Databases in Soil Survey. Objectives Identify databases used for population, analysis, and...

Databases in Soil Survey

Objectives

• Identify databases used for population, analysis, and publication of soils data

• Understand NASIS correlation concepts• Identify correlation procedures to create

fully reversible correlation

Soil Database History

• Pre-1972 – all hand written manuscripts• 1972 – Soil Survey Interpretation Record• 1974 – Manuscript tables computer generated• 1985 – State Soil Survey Database (SSSD)• 1994 – NASIS• 2003 – Staging Server/SDW/SDM/SSURGO• 2005 – Web Soil Survey• 2015 - ????

1974 – SOIL-6 Map Unit RecordUsed to retrieve data for

manuscript development

Maximum of 3 components for

the map unit Horizon layer depth adjusted to match county

TP

SOI-5 + SOI6 = MUIR– Map Unit Information Record - SSSD

Same S5id number for the

same component

used in various map units

Slight variations based on the S-5

Layer ID

NASIS Foundation – notice any differences?

Current Soil ‘Databases’• National Soil Information System (NASIS)

– Pedon PC (access db)– Analysis PC (access db)

• Official Series Descriptions (technically not a database) • Soil Classification Database (SC) • Soil Characterization Database (KSSL) • Soil Data Mart Database (SDM)

– Spatial (shape files)– Staging Server– Soil Data Warehouse– Soil Data Mart– Web Soil Survey (portal)

• SSURGO database (MS Access template)• U.S. General Soil Map (STATSGO)

Soil Correlation and Databases

The first basic correlation decision is made when you decide where to dig a hole that represents the landscape concept and whether to record a complete or partial pedon description or a field note.

Pedon Description

Properties

Interpretations

Lab Data

Properties are collected and inferred from pedon descriptions. Properties are also obtained from laboratory data. The old photos provide evidence that little

has changed over the years in the collection of soil properties.

Spatial Data

National Soil Information System

Product Development

KSSL Data

Pedon Data

Field digitizing

NASISTransactional database

Correlation of Pedon Data

Correlation of Pedon Data

POINT-PLOT texture and MAP

Correlation of Pedon

Data

Correlation of Pedon

DataPOINT-Plot lab data by soil and comp layer NAT

ArcGIS Analysis

• Pedon• Polygons

Soil Properties for Modelers• albedo dry• area name• area symbol• area type name • base saturation• bulk density fifteen bar• bulk density one third bar• bulk density oven dry• caco3clay ratio• calcium carbonate

equivalent• cec nh4oac ph7• clay total separate r• coarse fragment volume• comonth.month• component interp• component restriction• component kind• component name• component percent r• cosoilmoist.soimoiststat• cosoimoistdept l

• drainage class• ecec• fine sand separate• flooding duration class• flooding frequency class• geomorph feat name• geomorph feat type name• horizon depth to bottom r• horizon depth to top r• horizon designation• horizon thickness • hydrologic soil group• kf factor • kw factor• layer depth• linear extensibility percent• map unit symbol• mapunit acres• mapunit name• organic matter percent l, rv, h

• particle density • ph 01m cacl2• ph 1to1 h2o• pore quantity, shape, size• restriction depth to top h• restriction depth to top l• rock frag 3 to 10 in• rock frag > 10• sand coarse separate• sand total separate• sat hydraulic conductivity• sieve number 4• silt total separate• slope l, h• soil texture and modifier• sum of bases• t factor• water fifteen bar r• water one tenth bar• water one third bar• water satiated

Data Management• Point data is captured using PedonPC or NASIS• Soil boundaries are captured or modified• Methods are available to analyze data • The map unit concept is built after data is

collected, compiled, and analyzed • Soil property estimates are developed using the

component population collected for the specific map unit concept

Database Entry

‘a database lives or dies based on the consistency of the data

population’

Run NASIS report: ‘PEDON - Count soil name by state’ as an example. This report attempts to identify the number of pedons captured by county using the user pedon ID.

NASIS Site/Pedon Entry

S2005NE079001 • The User Site/Pedon ID has a specific, national standard, method of

population. The purpose of this field is to allow the user to place a label on the site to assist with locating the particular site record(s) in the national database.

• The national standard for the User Site ID is the “YYYYXXZZZ123” convention,

• where “YYYY” is the 4-digit year when the data or samples were collected; • “XX” is the 2-character state FIPS code such as “NE” for Nebraska (for

non-USA samples, use the abbreviation for the country code); • “ZZZ” is the 3-digit county FIPS code (e.g. 079), and • “123” is the 3-digit consecutive pedon number for that county in that year. • The letter S will preface the User Site ID for soil characterization samples.

.

NASIS Entry

Pedon Analysis Analysis PC is designed to analyze pedons from

NASIS to gather data in building components

Analysis PC• Established relationships among the tables• Built in queries available for use • New queries easily written or imported• Can use access queries or form analysis• Can analyze data in the spatial world• Can be joined with other Access databases

for further analysis

Soil Correlation and Databases

The second correlation decision is where do you draw the boundary and what soils are inside that polygon

Mapping/Correlation Decisions

• Initial Mapping– New musym and map unit concepts– Are tracked/documented until correlation– Split everything initially, lump at correlation– Reverse correlation back to the original map symbol

• Update Mapping– Reviewing correlated map units– Decisions on combining similar map unit concepts– Ability to track/document the origins of the map unit

Database Correlation Activities• Involves linking tables

– lmapunit– correlation– component pedon

• Involves documenting – lmuhistory– muhistory– text tables

Linking Tables

Create Data Mapunit

Link Pedons to Component

Link Mapunit and Datamapunit

Link Mapunit to a Legend

Documenting Correlation Decisions

Fully Reversible Correlation • Traces current musym/mapunit to the

original map field symbol • Map unit correlation documentation

– changing map unit name (Mapunit)– combining map units (Legend/Mapunit)– splitting map units (Legend/Mapunit)– changing map unit status (Legend)– changing map unit symbol (Legend)

Changing Map Unit Names

Changing map unit name• Documented in the Mapunit table• Changing the name will change it in every

location it is linked. • Use Mapunit History to document name change

Combining Map Units

Using an example of an Initial survey

Recording Correlation Decisions

Combine unit 4B consociation into unit 21B complex

• Combine map units• Changes are recorded in the Mapunit

History table.

Combining map unitsFirst step is to load/identify the map units in the mapunit table. The map units are highlighted, then using the icon (load related), the parameter box appears and the Mapunit table is chosen from the choice list. This will load the two map units in the

Mapunit table.

Combining map unitsCombine unit 4B consociation into unit 21B complexWhat legends are these map unit linked to? Where’s Waldo???

Combining map units

Combining map unitsEditing is required to insert a DMU link into the Correlation table.

Therefore, the data must be “checked out”.

Combining map units1. Copy the DMU link from the 4B consociation map unit and Paste into 21B complex

map unit. 2. Then make sure the REP DMU box is not checked for the 4B consociation DMU. 3. Change the 4B consociation map unit to “additional”

Combining map unitsLoad the related Data Mapunit and adjust the Component percentages to

reflect the new map unit concept.

Combining map unitsReturn to the Legend table. Notice that the map unit Status is changed in the Legend Mapunit table. Any changes made to a map unit impact those

Legends where the map unit is linked.

How can you identify those Legends that will be impacted?

Record Correlation Decisions

Type note

Populate the Mapunit History table

Linking historical map units to the MLRA map units

Map unit status changes

Map Unit Status

• Provisional – initial map unit concept

• Approved – Map unit concept approved by MLRA Project Leader and SDQS

• Correlated – Signed correlation document (initial) by MO Leader and State Conservationist

• Additional – replaced by another map unit concept

Documenting Decisions

Recording Correlation Decisions

• Changing map unit status in LMU History

Document Map Unit History• Correlation Decisions the map unit

Role of Spatial Database in Correlation

Provide visual analysis of the spatial distribution of map units

This includes:1. Soil properties2. Components or series3. Interpretations

Spatial database

Spatial database allows for the analysis of the distribution of data, whether is it point data, aggregated data or map unit interpretations

Supporting layers: 1. DEM’s , vegetation maps, land use, ORTHO, etc.

2. Spatial landscape and landform models

3. Analysis of spatial data (hillslope, slope gradient)

Summary• Soil Survey publication

– Historically, manuscripts – Today, databases

• Databases are provided for the – Population of data– Analysis of data– Publication of data

• Data is to be maintained in the “Corporate” database structure

• Why? Had all the initial documentation been in a database, you would have had all the information necessary to update.