories will be essential tools to future resource management and conservation efforts designed to manage and monitor natural resources like our sagebrush types that are so essential as Sage Grouse habitat.

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This presentation was made at the 2012 ASPRS Conference in Sacramento, CA on March 22, 2012.  Stumpf identifies the problems with using withheld training data in an Accuracy Assessment.  In addition, Stumpf discusses issues concerning potential sampling bias due to poor representation of the Project Area that is being tested, as well as alternate means of populating an Error Matrix to yield more meaningful Accuracy Assessment estimates.

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This presentation was made by Ken Stumpf at the 2012 ASPRS Conference in Sacramento, CA on March 22, 2012.

Ken presents the basic methodology and some of the initial results of this mapping project.  Discussion primarily includes how the Image Classification Map was developed using Discrete Classification, but also includes sample data products in both the raster and vector formats.  The benefits of mapping continuous variables like canopy cover and tree size are shown, as well as differences in query results based upon NVCS types as opposed to species specific cover estimates.  Accuracy Assessment results are presented visually by including Accuracy Assessment information in the map data set table information.

This version of the presentation includes Ken's notes.

Contact Ken Stumpf at GRS for further information.

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This presentation was made by Ken Stumpf at the 2012 ASPRS Conference in Sacramento, CA on March 22, 2012.

Ken presents the basic methodology and some of the initial results of this mapping project. Discussion primarily includes how the Image Classification Map was developed using Discrete Classification, but also includes sample data products in both the raster and vector formats. The benefits of mapping continuous variables like canopy cover and tree size are shown, as well as differences in query results based upon NVCS types as opposed to species specific cover estimates. Accuracy Assessment results are presented visually by including Accuracy Assessment information in the map data set table information.

Contact Ken Stumpf at GRS for further information.

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This download represents a presentation made at the May 2011 American Society of Photogrammetry and Remote Sensing (ASPRS)  Annual Conference in Milwaukie, WI.  It covers the basic design and implementation of the Accuracy Assessment undertaken at Lassen Volcanic National Park during 2008-09.  This assessment was designed to test two different maps (on based on photo-interpretation and the other on image classification) at the same time.  Each map was assessed using a stratified random sample design.  A data set of randomly of 25,000 randomly generated X,Y locations representing candidate accuracy assessment sites was generated.  These sites were spatially related to the map polygons they fell within.  List sampling was implemented by NVCS strata to select individual sample sites within each designated stratum.  Some points sampled only one of the maps while some points sampled both maps.  No points were moved away from boundaries, but the orientation of sample areas was altered in an unbiased systematic fashion so that all sample areas fell within the appropriate sample polygons.  Over 900 sites were visited and over 1000 land cover assessments were made - some sites had dual (different) samples to satisfy the need for independence between the sampling of the two maps.  Examples of list sampling queries and database updates are provided that demonstrate how to apply these techniques.

Contact Ken Stumpf at GRS for additional information.

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Land Cover Mapping in Alaska Based on Satellite Image Classification –Lessons Learned. Presented at the 2011 Alaska Survey and Mapping Conference, Anchorage, Alaska

Ken presents information and examples of spectral confusion encountered during GRS's recent efforts mapping nearly 25-million acres in Alaska. Ken demonstrates such confusion showing mapping examples from three different mapping project of the same area, with each map showing a different result. GRS's solution to resolving this confusion is presented. Ken also discusses GRS's ability to differentiate Black Spruce from White Spruce stands, as well as live healthy White Spruce stands from stands impacted by the Spruce Bark Beetle.

Contact Ken Stumpf at GRS for further information.

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Stumpf, K.A. ''An Image Classification Sampling Methodology based on the Integration of IP/GIS Capabilities.'' A slide presentation that represents GRS's approach to developing image classification training site locations. Images are stratified.  Large homogeneous areas of the same class are identified.  A candidate site database is generated.  Frequency distributions that identify large frequently occurring classes can be distinguished from rare infrequently occurring classes.  Field sampling plans can be developed to represent the diversity of classes across the landscape without oversampling frequently occurring classes.

Initially presented at the 2002 ASPRS Conference in Washington, D.C.; also presented at the 2004 ASPRS Conference, Denver, CO

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This download contains a presentation made by Ken Stumpf at the April 16, 2014 meeting of the Redding Area User Group (RAGU) in Redding, CA.  It describes some of the capabilities of the Discrete Classificaiton Map Data Sets produced by GRS for the Redwood national and State PArks and Lassen Volcanic National Park that were produced by GRS and delivered  in 2013 and 2014 and how these map data sets differ from the typical color-coded map data sets that are standard output for some of our national mapping programs.