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Mn/Model

Final Report Phases 1-3 (2002)

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Table B.26: Map Unit Names with No Textural Class Given in NRCS Database, and the Texture Classes Assigned to Them.

Map unit name Texture class assigned
ALLUVIAL LAND ALL
ALLUVIAL LAND, FREQUENTLY FLOODED ALL
ALLUVIAL LAND, OCCASIONALLY FLOODED ALL
ALLUVIAL LAND, POORLY DRAINED ALL
ALLUVIAL LAND, SLOPING ALL
ALLUVIAL LAND, WET ALL
ALLUVIAL-URBAN LAND COMPLEX ALL
ANKENY LOAM, 0 TO 2 PERCENT SLOPES L
AQUENTS AND HISTOSOLS, PONDED MPT
AQUENTS AND UDORTHENTS AQ
AQUENTS, SANDY AQ
AQUOLLS AND AQUENTS, PONDED AQ
AQUOLLS AND HISTOSOLS, PONDED MPT
AQUOLLS AND HISTOSOLS, SLOPING MPT
AQUOLLS, PONDED AQ
BEACH MATERIALS, SANDY BS
BEACH SAND BS
BECHYN LOAM, 2 TO 6 PERCENT SLOPES L
BIRCHLAKE SILTY CLAY LOAM, 1 TO 6 PERCENT SLOPES SCL
BIRCHLAKE SILTY CLAY LOAM, 12 TO 20 PERCENT SLOPES, ERODED SCL
BIRCHLAKE SILTY CLAY LOAM, 20 TO 30 PERCENT SLOPES SCL
BIRCHLAKE SILTY CLAY LOAM, 6 TO 12 PERCENT SLOPES, ERODED SCL
BLOWERS FINE SANDY LOAM, 1 TO 3 PERCENT SLOPES, STONY FSL
BLUFFCREEK-CLEARRIVER COMPLEX BL
BOROFOLISTS PEAT
BOROSAPRISTS MUCK
BOROSAPRISTS UNDIFFERENTIATED MUCK
BOROSAPRISTS, DEPRESSIONAL MUCK
BORROW LAND PIT
BORROW PITS PIT
BORUP MUCKY SILT LOAM, DEPRESSIONAL MK_SL
BRANDSVOLD FINE SANDY LOAM, THICK SOLUM FSL
BREAKS AND ALLUVIAL LAND ALL
CATHRO MUCK, CALCAREOUS MUCK
CEDARROCK SILTY CLAY LOAM SICL
CENSUS WATER WAT
CHETOMBA SILTY CLAY LOAM SICL
CLEARWATER MUCKY LOAM, DEPRESSIONAL MK_L
CLITHERALL SANDY LOAM SL
CLOTHO LOAM L
COHOCTAH LOAM, FREQUENTLY FLOODED L
COLAND LOAM, SANDY SUBSTRATUM, RARELY FLOODED L
COLO SILT LOAM, 0 TO 2 PERCENT SLOPES, CHANNELED SIL
CORVUSO SILTY CLAY LOAM SICL
CROWRIVER LOAM L
CROWRIVER-MANANNAH COMPLEX L
CUTAWAY LOAMY FINE SAND, 1 TO 6 PERCENT SLOPES LFS
DENT SILT LOAM, 1 TO 6 PERCENT SLOPES SIL
DORA MUCK, PONDED MUCK
DUBUQUE SILT LOAM, SHALLOW, 12 TO 18 PERCENT SLOPES, MODERATELY SIL
DUMPS DUMP
DUMPS, MINE DUMP
DUNE LAND DUNE
FILL LAND FILL
FLAMING LOAMY FINE SAND, 0 TO 3 PERCENT SLOPES LFS
FLOM-PARNELL STONY SILTY CLAY LOAMS ST-SICL
FLOM-PARNELL VERY STONY SILTY CLAY LOAMS ST-SICL
FLUVAQUENTS ALL
FLUVAQUENTS - HAPLOBOROLLS COMPLEX ALL
FLUVAQUENTS, CHANNELED ALL
FLUVAQUENTS, FREQUENTLY FLOODED ALL
FLUVAQUENTS, FREQUENTLY FLOODED-EUTROBORALFS COMPLEX, 0 TO 60 PERCENT SLOPES ALL
FLUVAQUENTS, LOAMY ALL
FLUVAQUENTS-HAPLOBOROLLS COMPLEX ALL
FORDVILLE STONY LOAM, 0 TO 2 PERCENT SLOPES ST-L
FORESTCITY-MANANNAH COMPLEX SICL
FOXLAKE SILTY CLAY LOAM SICL
FULDA LOAM, SAND SUBSOIL VARIANT, 0 TO 2 PERCENT SLOPES L
GLENCOE MUCKY LOAM, 0 TO 1 PERCENT SLOPES, PONDED MK-L
GLYNDON VERY FINE SANDY LOAM VFSL
GRAVEL PIT GR-PIT
GRAVEL PITS GR-PIT
GRAYCALM SAND, 0 TO 2 PERCENT SLOPES S
HALVERSON LOAMY FINE SAND, 1 TO 6 PERCENT SLOPES LFS
HALVERSON LOAMY FINE SAND, 6 TO 15 PERCENT SLOPES LFS
HAPLAQUOLLS AND HISTOSOLS, PONDED MPT
HAWICK GRAVELLY LOAMY COARSE SAND, 12 TO 20 PERCENT SLO PES LCOS
HAWICK GRAVELLY LOAMY COARSE SAND, 20 TO 35 PERCENT SLO PES LCOS
HAWICK-ESTHERVILLE COMPLEX, 6 TO 12 PERCENT SLOPES LCOS
HISTOSOLS, PONDED MPT
KNUTE FINE SANDY LOAM, THICK SOLUM FSL
LAKE BEACHES B
LAKE BEACHES, LOAMY BL
LAKE BEACHES, SANDY BS
LAKE BORDERS B
LIME QUARRY LQ
LIZZIE SILT LOAM, 0 TO 3 PERCENT SLOPES SIL
LIZZIE SILT LOAM, 12 TO 20 PERCENT SLOPES SIL
LIZZIE SILT LOAM, 2 TO 6 PERCENT SLOPES SIL
LIZZIE SILT LOAM, 6 TO 12 PERCENT SLOPES SIL
LOWLEIN SILT LOAM SIL
MADE LAND ART
MAHTOWA MUCKY SILT LOAM, 0 TO 1 PERCENT SLOPES MK-SIL
MANANNAH SILTY CLAY LOAM SICL
MARSH MUCK
MILACA SANDY LOAM, 12 TO 18 PERCENT SLOPES, VERY STONY ST-SL
MILACA SANDY LOAM, 18 TO 25 PERCENT SLOPES, VERY STONY ST-SL
MILACA SANDY LOAM, 2 TO 6 PERCENT SLOPES, VERY STONY ST-SL
MILACA SANDY LOAM, 6 TO 12 PERCENT SLOPES, VERY STONY ST-SL
MINES AND PITS PIT
MIXED ALLUVIAL LAND, 0 TO 6 PERCENT SLOPES ALL
MIXED ALLUVIAL LAND, 7 TO 17 PERCENT SLOPES ALL
MIXED ALLUVIAL LAND, MODERATELY WELL DRAINED ALL
MIXED ALLUVIAL LAND, POORLY DRAINED ALL
MORA LOAM, VERY STONY ST-L
MUCK AND PEAT, CALCAREOUS, FLOODED MPT
MUCK, CALCAREOUS, SEEPED MUCK
MUSTINKA SILTY CLAY LOAM SICL
NEWFOLDEN LOAM L
NEWSON MUCKY SANDY LOAM, 0 TO 1 PERCENT SLOPES MK-SL
NIDAROS MUCK, CALCAREOUS MUCK
NORTHWOOD MUCK, PONDED MUCK
NUTLEY SILTY CLAY LOAM, 0 TO 2 PERCENT SLOPES SICL
NUTLEY SILTY CLAY LOAM, 2 TO 6 PERCENT SLOPES SICL
OAKCREEK LOAM L
PARENT LOAM, VERY STONY ST-L
PEAT AND MUCK MPT
PEEVER CLAY, 2 TO 6 PERCENT SLOPES C
PEEVER-BUSE COMPLEX, 2 TO 6 PERCENT SLOPES CL
PERCY MUCKY LOAM, DEPRESSIONAL MK-L
PINELAKE SANDY LOAM SL
PINELAKE, LOAMY SUBSTRATUM-BRANDSVOLD COMPLEX SL
PITS, GRAVEL GR-PIT
PITS, GRAVEL-UDIPSAMMENTS COMPLEX GR-PIT
PITS, GRAVEL-UDORTHENTS COMPLEX GR-PIT
PITS, MINE PIT
PITS, QUARRIES UWB
PITS, QUARRY UWB
PITS,QUARRY UWB
PITS-QUARRY UWB
PLAINFIELD-URBAN LAND COMPLEX, 0 TO 6 PERCENT SLOPES UL
PLAINFIELD-URBAN LAND COMPLEX, 6 TO 15 PERCENT SLOPES UL
PREBISH FINE SANDY LOAM, VERY STONY ST-FSL
PRINSBURG SILTY CLAY LOAM SICL
PSAMMENTS, FILL FILL
PSAMMENTS, NEARLY LEVEL S
PSAMMENTS, NEARLY LEVEL TO SLOPING S
QUARRY UWB
REDBY LOAMY FINE SAND, STRATIFIED SUBSTRATUM LFS
RENSHAW AND FORDVILLE VERY STONY LOAMS ST-L
RENSHAW STONY LOAM, 0 TO 6 PERCENT SLOPES ST-L
RIVERWASH ALL
ROCK OUTCROP-LITHIC EUTROCHREPTS COMPLEX UWB
RONNEBY LOAM, EXTREMELY STONY ST-L
RONNEBY LOAM, VERY STONY ST-L
ROUGH BROKEN LAND BR
SANDSTONE OUTCROPS UWB
SANDY LAKE BEACHES BS
SEWAGE LAGOON WAT
SKAGEN LOAM L
SKAGEN LOAM, VERY COBBLY CB-L
SLICKENS C
STEEP LAND, HAYDEN-LESTER MATERIALS BR
STONELAKE-NEBISH COMPLEX, 12 TO 25 PERCENT SLOPES LS
STONY LAND BR
STRATHCONA AND KRATKA SOILS, DEPRESSIONAL FSL
SVEA STONY LOAM, 0 TO 2 PERCENT SLOPES ST-L
TERRACE ESCARPMENTS BR
TERRIL SANDY LOAM, SANDY SUBSTRATUM SL
UDIFLUVENTS UL
UDIPSAMMENTS UL
UDIPSAMMENTS, CUT AND FILL LAND FILL
UDIPSAMMENTS, PITS, GRAVEL COMPLEX GR-PIT
UDIPSAMMENTS-LAKE BEACHES, SANDY COMPLEX UL
UDIPSAMMENTS-PITS, GRAVEL COMPLEX GR-PIT
UDORTHENTS UL
UDORTHENTS, LOAMY UL
UDORTHENTS, LOAMY (CUT AND FILL LAND) FILL
UDORTHENTS, MODERATELY SHALLOW UL
UDORTHENTS, NEARLY LEVEL TO ROLLING UL
UDORTHENTS, SLOPING UL
UDORTHENTS, VERY STEEP UL
UDORTHENTS, WET SUBSTRATUM UL
UDORTHENTS, WET SUBSTRATUM (FILL LAND) FILL
UDORTHENTS, WET SUBSTRATUM (FILL LANDS) FILL
UDORTHENTS-PITS COMPLEX PIT
UDORTHENTS-PITS, COMPLEX PIT
UDORTHENTS-PITS, GRAVEL COMPLEX GR-PIT
UDORTHENTS-PITS, GRAVEL, COMPLEX GR-PIT
URBAN AREAS UL
URBAN LAND UL
URBAN LAND, 0 TO 2 PERCENT SLOPES UL
URBAN LAND-FINCHFORD COMPLEX UL
WATER WAT
WATER, MISCELLANEOUS WAT
WILDWOOD MUCK, PONDED MUCK
WYKOFF GRAVELLY LOAM, 6 TO 12 PERCENT SLOPES, MODERATELY ERODED GR-L
ZIM SILTY CLAY LOAM SICL

 

 

Table B.27: Texture Class Reassignments for all Records Initially Classified as VAR.

Texture Class Assigned Map unit name
UL UDORTHENTS, LOAMY, CUT AND FILL LAND
ALL ALLUVIAL LAND, OCCASIONALLY FLOODED
ALL ALLUVIAL LAND, GENTLY SLOPING
MPT HAPLAQUOLLS AND UDIFLUVENTS, LEVEL
AQ AQUOLLS AND HISTOSOLS, PONDED
UL UDORTHENTS-PITS, GRAVEL COMPLEX
ALL ALLUVIAL LAND
ALL ALLUVIAL LAND, OCCASIONALLY FLOODED
ALL ALLUVIAL LAND, OCCASIONALLY FLOODED

 

 

 

Table B.28 Suitability of Soil Texture Classes for Archaeological Sites.

Texture Class Description Suitability
ALL Alluvium 7
AQ Ponded or wet 2
B Beaches 10
BL Loamy beaches 10
BR Rough, broken land; steep land; stony land 5
BS Sandy beaches 10
BY-L Bouldery loam 4
BY-LCOS Bouldery loamy course sand 4
BY-SCL Bouldery sandy clay loam 4
C Clay 7
CB-FSL Cobbly fine sandy loam 5
CB-L Cobbly loam 5
CB-SICL Cobbly silty clay loam 5
CB-SIL Cobbly silty loam 5
CB-SL Cobbly sandy loam 5
CL Clay loam 3
CN-SIL Channery silt loam 3
COS Coarse sand 8
COSL Coarse sandy loam 8
CSL Clay, sand, loam complex 9
DUMP Dump 1
DUNE Dune 8
FB Peat 2
FILL Fill land 1
FL-L Flaggy loam (steep rocky land) 5
FL-SIL Flaggy silt loam 5
FL-SL Flaggy sandy loam 5
FS Fine sand 9
FSL Fine sandy loam 9
GR-COS Gravelly coarse sand 6
GR-COSL Gravelly coarse sandy loam 6
GR-FSL Gravelly fine sandy loam 6
GR-L Gravelly loam 6
GR-LCOS Gravelly loamy coarse sand 6
GR-LS Gravelly loamy sand 6
GR-PIT Gravel pit 6
GR-S Gravelly sand 6
GR-SL Gravelly sandy loam 6
HM Mucky peat 2
L Loam 9
LCOS Loamy coarse sand 9
LFS Loamy fine sand 9
LS Loamy sand 9
LVFS Loamy very fine sand 9
MK-CL Mucky clay loam 2
MK-L Mucky loam 2
MK-LFS Mucky loamy fine sand 2
MK-LS Mucky loamy sand 2
MK-SIC Mucky silty clay 2
MK-SICL Mucky silty clay loam 2
MK-SIL Mucky silt 2
MK-SL Mucky sandy loam 2
MK_L Mucky loam 2
MPT Mucky peat 2
MUCK Muck 2
PEAT Peat 2
PIT Pits, borrow pits, borrow land  
S Sand 9
SCL Sandy clay loam 9
SIC Silty clay 9
SICL Silty clay loam 9
SIL Silt loam 9
SL Sandy loam 9
SP Peat or muck over sand 2
ST-CL Stony clay loam 5
ST-FSL Stony fine sandy loam 5
ST-L Stony loam 5
ST-LFS Stony loamy fine sand 5
ST-MUCK Stony muck 5
ST-SICL Stony silty clay loam 5
ST-SL Stony sandy loam 5
STV-L Very stony loam 5
UL Urban land, made land 1
UWB Outcrop/quarry 1
VFSL Very fine sandy loam 9
WAT Water 2

 

 

 

Table B.29: Mean Values of Numeric Variables for Textural Classes, Added to Records with NODATA for these Variables.

Texture Class # of Records Corrected AvDepth AvClay AvAWC AvOM AvPh AvPerm
ALL 38 41 14 0.18 0.6 7.3 4.25
AQ 6 40 0 0 0 0 3.30
BS 6 60 8 0.08 0 0 4.00
C 1 11 51 0.16 4.7 7.2 .25
CB-L 1 11 21 0.16 3.8 7.2 1.30
FILL 4 60 9 0.10 0.8 7.8 3.65
FSL 2 10 11 0.16 3.0 6.5 3.72
GR-PIT 41 51 9 0.09 0.8 7.5 5.12
L 7 12 20 0.20 3.7 6.8 1.73
LFS 4 10 7 0.11 2.0 6.2 1.186
MPT 3 14 0 0.48 73.4 5.8 4.49
MUCK 22 18 1 0.42 63.7 6.2 3.07
PEAT 1 31 0 0.59 75.3 3.7 13.00
PIT 6 60 10 0.11 0.8 7.8 3.30
SCL 4 11 23 0.19 4.6 7.3 1.40
SICL 9 15 32 0.20 6.2 7.1 0.90
SIL 7 12 20 0.22 3.5 6.6 1.37
SL 3 10 11 0.15 2.8 6.4 3.84
ST-FSL 1 6 12 0.16 1.1 6.0 4.00
ST-L 2 6 17 0.17 4.2 6.4 1.74
UL 24 53 9 0.11 0.9 7.6 4.79
UWB 13 0 0 0 0 0 0

 

 

 

Table B.30: Mean Values of AvClay for Textural Classes, Added to Records with NODATA for this Variable.

Texture Class # Records Corrected AvClay
ALL 1 14
AQ 1 14
FB 12 0
FSL 2 11
HM 7 0
L 2 20
LFS 1 7
MK_L 1 16
MPT 49 0
MUCK 217 1
PEAT 14 0
SICL 1 32
SIL 2 20
SL 2 11
SP 36 1
ST-MUCK 1 1
UWB 5 0
VFSL 1 12

 

 

 

Table B.31 Mean Values of AvAWC for Textual Classes, Added to Records with NODATA for this Variable.

Textural Class # of Records Corrected AvAWC
ALL 1 0.18
AQ 2 0.18
L 1 0.20
MPT 4 0.48
MUCK 1 0.42
SP 1 0.41
UWB 4 0
VFSL 1 0.19

 

 

 

Table B.32 Mean Values of AvOM for Textual Classes, Added to Records with NODATA for this Variable.

Texture Class # of Records Corrected AvOM
ALL 6 0.6
AQ 2 0.6
BS 1 1.6
FILL 1 0.8
GR-L 3 3.4
GR-PIT 3 0.8
GR-S 1 1.6
L 1 3.7
LS 3 2.1
MPT 4 73.4
MUCK 1 63.7
S 17 1.6
SIL 2 3.5
SP 2 65.6
UL 1 0.9
UWB 4 0
VFSL 1 2.8

 

 

 

Table B.33 Mean Values of AvPh for Textural Classes, Added to Records with NODATA for this Variable.

Textural Class # of Records Corrected AvPh
FILL 1 7.8
GR-PIT 2 7.5
GR-S 1 6.5
L 1 6.8
LS 3 6.1
MPT 4 5.8
MUCK 2 6.2
S 4 6.5
SP 1 6.4
UL 1 7.2
UWB 4 0
VFSL 1 6.5

 

 

 

Table B.34 Attributes of SOILS grid

VALUE Numeric code from EPPL7 data.
MAPUNIT† The soil type’s index from the NRCS database SOILDAT
SOILCODE† The soil type’s index from the NRCS database SOILDAT
MUSYM_C† The soil type’s index from the NRCS database SOILDAT
MUNAME_C The soil type’s description, including other data such as erodibility or slope.
HYDCRIT_C A value (assigned by NRCS) denoting the criteria by which a soil qualifies to be classified as "hydric".
HYDRIC A numeric value (0 or 1001) assigned indicating which soils are hydric soils by the criteria used for this project. Criteria included all soils classified as hydric by NRCS except those classified only according to hydric criterion 2B3. Excluded soils are those in qualifying soil orders that are poorly drained or very poorly drained and have a frequently occurring water table at less than 1.5 feet from the surface for a significant period (usually more than 2 weeks) during the growing season if permeability is less than 6.0 in/h in any layer within 20 inches. Soils classified as hydric must have a frequently occurring water table less than one foot from the surface for a significant period.
MUID_C A combination of the county code and MUSYM_C. It is a unique identifier for each soil map unit within the state, just as MUSYM_C is a unique identifier within the county.
CNTYCODE_C County FIPS code.
AVDEPTH Mean depth to the lower boundary of the surface layer, expressed in inches
TEXTURE Soil texture class (see Table B.8).
AVCLAY Mean value for clay content of the surface layer, expressed as a percentage of the material less than 2 mm in size.
AVAWC Mean value for the available water capacity for the surface layer, expressed as inches/inch. This value is multiplied by 100 for the grid so that the data can be stored as integers.
AVOM Mean value for organic matter content of the surface layer expressed in percent by weight. This value is multiplied by 10 for the grid so that the data can be stored as integers.
AVPH Mean soil reaction (pH) for the surface layer, expressed as pH units. This value is multiplied by 10 for the grid so that the data can be stored as integers.
AVPERM Mean permeability rate of the surface layer, expressed as inches per hour. This value is multiplied by 100 for the grid so that the data can be stored as integers.
SITESUIT Suitability of soil for archaeological sites, based on soil texture classes. Values range from 1 (low suitability) to 10 (high suitability). This was a subjective classification developed by a project archaeologist.

†These three variables are redundant, but sometimes the cases don’t match.

 

 

 

Table B.35 Values for M_VEG Grid

Value

Value Description

0

UNCODED

1

PRAIRIE

2

WET PRAIRIES, MARSHES AND SLOUGHS

3

BRUSH PRAIRIE

4

ASPEN-OAK LAND

5

OAK OPENINGS AND BARRENS

6

BIG WOODS

7

RIVER-BOTTOM FOREST

8

ASPEN-BIRCH (Hardwood)

9

MIXED HARDWOOD AND PINE

10

WHITE PINE

11

WHITE AND NORWAY PINE

12

JACK PINE BARRENS AND OPENINGS

13

PINE FLATS

14

ASPEN-BIRCH (Conifer)

15

CONIFER BOGS AND SWAMPS

16

OPEN MUSKEG

17

LAKES

 

 

 

Table B.36 Attribute values for T_VEG Coverage and Correspondence to Symbols on Source Maps

SYMBOL ON SOURCE MAP DESC TYPE TEXT LABEL
COLOR ORANGE, WITH BLACK DOTTED LINES BETWEEN PRAIRIE AND WOODLAND PRAIRIE

1001

P
IDENTIFIED BY TEXT PRAIRIE MEADOW

1002

PMD
IDENTIFIED BY TEXT WET PRAIRIE

1003

WP
YELLOW OR WHITE, WITH IDENTIFYING TEXT MEADOW

2001

MD
WHITE AND NOT LABELED. DOTTED LINE BOUNDARY WHERE BORDER PRAIRIE. WOODED

3001

W
IDENTIFIED BY TEXT SUGAR MAPLE

3002

SM
RED RECTANBLES WITH DIAGONAL HATCHED LINES FIELD

4001

F
RED RECTANGLES TOWN

5001

T
IDENTIFIED BY TEXT RAVINE

6001

R
IDENTIFIED BY TEXT QUARRY

7001

Q
YELLOW, USUALLY WITH TEXT 'm' INSIDE OR ADJACENT MARSH

8001

M
WHITE WITH A HATCHED PATTERN OR PLAIN WHITE WITH IDENTIFYING TEXT SLOUGH

8002

SL
BROWN, MAY BE LABELED 'b' BOTTOMS

8003

B
WHITE WITH DASHED LINES FOR BOUNDARIES, LABELED WITH 's'. SWAMP

8004

S
IDENTIFIED BY TEXT OPEN SWAMP

8005

OS
BLUE LAKE

9001

L
BLUE, BUT SURROUNDED BY WATER ISLAND

9002

IS

 

 

 

Table B.37 Attribute values for T_CULT Coverage

TYPE CODE DESC
HOUSE

1001

H
CABIN

1002

C
FERRY

1003

F
FORT

1004

FO
FENCE

1005

FN
LANDING

1006

LD
MILL

1007

M
TOWNSITE

1008

TS
BARN

1009

B
BOARDING HOUSE

1010

BH
BREAKING

1011

BK
BRIDGE

1012

BR
CABIN/BREAKING

1013

CBK
CABIN/FARM

1014

CF
CATHOLIC BURIAL GROUND

1015

CBG
CHURCH

1016

CH
DAM

1017

D
FARM

1018

FM
HOUSE/CLEARING

1019

HC
HOUSE/HAY MEADOW

1020

HHM
HOTEL

1021

HO
LOGGING CAMP

1022

LC
LOG LANDING

1023

LLD
MILL SITE

1024

MS
OLD LUMBER CAMP

1025

OLC
RUINS

1026

RN
SAWMILL

1027

S
SHANTY

1028

SH
TOWHEAD

1029

T
SCHOOL HOUSE

1030

SCH
AGENCY MISSION

1031

AM
TRADING POST

1032

TP
GRAVE SITE

1033

G
ABANDONED MINE

1034

AM
GOVERNMENT BUILDING

1035

GB
WAREHOUSE

1036

WH
WHARF

1037

WF
TIMBER CUT FOR SAW LOGS

1038

TCL
POST OFFICE

1039

PO
LOGGING DAM

1040

LGD
CABIN/BARN

1041

CB
LEVEE

1042

L
WAREHOUSE/DWELLING HOUSE

1043

WDH
PLOWING

1044

P
STOCKYARD,STABLES,HOUSE

1045

SSH
STORE

1046

ST
HOUSE/CABIN

1047

HB
INDIAN VILLAGE

2001

IV
INDIAN SUGAR CAMP

2002

IS
INDIAN AGENCY

2003

IAG
INDIAN CORN FIELD

2004

ICF
INDIAN FIELD

2005

IF
INDIAN FIELD AND HOUSE

2006

IFH
INDIAN HAY MEADOW

2007

IHM
INDIAN LOGGING CAMP

2008

ILC
INDIAN SETTLEMENT

2009

IST
INDIAN CHIEFS HOUSE

2010

ICH
INDIANS FAVORITE CAMPGROUND

2011

IFC
INDIAN WIGWAM

2012

IW
INDIAN WIGWAM & FIELDS

2013

IWF
INDIAN CHIEFS WIGWAM

2014

ICW
INDIAN LOG HOUSE

2015

ILH
INDIAN HOUSE

2016

IH
INDIAN HOUSE AND CLEARING

2017

IHC
INDIAN FIELD AND BURIAL GROUND

2018

IFBG
INDIAN FORTRESS

2019

IFRT
INDIAN MOUND

2020

IM
INDIAN BURIAL GROUNDS

2021

IBG
INDIAN SUMMER CAMP

2022

ISC

 

 

 

Table B.38 Attribute values for T_RDS Coverage and Correspondence to Symbols on Source Maps

SYMBOL ON SOURCE MAP DESC TYPE

Solid black line overlaid by a solid red line

ROADS

1001
Linear features represented by a solid red line, with no underlying black line.

POSSROADS

1002
Dashed black lines overlaid by solid red lines. Portages are also included

TRAILS

2001
Railroad symbol. If a trail was located on a old railroad bed, it was identified as a railroad (that is, railroads took precedence over trails).

RR

3001
These are lines where the track apparently had not yet been laid down. They are labeled on the Trygg maps as a railroad survey lines.

RRSURVEY

3002

 

 

 

Table B.39 Attributes of TR_CLAIM Coverage

TYPE CODE DESC
SETTLERS CLAIM

3001

SC
TOWN SITE

3002

TS
CLAIMS

3001

C

 

 

 

Table B.40 Environmental Variables Used in Mn/Model

Variables

Phase 1

Phase 2

Phase 3

Absolute elevation (ABL)

X

X

X

Prevailing orientation (BLG)

X

X

X

Height above surroundings (HT90)

X

X

X

Solar Insolation (INSOL)

X

X

 
Relative elevation within a 90 meters (REL90A)

X

X

X

Surface roughness (RGH90)

X

X

X

Slope (SLP)

X

X

X

Distance to the edge of the nearest large lake (DED_BLK1)

X

X

X

Distance to the edge of the nearest large wetland (DEDBWET1)

X

X

X

Distance to edge of nearest lake, wetland, or area of organic soil (DED_COR)

X

X

 
Distance to edge of nearest lake, wetland, area of organic soil, or stream (DED_CORS)

X

X

X

Distance to edge of nearest lake (DED_LK1)

X

X

 
Distance to edge of nearest marsh (DED_MRSH)

X

X

 
Distance to edge of nearest river (DED_NWIR)

X

X

 
Distance to edge of nearest permanent lake (DED_PLK1)

X

X

 
Distance to edges of nearest perennial river (DED_PRIV)

X

X

X

Distance to edge of nearest river or stream (DED_RIV)

X

X

 
Distance to edge of nearest swamp (DED_SWM)

X

X

X

Distance to edge of nearest wetland (DED_WET1)

X

X

 
Distance to nearest intermittent stream (DINT)

X

X

X

Distance to nearest perennial streams (DPER)

X

X

 
Distance to nearest lake or wetland inlet/outlet (INOUT)

X

X

 
Distance to nearest lake inlets/outlet (LK_INOUT)

X

X

X

Distance to permanent lake inlet/outlet (LKPINOUT)

X

X

X

Distance to confluences between perennial streams and double line rivers (PER_CONF)

X

X

 
Distance to confluences between perennial and intermittent streams and double line rivers (RIV_CONF)

X

X

X

Distance to confluences between streams of different classes (STR_CONF)

X

X

 
Distance to wetland inlet/outlets (WT_INOUT)

X

X

 
Distance to permanent wetland inlet/outlets (WTPINOUT)

X

X

X

Distance to nearest major ridge or divide (DIS_MAJ)    

X

Distance to nearest minor ridge or divide (DIS_MIN)    

X

Direction to nearest permanent water (DIR_PWAT)

X

X

 
Direction to nearest water (DIR_WAT)

X

X

 
Direction to nearest water or wetland (DIR_WW)

X

X

X

Size of nearest lake (LK1_SIZE)

X

X

X

Size of nearest permanent lake (PLK1SIZE)

X

X

X

Size of major watershed (MAJ_AREA)    

X

Size of minor watershed (MIN_AREA)    

X

Vertical distance to nearest water (VAW1)

X

X

X

Vertical distance to nearest permanent water (VPW1)

X

X

X

Distance from well-drained soils (D_DRA30)

X

X

X

Distance to edge of nearest large area of organic soils (DED_BO30)

X

X

 
Distance to edge of nearest area of organic soils (DED_OR30)

X

X

X

Soil drainage (DRAIN30)

X

X

 
Distance to edge of nearest hydric soils (DED_HYD)

P

X†

 
Distance to edge of nearest large area of hydric soils (DED_BHYD)

P

X†

 
Distance to edge of nearest lakes, wetlands, or hydric soils (DED_CHY)

P

X†

 
Distance to edge of nearest lakes, wetlands, hydric soils, or streams (DED_CHYS)

P

X†

 
Soil depth (SOILDEP)  

X†

 
Clay content (CLAY)  

X†

 
Available water holding capacity (AWC)  

X†

 
Organic matter content (ORGMAT)  

X†

 
Soil pH (SOIL_PH)  

X†

 
Soil permeability (PERMEABL)  

X†

 
Soil suitability for archaeological sites (SITESUIT)  

X†

 
Soil diversity within 510 meters (SLDIV510)

P

   
Soil diversity within 90 meters (SLDIV90)

P

   
Soil diversity within 990 meters (SLDIV990)

P

   
Mine pits and dumps (MINES)

X

X

 
Susceptibility to sedimentation (SED)

X

X

 
Susceptibility to erosion by water (WAT_ERO)

X

X

 
Susceptibility to wind erosion (WND_ERO)      
On alluvium (ALLUV)

X

X

X

On colluvium (COLL)

X

X

 
On lake sediment (LK_SED)

X

X

 
Distance to glacial lake sediment (DIS_LKSED)

X

X

X

On peat (PEAT)

X

X

 
On terraces (TERR)

X

X

X

Distance to Marschner aspen woodland (DIS_AS)

X

   
Distance to woods (DIS_WOOD)

X

X

 
Distance to Big Woods (DIS_BW)

X

X

X

Distance to oak woodland (DIS_OK)

X

X

X

Distance to river bottom forest (DIS_RB)

X

X

X

Distance to prairie (DIS_PR)

X

X

X

Distance to brushland (DIS_BR)  

X

X

Distance to aspen-birch (DIS_ASBI)  

X

X

Distance to mixed hardwood and pine (DIS_MIX)  

X

X

Distance to pine forest (DIS_PINE)  

X

 
Distance to pine barrens, openings, and flats (DIS_PIBF)  

X

X

Distance to conifers (DIS_CON)  

X

X

Distance to hardwood forest (DIS_HDW)  

X

X

Vegetation diversity within 1/2 km (MRDIV510)

X

X

 
Vegetation diversity within 1 km (MRDIV990)

X

X

X

Distance to kentuky coffee tree (DIS_KEN)

X

X

 
Distance to paper birch (DIS_BIR)

X

X

 
Distance to sugar maple (DIS_MAPL)

X

X

 
Distance to cranberry (DIS_CRAN)

X

X

 
Distance to paper birch (DIS_PAP)    

X

Distance to sugar maple (DIS_SUG)    

X

Distance to beaver sites (DIS_BEAV)  

X‡

 
Distance to the grassland (DIS_GRS)

X‡

X‡

 
Distance to wild rice site (DIS_RICE)  

X‡

 
Distance to woodland (DIS_WDS)

X‡

X‡

 
Vegetation diversity within 1/2 km (TRDIV510)

X‡

X‡

 
Vegetation diversity within 1 km (TRDIV990)

X‡

X‡

 
Distance to Native American cultural features (DIS_IND)

X‡

X‡

 
Distance to historic roads and trails (DIS_RTS)

X‡

X‡

 
Distance to junctures of roads and water (RD_WAT)

X‡

X‡

 
Distance to bedrock exposures (DIS_ROCK)    

X

Depth to bedrock outcrops (DEPTH30)  

X

 

P - Nicollet County Pilot only
- Soil enhanced models only
‡ - Trygg enhanced models only

 

 

 

Table B.41 Values Used for Solar Altitude (SA) in each Archaeological Region

REGION SOLAR ALTITUDE (sa)
Southeast Riverine 22.5
Prairie Lakes 22.0
Southwest Riverine 22.5
Central Lakes Deciduous 21.0
Central Lakes Coniferous 19.5
Red River Valley 19.5
Northern Bog 18.5
Border Lakes 18.5
Lake Superior 19.0

 

 

 

Table B.42 Variables Transformed for Phase 3 Modeling

Grid Name Variable
RDDRA30 Square root of Distance to well-drained soils
RDEDCORS Square root of Distance to nearest lake, wetland, organic soil or stream
RDEDOR30 Square root of Distance to edge of nearest area of organic soils
RDEDBLK1 Square root of Distance to edge of nearest large lake
RDEDBWET Square root of Distance to edge of nearest large wetland
RDEDPRIV Square root of Distance to edge of nearest perennial river or stream
RDEDSWM Square root of Distance to edge of nearest swamp
RDINT Square root of Distance to nearest intermittent stream
SDIRWW Sine of Direction to nearest water or wetland
RDISASBI Square root of Distance to aspen-birch
RDISBR Square root of Distance to brushlands
RDISBW Square root of Distance to Big Woods
RDISHDW Square root of Distance to hardwoods
RDISMAJ Square root of Distance to nearest major ridge or divide
RDISMIN Square root of Distance to nearest minor ridge or divide
RDISPAP Square root of Distance to paper birch
RDIDPIBF Square root of Distance to pine barrens or flats
RDISRB Square root of Distance to river bottom forest
RDISROCK Square root of Distance to bedrock used for tools
RDISSUG Square root of Distance to sugar maple
RDISCON Square root of Distance to conifers
RDISLKSE Square root of Distance to glacial lake sediment
RDISMIX Square root of Distance to mixed hardwoods and pine
RDISOK Square root of Distance to oak woodland
RDISPR

Square root of Distance to prairie

RLK1SIZE Square root of Size of nearest lake
RLKINOUT Square root of Distance to nearest lake inlet/outlet
RLKPINOU Square root of Distance to nearest permanent lake inlet/outlet
RMAJAREA Square root of Size of major watershed
RMINAREA Square root of Size of minor watershed
RPLK1SIZ Square root of Size of nearest permanent lake
RRIVCONF Square root of Distance to nearest confluence between perennial or intermittent streams and large rivers
RWTPINOU Square root of Distance to nearest permanent wetland inlet/outlet

 

 

 

Table B.43 Model Input Form for Logistic Regression in S-Plus

Model run unique identifier Identity code assigned to models, using predetermined naming convention
Subregion(s) modeled Name of ECS subregion or combined subregions being modeled
Date Date model run
Modeler Name of person performing modeling
Dataset used Name of sample file used to create dataset (surv01, half01, jack01, allsite, allsurv, etc.).
Number of sites The number of sites (or surveyed places) in the dataset. This can be determined in S-Plus by issuing the command sum(gps#).
Type of sites used No single artifacts, no lithic scatters, all sites and negative points, only bison kills, etc.
Number of nonsites sum(ns#) Number of nonsites in the dataset. This can be determined in S-Plus by issuing the command sum(ns#).
Type of nonsites used Random points or negative survey locations
Areas excluded Types of areas not modeled (water, mines, steep slopes, undersurveyed areas, etc.)
Variables used All Phase 2, all Phase 3, all Phase 3 except "on alluvium," etc.
Other Any other comments about the model or dataset that may be important.

 

 

 

Table B.44 Model Results Form for Logistic Regression in S-Plus

Subregion(s): Name of region being modeled Model Run Identifier: Unique name of model run according to project naming conventions
Date: Date model is run Model Number: Rank of model assigned by S-Plus
Modeler: Person performing modeling
Intercept N.A. N.A. N.A. Coefficient of variable 0
ln(nonsites/sites) Calculated from model input N.A. N.A. N.A.
Variable 1 Column for locating variable in S-Plus database Regression coefficient as reported by S-Plus Probne0 reported by S-Plus N.A.
Variable 2 Column for locating variable in S-Plus database Regression coefficient as reported by S-Plus Probne0 reported by S-Plus N.A.
Variable 3 Column for locating variable in S-Plus database Regression coefficient as reported by S-Plus Probne0 reported by S-Plus N.A.
Variable 4 Column for locating variable in S-Plus database Regression coefficient as reported by S-Plus Probne0 reported by S-Plus N.A.
Variable 5 Column for locating variable in S-Plus database Regression coefficient as reported by S-Plus Probne0 reported by S-Plus N.A.
RMS Error Reported by GRID regression Chi-Square Reported by GRID regression

 

 

 

Table B.45 Variations of Model Grids in Phase 3

Subsection Problem Variance from Standard Methods Model Affected
The Blufflands Slice could not create 20 classes for S01_1_20. MODS01_1 = int(mod1 * 1,000,000) MODS01_1
Rochester Plateau Slice could not create 20 classes for S01_1_20. MODS01_1 = int(mod1 * 10,000,000) MODS01_1
St. Croix Moraine and Outwash Plain

Low probabilities resulted in low range of model values for H01_1 model. Slice did not result in 20 classes.

Even after multiplying with 10,000,000 slice yielded only 14 classes. Proceeded with 14 classes.

 

ModH01_1 = int(mod1 * 10,000,000)

 

MODH01_1
St. Croix Moraine and Outwash Plain

Low probabilities resulted in low range of model values for H02_1 model. Slice did not result in 20 classes.

Even after multiplying with 1,000,000 slice yielded only 15 classes. Proceeded with 15 classes.

 

ModH02_1 = int(mod1 * 1,000,000)

MODH02_1
Oak Savanna - St. Croix Moraine and Outwash Plain

Low probabilities resulted in low range of model values for S01_1 model.

An intercept of 20 was used instead of the value obtained from grid regression in sumgrd to get 20 classes.

ModS01_1 = int(mod1 * 1,000,000) S01_1_20
Oak Savanna - St. Croix Moraine and Outwash Plain No intercept was used in sumgrd to get 20 classes for V_1_3, since using the value obtained from grid regression did not result in 20 probability classes.   V_1_3
Anoka Sand Plain Low probabilities resulted in low range of model values for first Half1 model. Slice could not create 20 classes. MODH01_1 = INT(MOD1 * 100,000) MODH01_1
Red River Prairie Sumgrd and Mod1 are affected by the large intercept obtained from GRID regression. Used 5.619 instead of 335.619 as intercept to calculate sumgrd. When converting integer to floating point add 330 to make raw values comparable. T01_1
Pine Moraines and Outwash Plains   MODT_n = INT(MOD1 * 100,000) MODT_1 and MODT_2
Border Lakes   MODT_1 = INT(MOD1 * 1,000,000) MODT_1
Laurentian Highlands  

MODH01_1 = INT(MOD1 * 1,000,000)

MODH01_1
St. Louis Moraines and Tamarack Lowlands   MODH02_1 = INT(MOD1 * 1,000,000) MODH02_1
Great Lake Superior Plain MOD1 of first Half1 model has only values of 1.00. Slice could only create 1 class. Model process stopped.    
Great Lake Superior Plain MOD1 of second Half1 model has only values of 1.00. Slice could only create 1 class. Model process stopped.    
Great Lake Superior Plain Low Probabilities resulted in low range of model values for first Half2 model. Slice could not create 20 classes.

Even after multiplying with 100,000,000 the slice yielded 12 classes (when multiplying with 1,000,000,000, slice yielded same 12 classes). Proceeded with 12 classes for the region

MODH02_1 = INT(MOD1 * 100,000,000) MODH02_1
Great Lake Superior Plain Low Probabilities resulted in low range of model values for second Half2 model. Slice could not create 20 classes.

Even after multiplying with 1,000,000,000 the slice yielded 8 classes (when multiplying with 10,000,000,000, slice yielded same 8 classes). Proceeded with 8 classes for the region

MODH02_2 = INT(MOD1 * 1,000,000,000) MODH02_2
Inner Coteau Slice could not create 20 classes for H01_1_20. MODH01_1 = int(mod1 * 10,000,000) MODH01_1
Agassiz Lowlands Low Probabilities resulted in low range of model values for first Half1 model. Slice could not create 20 classes.

Even after multiplying with 10,000,000 the slice yielded 11 classes. Proceeded with 11 classes for the region.

MODH01_1 = INT(MOD1 * 10,000,000) MODH01_1
Littlefork Vermillion Uplands Low Probabilities resulted in low range of model values for first Half1 model. Slice could not create 20 classes.

Even after multiplying with 1000,000 the slice yielded 18 classes. Proceeded with 11 classes for the region

MODH01_1 = INT(MOD1 * 1,000,000) MODH01_1
Littlefork Vermillion Uplands Even after multiplying with a 1,000,000 slice resulted in only 4 classes. Proceeded with 4 classes. MODH02_1 = INT(mod2 * 1,000,000) MOD20_2 for HALF2
Agassiz Lowlands - Littlefork Vermillion Uplands Low Probabilities resulted in low range of model values for first Half1 model. Slice could not create 20 classes. MODH01_1 = INT(MOD1 * 100,000) MODH01_1
Agassiz Lowlands - Littlefork Vermillion Uplands Low Probabilities resulted in low range of model values for first Allsite model. Slice could not create 20 classes. MODT_1 = INT(MOD1 * 10,000,000) MODT_1

 

 

 

Table B.46 Phase 2 Model Classification Form

Model: Name of model according to Phase 2 naming conventions Subregion(s): Subregion or combination of subregions modeled
Modeler: Name of person performing modeling Date Date modeled
Class Modeled Sites Other Sites (of type modeled) All Sites (of the type modeled) - sum of n1 and n2
1 0 Low 1 Low 1 Low
2 1 Low 4 Low 5 Low
3 0 Low 5 Low 5 Low
4 2 Low 8 Low 10 Low
5 0 Low 10 Low 10 Low
6 1 Low 12 Low 13 Low
7 1 Low 14 Low 15 Medium
8 2 Low 16 Medium 18 Medium
9 0 Low 7 Medium 7 Medium
10 2 Low 17 Medium 19 Medium
11 3 Low 15 High 18 High
12 0 Medium 11 High 11 High
13 1 Medium 7 High 8 High
14 0 Medium 2 High 2 High
15 3 Medium 19 High 22 High
16 0 Medium 13 High 13 High
17 2 Medium 21 High 23 High
18 5 Medium 22 High 27 High
19 19 High 53 High 72 High
20 35 High 28 High 63 High
21 0 Water 0 Water 0 Water
22 0 Steep Slopes 0 Steep Slopes 0 Steep Slopes
23 0 Mines 0 Mines 0 Mines
TOTAL 77
-
285
-
362
-

 

 

 

Table B.47 Phase 2 Worksheet for Model Classification

Model: Name of model according to Phase 2 naming conventions Subregion(s): Name of subregion modeled
Modeler: Name of person performing the classification Date: Date classification performed
ax = 70% of sites (0.7 * TOTAL nx)

53.9

253.4
bx = 85% of sites (0.85 * TOTAL nx)
65.45
307.7
cx = # sites closest to 70% nx
54
259
dx = # classes containing cx (label these HIGH in Prob Class)
2
9

ex = estimated % area in high probability (5 * dx)

10%
45%
fx = # of all known sites (column n3) in high probability area
135

259

gx = % of all known sites in high probability area (fx/(n3 TOTAL))
37%
71.5%
hx = Estimated gain statistic for high probability areas (1 - (ex/gx))
0.7297
0.3706
ix = # sites closest to 85% nx
65
318
jx = # classes containing ix (If classes in this group are not labeled HIGH, label them MED)
9
13
kx = Estimated % area in high/med probability (5 * jx)
45%
65%
lx = # of all known sites (column n3) in high/med probability area
106
318
mx = % of all known sites in high/med probability area (lx/(n3 TOTAL))
29.3%
87.8%
nx = Estimated gain statistic for high/med probability areas (1 - (kx/mx))
0.5358
0.2597

3+

 

 

 

Table B.48 Reclassification Table for Deriving Final Probability Models

Old Class New Class Description
1 -11 1 Low Probability
12 - 18 2 Medium Probability
19 - 20 3 High Probability
21 21 Water
22 22 Steep Slopes
23 23 Mines

 

 

 

Table B.49 Phase 3 Model Classification Form

Model Distribution Among 20 Probability Classes
Subsection(s): Name of subsection or combination of subsections modeled Date: Date modeled
Model: Name of model, according to Phase 3 naming conventions Modeler: Name of person performing the modeling
1 1 527 95.126
2 3 526 94.946
3 1 523 94.404
4 2 522 94.224
5 1 520 93.863
6 5 519 93.682
7 2 514 92.78
8 5 512 92.419
9 9 507 91.516
10 6 498 89.892
11 7 492 88.809
12 11 485 87.545
13 14 474 85.56
14 19 460 83.062
15 37 441 79.603
16 32 404 72.924
17 40 372 67.148
18 72 332 59.928
19 114 260 46.931
20 146 146 26.354
21 Water 0 0 0
22 Steep Slopes 27 0 0
23 Mines 0 0 0
TOTAL 554
-
-

 

 

 

Table B.50 Phase 1 Model Evaluation Form

  Low Medium High Total % High/Medium
Area modeled 7,811,677 7,585,202 7,569,929 22,966,808  
34% 33% 33%   66%
Negative Survey Points 337 435 419 1291  
26% 34% 40%   74%
Modeled Sites 1 26 120 147  
0.5% 18% 82%   99%
Other Sites 14 69 255 338  
4% 20% 75%   96%
Single Artifacts 3 14 30 47  
6% 30% 64%   94%
All sites except single artifacts 15 95 375 485  
3% 20% 77%   97%
All sites including single artifacts 18 109 405 532  
3% 20% 76%   97%

 

 

 

Table B.51 Phase 3 Model Evaluation Form

Model Distribution Among Three Probability Classes
Subregion: Name of subregion modeled Date: Date of modeling
Model: Name of model according to Phase 3 naming conventions Modeler: Name of person performing modeling
Subregion #
2800159
933445
933310
109837
656230
0
5432981
-
  %
51.54
17.18
17.18
2.02
12.08
0
100
19.20
Negative Survey Points #
150
122
468
4
29
0
773
-
  %
19.4
15.78
60.54
0.52
3.75
0
100
76.32
Modeled Sites (training data) #
20
42
190
0
11
0
263
-
  %
7.6
15.97
72.24
4.18
100
88.21
Other Sites (test data) #
33
60
182
16
291
-
  %
11.34
20.62
62.54
0
5.5
0
100
83.16
All known sites of the type modeled #
53
102
372
0
27
0
554
-
  %
9.57
18.41
67.15
0
4.87
0
100

85.56

GAIN (high/medium):

0.59841

GAIN (high only):

0.74416

 

 

 

Table B.52 RMS-error, Chi-square,and P-values for Phase 3 Models

 
Site Probability Model
Survey Probability Model
Agassiz Lowlands
0.122
115.716
9
0.0000
0.292
748.353
24
0.0000
Anoka Sand Plain
0.327
158.386
12
0.0000
0.451
438.265
11
0.0000
Aspen Parklands
0.222
354.631
20
0.0000
0.292
748.925
24
0.0000
Big Woods
0.382
337.518
16
0.0000
0.455
758.353
18
0.0000
Blufflands
0.379
251.989
14
0.0000
0.411
433.910
13
0.0000
Border Lakes
N.A†.
N.A.†
16
N.A.
0.36231
576.66229
17
0.0000
Chippewa Plains
0.296
260.789
14
0.0000
0.429
763.153
22
0.0000
Coteau Moraines/ Inner Coteau
0.315
195.508
10
0.0000
0.439
507.333
13
0.0000
Glacial Lake Superior Plain/ North Shore Highlands/ Nashwauk Uplands
0.174
98.551
14
0.0000
0.379
702.270
20
0.0000
Hardwood Hills
0.240
274.031
16
0.0000
0.392
893.042
19
0.0000
Laurentian Highlands
0.219
24.799
6
0.0004
0.290
96.151
12
0.0000
Littlefork-Vermillion Uplands
0.133
94.733
8
0.0000
0.292
748.353
24
0.0000
Mille Lacs Uplands
0.246
215.700
19
0.0000
0.395
730.593
20
0.0000
Minnesota River Prairie
0.311
472.307
17
0.0000
0.422
1172.680
17
0.0000
Oak Savanna
0.249
159.787
11
0.0000
0.469
504.268
16
0.0000
Pine Moraines & Outwash Plains
0.254
286.570
14
0.0000
0.388
839.866
16
0.0000
Red River Prairie
0.668
1856.287
15
0.0000
0.358
633.979
14
0.0000
Rochester Plateau
0.329
325.747
14
0.0000
0.665
1928.214
13
0.0000
St. Croix Moraines & Outwash Plains (Twin Cities Highlands)
0.291
78.157
5
0.0000
0.584
1264.889
17
0.0000
St. Louis Moraines/ Tamarack Lowlands
0.167
90.403
11
0.0000
0.325
416.136
19
0.0000

†GRID was unable to fit the logistic regression for this model.

 

 

 

Table B.53 Lowest Resolution Database in Phase 3 Site Probability Models by Subsections

MODELED REGION VARIABLE SITE MODEL RESOLUTION
AGLW AGLW T_LVAA 500,000
ANOK ANOK T_1_3 500,000
ASPK ASPK T_HRAS 500,000
BDLK BDLK T_1_3 500,000
BGWD BGWD T_1_3 500,000
BLUF BLUF T_1_3 500,000
CHIP CHIP T_1_3 500,000
COIC COTM T_1_3 500,000
COIC ICOT T_1_3 500,000
GNUS GLKS T_GNLN 500,000
GNUS NSHH T_GNLN 500,000
GNUS NSHU T_GNLN 500,000
HRDH HRDH T_1_3 500,000
LARH LARH T_1_3 500,000
LVUP LVUP T_AGLV 500,000
MLAC MLAC T_1_3 500,000
MNRP MNRP T_1_3 500,000
OSAV OSAV T_OSTW 500,000
PINE PINE T_1_3 500,000
PLAT PLAT T_BLPL 500,000
REDR REDR T_1_3 500,000
STTA STLS T_1_3 500,000
STTA TAML T_1_3 500,000
TWCH TWCH T_1_3 250,000

 

 

 

Table B.54 Number of Sites in Modeled Population

Subsection

Modeled Sites

All Sites/km2

ROCHESTER PLATEAU

81

0.01844

THE BLUFFLANDS

554

0.12052

ASPEN PARKLANDS

59

0.00684

ANOKA SAND PLAIN

337

0.07108

BIG WOODS

637

0.08744

HARDWOOD HILLS

470

0.02679

OAK SAVANNA

121

0.01907

TWIN CITIES HIGHLANDS (ST. CROIX MORAINES)

126

0.05599

AGASSIZ LOWLANDS

53

0.00323

LITTLEFORK-VERMILLION UPLANDS

25

0.00491

CHIPPEWA PLAINS

513

0.06543

PINE MORAINES & OUTWASH PLAINS

474

0.03598

ST. LOUIS MORAINES

112

0.03051

TAMARACK LOWLANDS

74

0.01047

BORDER LAKES

960

0.11670

LAURENTIAN HIGHLANDS

120

0.09052

NASHWAUK UPLANDS

36

0.00835

NORTH SHORE HIGHLANDS

44

0.01294

GLACIAL LAKE SUPERIOR PLAIN

6

0.01247

MILLE LACS UPLANDS

437

0.03066

COUTEAU MORAINES

220

0.03337

INNER COTEAU

130

0.03806

MINNESOTA RIVER PRAIRIE

969

0.03298

RED RIVER PRAIRIE

270

0.01610

 

 

 

Table B.55 Impact of Errors in ARCHDATA.PAT on Models

Phase 3 Modeling Region Number of eligible sites omitted from modeling Percentage of all sites Impact on model
Agassiz Lowlands
7
11.7
Significant
Anoka Sand Plain
1
0.3
Insignificant
Big Woods
11
1.0
Very small
Chippewa Plains
10
2.0
Very small
Hardwood Hills
7
1.5
Very small
Minnesota River Prairie
1
0.1
Negligible
Pine Moraines & Outwash Plains
35
6.4
Possibly significant
Blufflands
1
0.2
Negligible

 

 

 

Table B.56 Results of Logistic Regression in GRID

Variables Model 1 Model 2 Model 3 Model 4
Intercept 0 12.331 0 8.226 0 5.158 0 6.247
DED_LK1 1 -0.002 1 -0.001 1 -0.001 1 -0.002
LK1_SIZE 2 0.000     2 0.000    
DED_RIV 3 0.001 2 0.001 3 0.000    
DIR_PWAT 4 0.007 3 0.005 4 0.005 2 0.005
VPW1 5 -0.002 4 0.005        
DED_WET1 6 0.000     5 0.000    
DED_OR30 7 0.000            
LK_INOUT 8 0.000            
WT_INOUT 9 0.000            
STR_CONF 10 0.000            
D_DRA30 11 0.001 5 0.001 6 0.000    
ABL 12 0.030 6 0.030        
RMS error   0.259   0.270   0.274   0.274
Chi-Square   19.729   21.388   22.114   22.123
d.f. 12   6   6   2  
p-value   0.7121   0.0450   0.0145   0.0002

 

 

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Acknowledgements

Mn/Model was financed by the Minnesota Department of Transportation using funds set aside by the Federal Highway Administration's Intermodal Surface Transportation Efficiency Act.

 

Copyright Notice

The Mn/Model process and the predictive models it produced are copyrighted by the Minnesota Department of Transportation (MnDOT), 2000. They may not be used without MnDOT's Consent.