Presentation on theme: "Soil Data Join Recorrelation Initiative"— Presentation transcript:
1 Soil Data Join Recorrelation Initiative Overview and BackgroundPurpose, Issues, Objectives, InitiativeAdvisory Team / Technical TeamNational Instruction HighlightsReportable MeasuresFY12 and Beyond
2 Overview and Background Chief’s decision memo regarding NASISImprove the databaseAccelerate MLRA approach by re-correlating data joins (harmonization)Accelerate Phase 1 of MLRA updateGoal is seamless soil survey data
3 Soil Data Join Recorrelation (SDJR) (a.k.a. Harmonization) What is it?Effort to provide seamless soil survey information in a timely fashionCorrelation and data enhancement using legacy soils data to provide seamless soils dataOne data mapunit or consistent properties correlated to geographically consistent map unitsSame namedSimilar namedUniquely named
4 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 generatedWe need to provide consistent data for USDA programsIf we don’t do this, others (non-soil scientists) will make changes to make data consistentWe have enough data to make decisions for many instancesMany soil scientists that have key knowledge for making these decisions will likely be retiring soon
5 National Soil Survey Database Harmonization Project Why now?Allows for SSOs and MOs to do a thorough analysis of all their dataThrough this analysis long range and yearly plans, and projects can be developed and prioritizedUsing Benchmark Soils, we can harmonize/make consistent a large percentage of our data
6 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
7 Division Director Charge: Establish Advisory and Technical teams to look at accelerating Phase I (data harmonization) of MLRA updatesProvide advice for implementationDevelop objectives, goals, and direction
8 Advisory Team Cameron Loerch Tom Weber Ken Scheffe Cleveland Watts Paul FinnellDennis WilliamsonJon GerkenRoy VickDave HooverJerry SchaarAmanda MooreSteve ParkMike Domeier
9 Technical Team Thorson, Thor - NRCS, Portland, OR Tallyn, Ed - NRCS, Davis, CAFisher, John – NRCS, Reno, NVMueller, Eva- NRCS, Bozeman, MTWehmueller, William - NRCS, Salina, KSHahn, Thomas - NRCS, Denver, COUlmer, Mike - NRCS, Bismarck, NDGlover, Leslie - NRCS, Phoenix, AZGordon, James - NRCS, Temple, TXWhited, Michael - NRCS, St. Paul, MNEndres, Tonie - NRCS, Indianapolis, INFinn, Shawn - NRCS, Amherst, MADave Kingsbury - MOL, WVAnderson, Debbie - NRCS, Raleigh, NCAnderson, Scott - NRCS, Auburn, ALMersiovsky, Edgar - NRCS, Little Rock, ARMark Clark – MO Leader, AKDavid Gehring - NRCS, Lexington, KYPaul Finnell, NSSCKen Scheffe, NSSCCathy Seybold, NSSCSteve Monteith, NSSCZamir Libohova, NSSCDeb Harms, NSSCSteve Peaslee, NSSCSub-CommitteesDatabaseClimateGISCorrelationInterpretationsESDLab Data
10 What are the issues?Existing product developed over a time span of 60 years. Naturally incorporating differences due to technology and time.
11 What are the issues?K factors are one interpretation dependent on texture that are dependent on map unit conceptUSDA conservation programs rely on high quality, consistent data for program eligibility and conservation planning.
12 What are the issues? Same map unit name, different composition Same named map units representing the same soil/landscape/veg relationship with differing composition result in inconsistent use and results.
13 What are the issues? Lines join, interpretations differ Surveys that appear to join spatially, have inconsistent interpretations due to minor differences in the horizon thickness and composition data.
14 Issues: Statewide Interpretations There are more and more data needs for broad conservation planning, such as at State Levels. Highlights the need for consistency.
15 Bulk Density, 5-20 cm (Mg m-3) Issues: Nationwide Soil Property Data UsersAlso at a National Level, soil property data is being used in Models and other planning purposes. Again highlighting the needs for complete, consistent data.2.33Bulk Density, 5-20 cm (Mg m-3)0.02
16 Expectation of consistent interpretations: What are the issues?MLRA 75-Crete sil, 0-1%Dwellings with BasementsThis initiative is looking for positive results such as this example.Expectation of consistent interpretations:BeforeAfter
17 Basic Objectives - SDJR Support the development of seamless soils data for use with CDSI, USDA Farm Bill Programs, and added value SSURGO productsProcess resulting in correlation of similar data map units taking into account existing legacy data, laboratory data, and expert knowledge
18 Basic Objectives - SDJR Dissolve the perceived data faults in interpretations visible in geospatial presentation of soil survey informationOften resulting from minor variation in data population, horizon depths, composition, and vintage of guidance documents
19 Basic Objectives - SDJR Improve the databaseReduces the number of DMU’s for same and similarly named soil map unitsIdentify priority update needsBuilds the foundation for next generation of soil survey – disaggregation
20 National Instructionhttps://nrcs.sc.egov.usda.gov/ssra/nssc/default.aspx
21 National Instruction Highlights NASISSoil Survey ReportsCorrelation DocumentsLab DataPublished Research & DocumentsGIS ProductsExpert KnowledgeConducted through a review of existing data:Map Unit Concept and CompositionInitiative focuses on evaluation and review of “existing” data, several reports and tools to access NASIS data, Published survey reports to understand the concept of the map unit and its composition, Review of correlation documents and decisions, Lab Data, any research projects or investigations, tools and products using GIS technologies (climate, geology, DEM, Land cover, STATSGO, ecoregions) to estimate distribution.
22 National Instruction Highlights Focus on Same and Similarly named map unitsIntegrating Uniquely Named Map UnitsSRSS/SDQS additional ideas to utilize SDJR approachPrioritize with Initial List of MU’sConsider Benchmark SoilsConsider Priority Landscapes
23 National Instruction Highlights Creating SDJR Projects in NASISSDJR Project MilestonesCreate spatial distribution mapsCompile historical dataPopulate correlated map units into SDJR projectEnter pedons in NASISReview historical MU/DMUsCreate and populate the new MLRA MU/DMUDocument the MLRA MU/DMUIdentify/propose future field projectsUpdate OSD and lab characterization dataQuality control completedQuality assurance completedCorrelation activities completedSSURGO certification
24 National Instruction Highlights Harmonized Soil Data is:Linked to Same DMUMeets Data Completeness StandardsComponents Total 100%Major and Minor Soils Populated
25 National Instruction Highlights Lab data reviewedThe pedons will be reviewed and updatedUpdating the correlated name and correlated classification for sampled pedonsOSD reviewed and updated;Classification updated to current taxonomy if necessaryOther updates to the OSD will follow the standard operating procedures for the MLRA regional office
26 National Instruction Highlights Legacy Data Populated and ArchivedPublished manuscript TUD’sPedon dataESD’sComponent productivityComponent ecological siteWork with ecological site inventory specialist and local rangeland management specialistMap unit certified by QA process through MO
27 National Instruction Highlights Identification of project needs that require future field work and analysisDocument in NASIS as a proposed projectBrief descriptionEstimated extentAreas not joining spatially across political boundaries are identified as future projects and documentedCapture ESD inventory and development needs
28 Reportable measure’s SDJR (Harmonization) projects 20% of total map unit acreageReport 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%20%
29 FY 2012 – SDJR3rd QuarterTraining to MLRA SSO’s by MO (Technical Team)4th QuarterDevelop and work on a projectTest National InstructionDevelop future SDJR projectsOther Priorities (Initial; Agreements; projects)
30 FY 13 and Beyond Priorities and goals developed Fully engaged in SDJRPriorities and goals developedSSD – MO’sMLRA Advisory and Management TeamsComplete Initial surveys before full implementation.Support from the MO (Technical Team)