June 1997 SurveysSoil - Minnesota Department of Administration

Minnesota Governor�s Councilon Geographic Information

June 1997

CountySoil

SurveysGuidelines for Digitizing

The Governor�s Council on Geographic Information wascreated in 1991 by Governor Arne H. Carlson to provideleadership in the development, management and use ofgeographic information and related technology. Withassistance from Minnesota Planning, the council providespolicy advice to all levels of government and makesrecommendations regarding investments, managementpractices, institutional arrangements, education,stewardship and standards.

Minnesota Planning is charged with developing a long-range plan for the state, stimulating public participationin Minnesota�s future and coordinating activities withstate agencies, the Legislature and other units ofgovernment.

Upon request, County Soil Surveys: Guidelines forDigitizing will be made available in alternate format, suchas Braille, large print or audio tape. For TTY, contactMinnesota Relay Service at (800) 627-3529 and ask forMinnesota Planning.

658 Cedar St.St. Paul, MN 55155(612) 296-3985

June 1997

For additional information or copies of County SoilSurveys, contact the council staff coordinator at(612) 296-1208 or e-mail, [email protected] electronic copy of this report can be found on theGovernor�s Council on Geographic Information�s WorldWide Web home page: www.lmic.state.mn.us/gc/gc.htm.

Cover map: Natural Resources Conservation Service,Minnesota State Office (map image shown in reverse).

Soils Data Committee MembersJay Bell, University of MinnesotaRobert Bixby, St. Cloud State UniversityAl Giencke, Natural Resources Conservation ServiceTim Kelly, Minnesota Department of Natural ResourcesGreg Larson, Board of Water and Soil ResourcesLes Maki, Minnesota Department of Natural Resources (co-chair)Joe McCloskey, Natural Resources Conservation ServiceGlenn Radde, Minnesota Department of Natural ResourcesDoug Thomas, Board of Water and Soil ResourcesDavid Vessel, Metropolitan CouncilDon Yaeger, Land Management Information Center at

Minnesota Planning (co-chair)

County Soil Surveys: Guidelines for Digitizing 1

C

Summaryreating a high-quality digital soil map and related database forgeographic information systems is an expensive process. Thisreport is intended to provide information and guidance to

Minnesota organizations considering developing digital soil maps fromcounty soil surveys.

Local and statewide demands fordigital soil survey data are faroutpacing the ability of federal andstate soil mapping organizations toproduce the data.

Modern soil surveys can be usedfor highway construction,agricultural planning, taxassessment, forest management andecological research, among otheractivities. To provide informationthat local officials and others canuse to make the best soil mappingdecisions, the Governor�s Councilon Geographic Information SoilsData Committee has developedCounty Soil Surveys: Guidelines forDigitizing, which:

Categorizes the nature andcurrent status of all county soilsurveys in Minnesota

Describes common GIS dataformats by which soil data can bestored

Identifies methods and resourcesfor converting soil surveys into digitalmap files and related databases

Techniques used by the federalNatural Resources ConservationService to classify and map soilshave changed significantly fromearly surveys, some of which weredone in the 1930s. Minnesota�scounty soil surveys in general tendto fall into one of three categories:

Outdated and in need of majorresurvey before they are convertedto digital form

On unrectified base maps and inneed of spatial corrections beforedigitizing

On modern orthophoto basemaps and ready for digitization

A hard look needs to be taken atthe county soil survey beforeembarking on converting it to adigital product. Changing methodsfor producing county soil surveysover time have resulted in a lack ofstandardization. Loading anoutdated survey into a GIS will notimprove either the quality or theaccuracy of the data. The processof bringing an outdated survey upto current NRCS specificationsdepends on the date and surveytechniques used in the originalmapping effort. This reportdescribes the evolution of theNational Cooperative Soil Surveyin Minnesota and appropriate usesof soil surveys, as well as providesinformation to determine the statusof all county soil surveys.

The report also describes thecommon GIS file types andconsiderations to be made inchoosing which to use. While adiscussion of file types can besomewhat technical, anunderstanding of the most commonfile types is important. File typesaffect the cost of the dataconversion and the overallusefulness of a digital soil survey.

Finally, the report reviews issuesthat should be considered beforeconverting paper soil survey mapsinto a digital GIS format.

County Soil Surveys

1 Summary

2 Contacts and Glossary

3 Introduction

4 Soil Mapping inMinnesota

5 Soil Survey Quality

6 Digitizing StatusCategories

8 Technical Options

11 Advice on ProducingDigital Soil Data

2 Minnesota Governor�s Council on Geographic Information

ContactsNatural Resources Conservation ServiceUnited States Department of Agriculture

Contact the state office to find yourfield representative:(612) 290-3679fax (612) 290-3375

Questions about the Soil Survey Information System:Pierre RobertDepartment of Soil, Water and ClimateUniversity of Minnesota439 Borlaug HallSt. Paul, MN 55108(612) 625-3125fax (612) 624-4223

Questions about the Environmental Planningand Programming Language, version 7.0:Land Management Information CenterMinnesota Planning658 Cedar St.St. Paul, MN 55155(612) 296-1211fax (612) 296-1212

GlossaryBelow are generallyaccepted definitionsfor terms used in thisreport.

Base map � Mapcontaining geographicfeatures used fororientation.

Digital soil data � Soildata stored in a digital,or computerized,format.

Edge matching �Ensuring that thefeatures on adjacentmap sheets fit together.

Geo-referencing �Translating the locationof map features intoreal-world coordinatessuch as latitude andlongitude.

Metadata � Detaileddescriptions aboutdata: geographic areacovered, methods usedto produce it, currency,accuracy, and so on.

Orthophoto �Computer-generatedphotograph thatcorrects for distortioncaused by hills, valleysand other landscapefeatures.

Raster format � Datastructure where rowsand columns are usedto store images.

Rectified photography� Method used tominimize distortioncaused by the cameraangle.

Soil survey �Systematic inventory ofsoil types in ageographic area.

Terrain reliefdisplacement �Distortion of featureson an aerialphotograph caused byhills, valleys and otherlandscape features.

Tic � Geographiccontrol point orregistration mark on amap, which representsa known location onthe earth�s surface.

Vector format � Datastructure where allmap features are storedas points, lines, andareas.


Introductionigital soil data was identified as the highest priority data need in arecent user survey conducted for the Governor�s Council onGeographic Information. Since the early 1980s, several organized

programs have produced digital soil map data. At the same time, data isbeing developed by various independent efforts in many inconsistent formsbecause of the lack of standards. Due to the cost of producing this data, itmust be collected using high-quality processes that are structured anddocumented to common standards. Only in this way will digital soil data beobtained that can be used for any geographic area, such as county,watershed, ecoregion or farmstead.

This document is designed to helpelected officials and others makeinformed decisions about creatingdigital soil data and dealing withvendors. It breaks up the decision-making process into three steps:

Determine the status of a countysoil survey for digitizing. Countysoil surveys vary greatly in qualityand suitability of mapping foraccurate digitizing. It is importantto understand the implications of

these differences before trying tocreate a digital soil map.

Review options for creating adigital soil product. Each optionhas advantages and disadvantages,depending on the quality of theexisting map.

Decide the technicalspecifications for the digital soilproduct. Following thespecifications presented in thisdocument will help to ensure thegreatest geographic compatibility ofsoil data with other digital data.These specifications can be used toguide vendors hired to do thedigitizing work.

D

In this map from a modern soil survey, soil types are superimposed on a digital orthophoto base map. It shows about 1.5 squaremiles of Sherburne County just northeast of Elk River. Source: NRCS, Minnesota State Office


Soil Mapping in Minnesotainnesota soils have been mapped at scales and complexitiesranging from page-sized state maps with general soil features todetailed site plots. Minnesota is part of the National Cooperative

Soil Survey, which creates detailed soil maps at the county level. The countysoil survey program was established in 1899 within the U.S. Department ofAgriculture to help farmers determine the crops and management practicesmost suitable for the soils on their farm. As scientists learned more aboutsoils, they investigated soil characteristics for other land uses. Modern soilsurveys can be used for such diverse activities as highway construction, farmplanning, tax assessment, forest management and ecological research.

Since the 1920s, aerialphotography has been used as anaid for soil mapping and apresentation base for the final map.This has greatly increased theprecision of soil surveys andpermitted extensive mapping atdetailed scales (1:24,000 or less).Participating in this effort havebeen federal and state agencies andthe agricultural experiment stationsof land grant universities, such asthe University of Minnesota.

The NCSS adheres to a set ofstandards for soil map production,data collection and publication ofsoil surveys, making it one of themost historically consistentresource surveys. Consistency inmethodology and final products,used with a common system of soilclassification and interpretation,allows nearly seamless soilinterpretations across politicalboundaries for watershed,ecoregion, state or national levels.

One of the first county soil surveysin Minnesota was produced in1906 for Blue Earth County. Earlysoil maps were crude because nostandard mapping proceduresexisted. County surveys werecreated at a fairly slow pace for thenext 50 years. By the end of 1963,only one-third of the state had beenmapped. In 1977, Minnesota

embarked on a 16-year program toaccelerate the rate of soil surveymapping. This acceleration wasjustified by the state�s pressing needfor knowledge of the soil resourcebase to assess agricultural and forestproductivity and to evaluate theenvironmental impacts of land-usechanges. The LegislativeCommission on MinnesotaResources provided about one-third matching funding inpartnership with counties and thefederal government to complete orinitiate mapping in all but threecounties by the late 1990s.

Uses of County SoilSurveysSoil scientists produce a county soilsurvey by observing the terrain,drainage patterns, native vegetativecover and the parent material fromwhich the modern soils wereformed. Soils are classified andnamed based on nationwideuniform procedures. Areas withsimilar soil characteristics,delineated on aerial photographs inmodern county soil surveys, arecalled map units. Published soilsurveys contain maps with variousmap units delineated on base maps,plus a variety of tables that showhow various soils will respond todifferent land-use applications.

The modern county soil survey isdesigned for basic land-use andrelated natural resource planningand management. The surveycontains descriptions of thephysical and chemical properties ofsoils and interprets the capabilitiesand limitations of soils foragricultural, forestry and urbanuses. Agricultural land uses havebeen a traditional focus of soilsurvey applications. The surveysprovide guidance on soil suitabilityfor particular agriculture uses andtechniques for overcoming soil andterrain limitations. Becauseagricultural productivity is soclosely tied to soils, soil surveyshave also formed a basis for ruralland appraisal.

Soil surveys also are being used fordiverse applications, such ascommunity planning of residentialand commercial development,transportation, recreation open spaceand natural areas, and in dealing withland-use conversions. For example, asoil survey can aid substantially in thesearch for suitable land for residentialexpansion by a community thatwants to minimize losses of valuableagricultural land and retain highlyerodible forest land in forest cover.

Natural resource applications ofsoil surveys arise out of the closeconnection between land-usemanagement and natural resourceconditions. Poor management ofsoil for a particular land use oftenresults in an undesirableenvironmental situation. Anexample is the effects of acceleratedsoil erosion on lakes and streamscaused by inappropriate land-usepractices. Soil surveys are also animportant consideration in

M


he quality of any county soil survey should be determined beforeany soil survey digitizing project is started. The County Soil SurveyStatus table on page 9 contains the status of soil surveys for each

county. The characteristics of a particular survey can influence the selectionof the method used to acquire the soil data and the usefulness of the finaldigital data product.

prioritizing land for retention orchanges in use to meet naturalresource goals. To lessen the effectsof erosion, for example, theidentification of highly erodiblelands through a soil survey, alongwith information on land use, canbe used to help target lands forsuch programs as land set asidesand conservation easements.

Soil Survey Quality

It is imperative to recognize thatdigitizing will not increase thequality of a soil survey. If a county�ssoil survey is outdated, digitizing thedata will not increase its accuracy.The same can be said about existingdigital soil surveys identified in thesurvey status table. The fact thatthese surveys were digitized doesnot improve their quality.

Two principal accuracy issues mustbe considered before digitizing a soilsurvey: spatial accuracy andattribute accuracy. Spatial dataindicates where something occurs,while attribute data indicates thenature or characteristics of thespatial data. If soil boundary linesare to be digitized and overlaid withother geo-referenced data layers,they need to be consistent with theoriginal published survey. Thespatial accuracy of the line work in asoil survey is a function of three

of vertical relief) but can beconsiderable in higher-relieflandscapes. For both NHAP andNAPP orthophotography, tilt andterrain relief displacement errorshave been removed. Theseorthophotos have the samequalities as a map, such asconsistent scale. Soil surveyscompiled on this base should besuitable for digitizing.

Topographic relief. Withtopographic relief, areas of lowrelief (flat areas with less than 45feet of vertical topographic relief)are less likely to be distorted.Topographic distortions have beenvirtually eliminated in soil surveysbased on orthophotos because theyare corrected for both geometricand relief errors found in aerialphotographs. Higher-relief areaswill require some form ofrecompilation to a corrected mapbase before they are suitable forgeographic information systemapplications.

T

Soil surveys can play an importantrole in natural communityrestoration efforts because theyprovide a window to the past,showing conditions before the majorhuman landscape modifications ofthe last two centuries. They canreveal original natural communitiesand features, thereby pointing torestoration opportunities.

Modern county soil surveys,however, are not intended for site-specific land-use determinations,such as the siting or approval ofindividual septic systems. Findingsuitable sites for such land usesusually requires on-siteinvestigation of soil characteristicsby a professional soil scientist.

characteristics: scale, photographicbase and topographic relief.

Scale. Generally the larger thescale, the higher the spatialaccuracy.

Photographic base. Thephotographic base determines thetypes of spatial errors the surveywill inherit from the base map. TheNCSS has used three types of basemaps in digitizing soils: rectified airphotos, National High AltitudePhotography orthophotos andNational Aerial PhotographyProgram orthophotos. Soil surveysfor 63 Minnesota counties havebeen published on rectified aerialphotography. In rectified airphotos, tilt displacement (tilt of theaircraft) errors have been corrected,but spatial errors due to terrainrelief displacement have not.Spatial errors are minimal in low-relief landscapes (less than 45 feet


Digitizing Status Categorieshe Governor�s Council on Geographic Information has developedfour categories of county soil surveys (see the County Soil Surveymap on page 7). These classes are based on the vintage of the survey

and the type of photography used for the survey map base. They aredesigned to help users determine the best path to creating a digital soildatabase. Categories 1 through 3 are outlined below; Category 4 recognizeswhere no soil survey exists because the county has not been surveyed (thisincludes three counties).

Attribute accuracy is related to thevintage of the survey. Counties aredivided into three categories basedon soil survey vintage:

Modern survey based on thecurrent classification standard.These include counties wheresurveys have been published (35counties); completed and awaitingpublication, including thoseupdated to modern standards (18counties); and in progress,including updates (10 counties).These surveys are considered to begenerally suitable for detailed land-use planning by the NaturalResources Conservation Service.

Outdated survey based on aclassification standard no longerconsidered acceptable.

Recorrelation or extensive fieldwork is needed to developinterpretations suitable for modernuses (21 counties).

No survey. No soil survey isavailable or in progress (threecounties).

Since soil scientists have learnedmore about soils since the first soilsurvey was conducted inMinnesota, both the soil mappingunits for soils and their attributeshave evolved. Outdated soil surveyshave two principal shortcomings:

They do not match up seamlesslywith surveys from surroundingcounties. The soil mapping units inmodern surveys have beenstandardized nationally. Before the

availability of standardizedmapping units, soil scientists oftenlabeled units with local monikers.As a result, identical soils inoutdated surveys are often labeleddifferently from one county to thenext. This makes direct comparisonsfrom an outdated survey to anyother soil survey difficult.

They reflect the most current soilresearch at the time they werepublished. The many soil surveys inMinnesota reflect generations ofsoil science investigations. As aresult, some soil mapping unitsfrom outdated surveys are notdirectly convertible to modernunits. The quality of outdated mapunit attributes will vary accordingto the year of interpretation.

Category 1: Modern soil surveyon an orthophoto base. These soilsurveys have both accurate spatialand attribute information andrepresent the highest-quality soilsurvey data. They should becarefully digitized to retain thequality of the data. This categoryhas three subgroups based onmapping status: 1A, soil surveypublished (one county); 1B, soil

survey awaiting publication(10 counties); and 1C, soil surveybeing mapped (10 counties).

Category 2: Modern soil surveyon rectified photography. Thesesoil surveys have accurate attributeinformation, but spatial accuracyvaries with topography � generallyhigh in areas with little relief butmarkedly less so in those of high

relief. This means that the soil layerin the GIS will not consistently lineup with other layers. The lack ofspatial accuracy often will result ingaps and overlaps when the soilsurvey data sheets are assembledfor a county. Digitizing a soil surveywill not improve its spatialaccuracy. Digitizing firms often�edge-match� the soil survey, butthis improves only the visual appealof the map, not the spatial accuracy.Category 2 soil surveys that aredigitized will have variable spatialaccuracy. Digitizing these surveysmay not be a wise investment ofpublic funds. They can, however,be recompiled on orthophoto basemaps to correct spatial accuracyproblems. The recompiled survey

T


would then be considered to be aCategory 1 soil survey.Recompilation is a difficult andexpensive task that must besupervised by a qualified soilscientist. The NRCS should beinvolved before any recompilationdiscussion or work is attempted.For more information, contactthe state NRCS office at(612) 290-3679.

Category 2 surveys fall into threegroups based on relief classes.These classes were determined bycalculating elevation diversity from3-arc second digital elevation modeldata and provide, at best, roughguidelines of relative terrain relief.The groups are: 2L, lowest relief(18 counties); 2M, moderaterelief (18 counties); and 2H,highest relief (six counties).

Category 3: Outdated soil surveyrequiring updating of map orattribute data before digitizing.These soil surveys have all theshortcomings of Category 2surveys, plus they represent anoutdated understanding of soils.This means that their soil mappingunits and attributes are not current.Mapping units in Category 3surveys are often unique to thecounty and end abruptly at thecounty boundary. In addition, theattributes associated with a soilmapping unit, such as productivity,may have changed since the surveywas published.

Digitizing a Category 3 soil surveywill not improve the survey�saccuracy and is not recommended.A digitized Category 3 soil surveywill contain the limitations outlinedin Category 2 as well as unreliableattribute information. If such asurvey is digitized, the process usedto digitize it, along with theshortcomings inherent in it, shouldbe documented for others who maywish to use the data.

An updated soil survey is requiredto raise Category 3 surveys to aCategory 1 status. An NRCSevaluation of the soil survey shouldbe completed before anyrecompilation work is initiated.

Category 3 soil surveys fall intothree groups based on relief: 3L,low relief (six counties); 3M,moderate relief (10 counties); and3H, high relief (five counties).

Source: Soils Data Committee, Minnesota Governor�s Councilon Geographic Information

Lake ofthe Woods

Koochiching

Mah

nom

en

Wad

ena

Pine

Kan

abec

Aitkin

MilleLacs

Isanti

Otter TailCrowWing

Todd

Grant

StevensTraverse

Swift

Stearns

Anoka

Kan

diyo

hi Meeker

ChippewaWright

Yellow Medicine

Linc

oln Lyon

Pipe-stone

Rock Nobles

Murray

Redwood

McLeod

SibleyDakotaScott

LeSueur

Brown

Watonwan

Jackson

Was

eca

Rice

Steele DodgeOlmsted Winona

HoustonFillmore

Kittson

Clay Becker

Carlton

Itasca

Beltrami

Hubbard Cass

MorrisonDouglas

Pope

Cotton-wood

Martin

Roseau

Marshall

Polk Pennington

Norman

Wilkin

Red Lake

Renville

Nicollet

Freeborn Mower

Blue Earth

Hennepin

Faribault

Goodhue

Wabasha

Chi

sago

Was

hing

ton

Ram

s.

Lake

St. Louis

Lac QuiParle

Cook

Carver

BigStone

Benton

Cle

arw

ater

Sherburne

Category 1�Modern Surveyon Orthophoto Base Maps

Category 2�Modern Surveyon Rectified Photo Base Maps

Category of Soil Surveyas of January 1, 1997

Category 3�OutdatedSoil Survey

No Survey Ever Done

Only About One-Fourth of Counties Have Surveys Readyfor Digitizing to Modern Standards


Technical Optionsome parts of the state may have some form of digitized soil dataavailable (see the County Soil Survey Status table on page 9), butwith the potential limitations previously discussed. Existing

products include the Soil Survey Information System, raster files in otherformats such as EPPL7 and vector files in various file formats, such as ARC/INFO, DLG and MAPINFO. Depending on the survey area�s situation, theavailability of an existing digital product may facilitate the production of anaccurate, geo-referenced soil survey.

Digital FormatsA GIS manages and manipulatestwo types of data produced by amodern soil survey: attribute andspatial. Attribute data describes thecharacteristics of each soil mappingunit, such as predominant soilseries, soil drainage class andtexture of the surface horizon.Spatial data is represented bypoints, (e.g., wet spots, sinkholes),lines (e.g., stream and drainagesystems) and polygons (e.g., soilmapping units). This spatialinformation must be referenced toa geographic coordinate system andis usually stored as either raster(grid-cell) or vector (arc-node)digital format.

In raster formats, an area is dividedinto rows and columns of cells(rasters), and each raster is assignedan attribute value representing thefeature for that location. Rasters ofvarious sizes can be used,depending on the scale of the mapbeing digitized. Grid cell sizes of 10to 30 meters square typically areused for county-level surveys. Withraster data, the value of a cellrepresents the predominantmapping unit if more than onemapping unit occurs in that grid-cell location.

Vector formats are based on theexplicit definition of coordinatesthat define the location of a point,line or polygon feature. Forexample, a soil mapping unit

consists of a series of points definingvectors that outline the unitboundaries. Each vector is assignedtwo identifiers, one for each side ofthe vector. Each identifier definesthe attribute for the polygon.

Digital Soil DataFormats Common inMinnesotaRaster Soil DataRaster soil data in Minnesota isgenerally available through theUniversity of Minnesota Soil SurveyInformation System and the

Environmental Planning andProgramming Language, version 7.0.The majority of modern soil surveyshave been captured and converted toraster files for use in one or both ofthese two programs. These specificformats and their inherent limitationsare highlighted below.

SSIS. This polygon-basedproduct displays soil on a section-by-section basis, along withassociated attributes such as acidityor alkalinity and hydrologic group.SSIS calculates acreage of selectedpolygons and attributes, anddisplays and calculates small areacoverage within a section to showsoil variability within fields.

In early versions of this system,each section file represented onesquare mile whether or not it was afull section. The sections on thenorth and west side of mosttownships are either less or morethan one square mile because of

S

This gray-tone map displays soil types using EPPL7 raster-format software. It shows thenorthwestern corner of Le Sueur County. The straight white lines represent section linesfrom the Public Land Survey. Source: Land Management Information Center


National Cooperative Soil SurveyCounty Soil Survey Status, January 1, 1997

*Digitized products are described in more detail in the next section.

Note: This inventory of digitized products is still being compiled. People who have information on digital soil products not listed here areasked to contact Jay Bell, Department of Soil, Water and Climate, University of Minnesota, 439 Borlaug Hall, St. Paul MN 55108; telephone,(612) 625-6703; e-mail, [email protected] . For information on the Soil Survey Information System, contact Pierre Robert, Departmentof Soil, Water and Climate, University of Minnesota, 439 Borlaug Hall, St. Paul, MN 55108; telephone, (612) 625-3125; fax (612) 624-4223.For information on the Environmental Planning and Programming Language, version 7.0, contact the Land Management Information Center,658 Cedar St., St. Paul, MN 55155; telephone (612) 296-1211; fax (612) 296-1212.

Marshall 1B Modern NHAP Ortho L NoMartin 2L Modern Rectified L SSIS, VectorMcLeod 2L Modern Rectified L SSIS, EPPL7Meeker 2M Modern Rectified M NoMille Lacs 1C Modern NAPP Ortho M No

Morrison 2M Modern Rectified M NoMower 2M Modern Rectified M SSIS, EPPL7 (partial)Murray 2M Modern Rectified M SSIS, EPPL7Nicollet 1A Modern NHAP Ortho L SSIS, EPPL7Nobles 3M Outdated Rectified M No

Norman 3L Outdated Rectified L SSISOlmsted 2H Modern Rectified H SSIS, VectorOtter Tail 1B Modern NHAP Ortho M NoPennington 2L Modern Rectified L SSIS, EPPL7Pine 4 No survey N/A M N/A

Pipestone 3M Outdated Rectified M SSIS, EPPL7Polk 1B Modern NHAP Ortho M NoPope 3M Outdated Rectified M NoRamsey 2H Modern Rectified H SSIS, Vector

(in progress), EPPL7

Red Lake 1C Modern NAPP Ortho L NoRedwood 2L Modern Rectified L SSIS, EPPL7Renville 1B Modern NHAP Ortho H NoRice 1B Modern NAPP Ortho H NoRock 2M Modern Rectified M SSIS, EPPL7

Roseau 1C Modern NHAP Ortho L NoScott 3H Outdated Rectified H Vector (in progress)Sherburne 1B Modern NAPP Ortho L NoSibley 1B Modern NHAP Ortho L SSISSt Louis 1C Modern NAPP Ortho M Vector (in progress)

Stearns 2M Modern Rectified M SSIS, Vector, EPPL7Steele 3M Outdated Rectified M SSIS, EPPL7Stevens 3L Outdated Rectified L SSIS, EPPL7Swift 1C Modern NAPP Ortho L SSIS, EPPL7Todd 2M Modern Rectified M No

Traverse 2L Modern Rectified L SSIS, EPPL7Wabasha 3H Outdated Rectified H NoWadena 2L Modern Rectified L SSIS, VectorWaseca 1C Modern NAPP Ortho M NoWashington 2H Modern Rectified H SSIS, Vector

Watonwan 2L Modern Rectified L SSIS, EPPL7Wilkin 2L Modern Rectified L SSIS, EPPL7Winona 2H Modern Rectified H SSIS, EPPL7Wright 1C Modern NAPP Ortho M NoYellow Medicine2L Modern Rectified L SSIS, EPPL7

County Category Vintage Base Map Relief Digitized Product*County Category Vintage Base Map Relief Digitized Product*

Aitkin 2L Modern Rectified L NoAnoka 3L Outdated Rectified L Vector (in progress)Becker 2M Modern Rectified M NoBeltrami 2L Modern Rectified L SSIS (partial),

EPPL7 (partial)

Benton 2M Modern Rectified M SSISBig Stone 2L Modern Rectified L SSIS, EPPL7Blue Earth 2M Modern Rectified M SSIS, EPPL7Brown 2M Modern Rectified M SSIS, EPPL7Carlton 3M Outdated Rectified M Vector

Carver 3H Outdated NHAP Ortho H SSIS, Vector(in progress), EPPL7

Cass 2M Modern Rectified M NoChippewa 2L Modern Rectified L SSIS, EPPL7Chisago 2M Modern Rectified M SSIS, EPPL7

Clay 2L Modern Rectified L VectorClearwater 1B Modern NHAP Ortho M NoCook 4 No survey N/A H N/ACottonwood 3M Outdated Rectified M SSIS, EPPL7Crow Wing 3M Outdated Rectified M No

Dakota 2M Modern Rectified M VectorDodge 3M Outdated Rectified M SSIS, EPPL7Douglas 3M Outdated Rectified M SSISFaribault 2M Modern Rectified M SSIS, EPPL7Fillmore 3H Outdated Rectified H No

Freeborn 2L Modern Rectified L NoGoodhue 3H Outdated Rectified H SSIS, EPPL7Grant 3L Outdated Rectified L NoHennepin 2M Modern Rectified M SSIS, Vector (partial)Houston 2H Modern Rectified H SSIS, EPPL7

Hubbard 1C Modern NAPP Ortho M NoIsanti 3L Outdated Rectified L NoItasca 2M Modern Rectified M VectorJackson 2L Modern Rectified L SSIS, VectorKanabec 1C Modern NHAP Ortho M No

Kandiyohi 2L Modern Rectified L SSIS, EPPL7Kittson 3L Outdated Rectified L SSISKoochiching 1C Modern NAPP Ortho L NoLac Qui Parle 1B Modern NHAP Ortho L NoLake 4 No survey N/A H N/A

Lake of the Woods2L Modern Rectified L NoLe Sueur 2H Modern Rectified H SSIS, EPPL7Lincoln 3M Outdated Rectified M NoLyon 2M Modern Rectified M SSIS, EPPL7Mahnomen 1B Modern NHAP Ortho L SSIS


survey corrections. Since 1992,however, the section files in SSIShave been geo-referenced and aremuch better referenced to thePublic Land Survey.

SSIS is not a GIS. Early versions arenot spatially oriented, nor can thesystem combine map themes, createnew themes or coverages or displaysoil maps for more than a section,such as a township or county. Bythemselves, SSIS section files arenot well suited to conversion to aGIS. They can be converted toother GIS formats such as rasterand vector; however, spatial errorsintroduced through the addition ofgeo-referencing will remain and canbe significant in Category 2 and 3counties.

EPPL7. This raster-based GIS ismade up of four major programs:EPPL, DOTPLOT, DISPLAY andDIGITIZE. Most EPPL7 soilcoverages have been createdthrough the conversion of SSISfiles. The final product is digital ina raster format with vector overlaycapability. EPPL7 soil coverages canbe used in most raster-based GISsoftware programs. They can alsobe converted to a vector-based GISthrough the use of common fileconversion routines.

The main consideration when usingan EPPL7 soil layer is one of spatialaccuracy. Because the most likelysource for this layer was SSIS datafrom Category 2 or 3 surveys, thespatial errors introduced are carriedforward to the EPPL7 database.Additional spatial error may beintroduced in the conversionroutine because of the need to�rubber sheet� (that is, adjust tobetter fit a more accurate base map)the sections to real coordinates and

the required edge-matching.Although spatial error in the datamay exist, EPPL7 soil layers arewell suited for raster-based systemsand for natural resource analyses atthe township and county levels.

Vector Soil CoveragesWhile vector soil coverages are notas common in Minnesota as rastercoverages, almost all recent effortsto digitize soil surveys have resultedin vector coverages. Current vectorcoverages are limited to just a fewcounties.

A number of commercial vector-based GIS software packages areavailable. They are characterized bya data format that is commonlyreferred to as vectors or polygons.Because these systems use lines,points and polygons to characterizedata, they provide for a high degreeof spatial accuracy. In using avector-based soil layer, the userneeds to understand how the layerwas created. In general, vector-based soil layers are generated in a

two-step process. The first stepinvolves scanning or hand-digitizing the hard-copy soil mapsheets. The second step is �rubbersheeting� the digital file to real-world coordinates. Therubber-sheeting process, however,will not remove terraindisplacement errors. The samespatial errors that occur in SSIS andEPPL7 are likely to occur in thisprocess unless the soil survey wasdone with and compiled ontoorthophotographs. Vector soillayers can also be created byconverting raster coverages. MostGIS packages allow for the creationof DLG- or DXF-formatted linefiles, which can be exported andimported between GIS packagesand converted into a data layer. Aswith the EPPL7 soil layer, as long asthe end user of the data is aware ofthe potential for spatial error anduses the data within its limitations,soil information is a useful andpowerful layer in a vector-basedGIS system.

Lb

Lake George

Rf

LnA

Iw

ZmB LnA

Mc

Ma

Ma

Ma

Ma

Ma LnA

Iw

Mc

LnA Ma

Iw

LnA

LnA

LnA

ZmC

LnA

Ma ZmB LnA

ZmB

LnA

Zm

B

Iw

Iw

Iw

ZmA ZmA Rf ZmB

Ma

Iw

Iw

ZmB

Ma

Iw

Ma

Iw

Iw

LnA

Iw

LnA

Ma

ZmB

LnA Ln

A

Ma

ZmA

LnA ZmB

Iw

LnA

Ma

ZmA

ZmB

In this vector line map, soil types are indicated by letter codes. Note the detailcaptured in this example of a one-half square mile area from the Anoka CountySoil Survey. Source: Land Management Information Center


Advice on Producing Digital Soil Datathe data file may have to beprocessed to match the projectionafter it is done. The necessaryspecifications are: projection, suchas UTM or State Plane; zone, ifapplicable; units, such as meters orfeet; datum, either NAD27 orNAD83; and spheroid, such asClark 1866 and so on.

Map RegistrationEach soil survey map sheet must beregistered with a minimum of fourtics. The data should ideally bewithin a polygon defined by thetics. Data outside the tics will havesignificantly deteriorated spatialaccuracy. Most modern soil surveyshave State Plane coordinate ticmarks on each sheet (and oninsets). These coordinates should beused for registration andconversion to other projections.

Data ModelAll files for the entire project areashould be submitted using thefollowing criteria (the terminologyused here is for the ARC/INFO GISsystem; these terms and processescan be found in most other GISpackages):

All features recorded in the datafiles will be captured as areas (notjust linear or point features). Whenplotted and registered to itscorresponding manuscript, noplotted line will deviate from theoriginal line work by more than0.010 inch.

Each coverage will have polygontopology. All features recorded inthe data files will be captured asareas (not just linear or pointfeatures). When plotted andregistered to its correspondingmanuscript, no plotted line willdeviate from the original line workby more than 0.010 inch.

N

met, the data will probably need tobe digitized again to make itcompatible with other data sets.

CommonConsiderationsSome of the more commonconventions found in soil surveycontracts are noted below. Whilethis list is not comprehensive andthe language cited is not intendedto be used verbatim, the list doesaddress many issues that are easilyoverlooked. Misunderstandings,costly contract amendments andunmet expectations can be avoidedby discussing these issues with thedigitizing vendor before data iscollected.

File Naming ConventionA standardized file naming scheme,with up to an 8-character file nameand a 3-character extension, allowseasy implementation of batchprocessing. A common method is afour-character county abbreviationand an NRCS sheet number (1-99)(e.g., anok001.e00). Map sheetswith insets will require separatefiles for each inset. These inset filesshould be named with the four-character county abbreviation, aone-digit alpha code starting with�a,� and an NRCS sheet number(e.g., anok001a.e00).

Map ProjectionThe map projection should matchthe organization�s standard.Specifying a map projection isimportant; if this is not done, all of

Contracting for the production ofdigital soil data can be complicated.This section offers guidance onvarious aspects of the contractingprocess. Digital soil data resultingfrom contracts that include thefollowing provisions will ensure thegreatest compatibility with otherdigital data and will best meet theneeds of local governments andcontribute to the state�s goal ofachieving a seamless digital soildatabase.

Determining the CostThe cost of acquiring a digital soilsurvey will depend on thecondition of a county�s current soilsurvey. For Category 2 or 3surveys, digitizing the map sheets(scanning and labeling) mayrepresent only a small portion ofthe total cost of creating a digitallayer. This is because of therelatively high costs ofrecompilation and correlation.

Starting the ProcessOnce the decision is made todigitize a soil survey, the NRCSfield representative should becontacted. This person can providea list of resources and informationon other soil digitizing projects inthe area (e.g., A Quality Matrix forDigital Soil Surveys). NRCSdigitizing specifications weredesigned to ensure the greatestcompatibility of soil data with otherdigital data. If modern NRCS soilclassification specifications are not

RCS is producing digital soil data to national standards fromcounty soil surveys, although present funding and staffing levelsallow this work to proceed at only a slow pace. Many counties are

choosing to produce digital data before the NRCS schedule would allow.Most will contract this production work out.


Point soil features will becaptured on a separate coveragewith point topology. When plottedand registered to its correspondingmanuscript, no plotted point willdeviate from the original line workby more than 0.010 inch.

Every polygon will be assignedone and only one label. Each labelpoint will be located away from thepolygon edges and as near thecenter of the polygon as is practical.

Only soil information will becaptured; no digital representationof internal tics or administrativeboundaries, such as section lines, isrecommended. Within the samesheet, adjacent polygons of thesame soil type are not permitted(run the dissolve function tocheck).

The coverage will contain nonode errors. Connectivity betweenline segments will be complete.

The use of pseudo-nodes will bekept to a minimum and used onlywhen necessary.

Extraneous marks that may existon the manuscript will not becollected in digital files.

Graphic Data AccuracyGraphic plots should be producedby the vendor and delivered withthe data to test positional accuracyof the digital line work. When eachplot is registered to itscorresponding manuscript, noplotted line should deviate from theoriginal line work by more than0.010 inch.

Output FormatFinal digital products should beprovided in vector format. Onecommonly used format isuncompressed ARC/INFO exportfiles, which is preferred. Thisindustry standard format is widelyused in Minnesota and easily

converted to most other geographicdata formats. A convenient way totransfer data is via a CD-ROMwritten using the ISO 9660 CD-ROM archive standard. A printedlist of data files should be includedwith each CD.

DocumentationThe digitizing vendor must submita final report documenting the dataas a condition of acceptance. It isrecommended that vendors fill outthe standard state metadata filedeveloped by the Governor�sCouncil on GeographicInformation. Substantially moreconcise than the federal standard,this file can be requested from thecouncil�s Internet home page atwww.lmic.state.mn.us/gc/gc.htm.The vendor�s final report mustinclude the following informationat a minimum:

Process. Detailed informationabout the procedures used toproduce the final data productsshould include descriptions of datacapture, processing and quality-control techniques andidentification of the specifichardware and software used.

File information. Detailedinformation about each completeddata file should include thefollowing: data file name, asdiscussed above under �FileNaming Conventions�; data filearea of coverage (descriptive orgraphic); and source information,including source citation and scaleor resolution, type of source(photography, orthophotography,satellite image, etc.), type of sourcemedia (polyester-based product,stable paper, paper, etc.) and dateof source material.

Final production date andproduction manager�s name.

Acceptance TestingAll submitted data must pass aquality assurance test to confirmcompliance with data compatibilityrequirements outlined in thecontract. Submitted data must beindependently tested and reviewed.Acceptable error rates and aremedy for failure to meetstandards should be established; acommon remedy is to return thedata to the vendor for free repair.The acceptance testingrecommended by the NRCS varieswith the quality of the soil survey.The local NRCS representativeshould be consulted before criteriaare set.

Delivery Schedule and MediaA schedule for the orderly deliveryand acceptance testing of all datasets should be established and thevendor required to submit inwriting for approval any change tothe schedule or delivery method.

Township Tic LabelingSection corners used to register thesoil survey should adhere to thenumbering conventions maintainedby the Land ManagementInformation Center. A layer ofstatewide section corners isavailable from the LandManagement Information Center ata scale of 1:24,000 (SECTIC24K).More accurate section corner datamay be used where it exists, andState Plane tics on the soil sheet,especially for insets, can be used,since four-section sections arerarely available.

Documents

June 1997 SurveysSoil - Minnesota Department of Administration