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Soil Data Join Recorrelation Initiative • Overview and Background – Purpose, Issues, Objectives, Initiative • Advisory Team / Technical Team • National Instruction Highlights • Reportable Measures • FY12 and Beyond Overview and Background • Chief’s decision memo regarding NASIS – Improve the database – Accelerate MLRA approach by re-correlating data joins (harmonization) – Accelerate Phase 1 of MLRA update – Goal is seamless soil survey data Soil Data Join Recorrelation (SDJR) (a.k.a. Harmonization) What is it? • Effort to provide seamless soil survey information in a timely fashion • Correlation and data enhancement using legacy soils data to provide seamless soils data • One data mapunit or consistent properties correlated to geographically consistent map units • Same named • Similar named • Uniquely named SDJR Why now? • It has been a SSD Director priority for at least 2 years • With the completion of SSURGO many added value products are being generated • We need to provide consistent data for USDA programs • If we don’t do this, others (non-soil scientists) will make changes to make data consistent • We have enough data to make decisions for many instances National Soil Survey Database Harmonization Project Why now? • Allows for SSOs and MOs to do a thorough analysis of all their data • Through this analysis long range and yearly plans, and projects can be developed and prioritized • Using Benchmark Soils, we can harmonize/make consistent a large percentage of our data Division Priority • FY- 2012 Soils Division Priorities – Begin a multi-year initiative to complete Soil Survey Data Join Re-correlation (often referred to as harmonization) so that soils information matches from county to county and state to state on 1 billion acres Division Director Charge: • Establish Advisory and Technical teams to look at accelerating Phase I (data harmonization) of MLRA updates – Provide advice for implementation – Develop objectives, goals, and direction Advisory Team • Cameron Loerch • Tom Weber • Ken Scheffe • Cleveland Watts • Paul Finnell • Dennis Williamson • Jon Gerken • Roy Vick • Dave Hoover • Jerry Schaar • Amanda Moore • Steve Park • Mike Domeier Technical Team 1. Thorson, Thor - NRCS, Portland, OR 2. Tallyn, Ed - NRCS, Davis, CA 3. Fisher, John – NRCS, Reno, NV 4. Mueller, Eva- NRCS, Bozeman, MT •Paul Finnell, NSSC 5. Wehmueller, William - NRCS, Salina, KS •Ken Scheffe, NSSC •Cathy Seybold, NSSC 6. Hahn, Thomas - NRCS, Denver, CO •Steve Monteith, NSSC 7. Ulmer, Mike - NRCS, Bismarck, ND •Zamir Libohova, NSSC 8. Glover, Leslie - NRCS, Phoenix, AZ •Deb Harms, NSSC 9. Gordon, James - NRCS, Temple, TX •Steve Peaslee, NSSC 10. Whited, Michael - NRCS, St. Paul, MN •Sub-Committees 11. Endres, Tonie - NRCS, Indianapolis, IN •Database 12. Finn, Shawn - NRCS, Amherst, MA •Climate 13. Dave Kingsbury - MOL, WV •GIS 14. Anderson, Debbie - NRCS, Raleigh, NC •Correlation 15. Anderson, Scott - NRCS, Auburn, AL •Interpretations •ESD 16. Mersiovsky, Edgar - NRCS, Little Rock, AR •Lab Data 17. Mark Clark – MO Leader, AK 18. David Gehring - NRCS, Lexington, KY What are the issues? What are the issues? • K factors are one interpretation dependent on texture that are dependent on map unit concept What are the issues? • Same map unit name, different composition What are the issues? Lines join, interpretation s differ Issues: Statewide Interpretations Issues: Nationwide Soil Property Data Users 2.33 0.02 Bulk Density, 5-20 cm (Mg m-3) What are the issues? MLRA 75-Crete sil, 0-1% Dwellings with Basements Before Expectation of consistent interpretations: After Basic Objectives - SDJR • Support the development of seamless soils data for use with CDSI, USDA Farm Bill Programs, and added value SSURGO products • Process resulting in correlation of similar data map units taking into account existing legacy data, laboratory data, and expert knowledge Basic Objectives - SDJR • Dissolve the perceived data faults in interpretations visible in geospatial presentation of soil survey information Often resulting from minor variation in data population, horizon depths, composition, and vintage of guidance documents Basic Objectives - SDJR • Improve the database • Reduces the number of DMU’s for same and similarly named soil map units • Identify priority update needs • Builds the foundation for next generation of soil survey – disaggregation National Instruction https://nrcs.sc.egov.usda.gov/ssra/nssc/default.aspx National Instruction Highlights • Conducted NASIS through a review Soil Expert of existing data: Knowledge Survey Reports • Map Unit Concept and Composition GIS Correlation Products Documents Published Research & Lab Data Documents National Instruction Highlights • Focus on Same and Similarly named map units Prioritize with Initial List of MU’s Consider Benchmark Soils Consider Priority Landscapes • Integrating Uniquely Named Map Units – SRSS/SDQS additional ideas to utilize SDJR approach National Instruction Highlights • Creating SDJR Projects in NASIS SDJR Project Milestones • Create spatial distribution maps • Compile historical data • Populate correlated map units into SDJR project • Enter pedons in NASIS • Review historical MU/DMUs • Create and populate the new MLRA MU/DMU • Document the MLRA MU/DMU • Identify/propose future field projects • Update OSD and lab characterization data • Quality control completed • Quality assurance completed • Correlation activities completed • SSURGO certification National Instruction Highlights • Harmonized Soil Data is: Linked to Same DMU Major and Meets Data Minor Soils Completeness Populated Standards Components Total 100% National Instruction Highlights • Lab data reviewed – The pedons will be reviewed and updated – Updating the correlated name and correlated classification for sampled pedons • OSD reviewed and updated; – Classification updated to current taxonomy if necessary – Other updates to the OSD will follow the standard operating procedures for the MLRA regional office National Instruction Highlights • Legacy Data Populated and Archived – Published manuscript TUD’s – Pedon data • ESD’s – Component productivity – Component ecological site – Work with ecological site inventory specialist and local rangeland management specialist • Map unit certified by QA process through MO National Instruction Highlights • Identification of project needs that require future field work and analysis – Document in NASIS as a proposed project • Brief description • Estimated extent – Areas not joining spatially across political boundaries are identified as future projects and documented – Capture ESD inventory and development needs Reportable measure’s • SDJR (Harmonization) projects – 20% of total map unit acreage 20% – Report when QA milestone in project has been completed. – Post to SDM when scheduled (annual) • Initial soils mapping = 100% • MLRA field projects = 100% • High priority extensive revision = 100% FY 2012 – SDJR 3rd Quarter • Training to MLRA SSO’s by MO (Technical Team) 4th Quarter • Develop and work on a project • Test National Instruction • Develop future SDJR projects • Other Priorities (Initial; Agreements; projects) FY 13 and Beyond Fully engaged in SDJR Priorities and goals developed • SSD – MO’s • MLRA Advisory and Management Teams Complete Initial surveys before full implementation. Support from the MO (Technical Team) National Bulletin Summary Improve/enhance/populate database SDJR Reconcile DMU’s for same and similarly named map units Process Identify future project needs Build foundation for next generation Discussion • Questions?
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