Bordner Survey User Guide
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1 User Guide: Wisconsin Land Economic Inventory (WLEI) Digitized Maps History and Background Information The WLEI was a comprehensive and extremely detailed mapping of Wisconsin’s counties. The genesis of the program was in the Progressive era. By the 1920s court and law rulings had clarified that states had authority for land use planning that included private lands. Following the cutover era in Northern Wisconsin, with devastated forests, burned land, and abandoned farms, the state of Wisconsin saw the need for comprehensive inventory of the land to guide planning. Field mapping started in 1928, and it was completed under WPA funding in the late 1930s. Each township was inventoried by crews traversing each section of land along the “40” lines, or every one-quarter mile. Essentially everything about the land and what was on it was mapped and described. Eventually this resulted in over 100 classes of information, from polygons of forest type and quality, to detailed classes of agricultural use, and all infrastructure features that could be identified. The survey was executed by field workers who were by and large trained foresters, with a standard accuracy of 2 chains for open country, and 4 chains (1 chain = 66’) for wild or densely wooded country. Field workers’ hand drawn maps were later adjusted with aerial photography to produce a published maps for nearly every township in Wisconsin. The published maps – often referred to as the Bordner maps named for the director of the program – have been optically scanned and are available online through the UW Libraries Digital Collections site (https://uwdc.library.wisc.edu/collections/EcoNatRes/WILandInv/). Milwaukee and Menominee Counties were not mapped. Lincoln, Manitowoc, and Sheboygan County township maps were never published. For those counties with unpublished maps, the original sketch maps were located in the Historical Archives at the Wisconsin Historical Society, and scanned. While the original published maps offer an insight to landscape features, they do not allow for complex analysis using modern technologies and techniques. Over seventy years after the last map was published, the Forest Ecosystem and Landscape Ecology Lab (FLEL) of the University of Wisconsin-Madison, Department of Forest and Wildlife Ecology has collaborated with the Wisconsin State Cartographer’s Office (SCO) to digitize the maps into a GIS dataset and make the data available to the public. This digitized dataset can help researchers and educators further understand the landscape of Wisconsin during the time of peak deforestation and land abandonment. Furthermore, this digitized dataset offers a tool for future landscape management including but not limited to; shoreline changes, erosion, reforestation, and wetland restoration. Digitization Processes and Methodology Step 1: Georeference Original Maps First part of the GIS digitization process of the Bordner survey maps was to georeference the original published township maps. Using section line intersections as a reference, these scanned maps were then georeferenced to the Department of Natural Resource’s 'Landnet' GIS database layer containing the section lines, using section line intersections as tie points. In cases where there were missing section lines on the original maps, aerial photography was used to help with geo-referencing. The maps were referenced using 2 the NAD 1983 HARN Transverse Mercator coordinate system, with the transformation “adjust”, and an output raster having a cell size of 1m. Step 2: Digitize Next the section lines for a given township were overlaid on top of the geo-referenced image using a hollow display. Polygons: Polygon features include land cover land use features, such as forest, agriculture, lakes etc. Polygon features were cut using the “Cut Polygon” editing tool by tracing the land cover land use boundary lines on the geo-referenced maps. Wacom digitizing tablets were used to increase digitization precision and speed. Lines: Linear features include roads, telephone lines, power lines, streams etc. Digitizers traced these features, and in cases where two or more features followed the same path, one line was drawn then copied and pasted to insure accuracy. Linear features that cross township borders were sometimes displaced slightly when their path didn’t match exactly between two georeferenced township maps. Points: Point features include houses, churches, cheese factories, mills, taverns etc. Digitizers place the appropriate point in the center of these features. In some cases the map indicates number of buildings in a group and/or the distance a building is located from a road, this information was also captured by the digitizers. Step 3: Assign Attributes Point and line features were attributed during the digitization process. Once all of the polygon features for a township were cut, they were each assigned an attributes reflecting the information present on the original map. Land Cover, Diameter Classes, and Density of Stand were all captured during the attribution process. Labels for water bodies and urban areas were documented in the “Notes” field when present. In cases where survey lines were unclear, or polygons were left blank, judgment calls were made using the help of aerial photography when necessary. In these instances the type of judgement call that was made was recorded in the database, often with a note explaining the judgement call in the “Notes” field. Step 4: Review Finally, when all of the survey maps for a county were digitized and attributed, they were then reviewed for quality control. This review process consisted of checking for null values, sliver and overlap of polygons (topology), diameter and percentage outliers, and an overview of the documented notes/judgment calls. After reviewing the digitization work, all of the individually digitized townships were merged for their given county and stored in a geodatabase for future processing. Additional Information Regarding the Bordner Dataset 3 ● ● ● ● ● Some land cover polygons have up to four forest cover species. In some cases the original survey maps included a percentage for polygons with more than one cover type, however in many cases they did not. The Bordner Survey was a project that took 20 years to complete. Dates for each county can be found online at: https://www.library.wisc.edu/steenbock/wisconsin-land-economic-inventory-the-bordner-survey-land-cover-m aps/. In some cases bordering counties could have over a decade between the production of survey maps. Section lines were used for the digitization process. Sometimes these lines transverse a single polygon feature, dividing it into a few smaller polygons. This can cause inaccuracies when trying to count a number of stands, or calculate average size of a stand, etc. Some maps have land cover codes that remain unknown due to fact the were absent from the legend. When a polygon was missing a land cover attribute in the original maps, historic aerial photos were used to identify whether the land cover should be attributed as either “unknown forest” or “unknown grassland”. Field Descriptions Polygons: ● Field Description Cov1 Dominant Cover Type MinDiam1 Minimum Diameter Size at Breast Height for Cov1 MaxDiam1 Maximum Diameter Size at Breast Height for Cov1 Den1 Density for Cov1 PctCov1 Percent of Stand that Cov1 Occupies (not all townships include this) Cov2 Second Most Prevalent Cover Type MinDiam2 Minimum Diameter Size at Breast Height for Cov2 MaxDiam2 Maximum Diameter Size at Breast Height for Cov2 Den2 Density for Cov2 PctCov2 Percent of Stand that Cov2 Occupies (not all townships include this) Cov3 Third Most Prevalent Cover Type MinDiam3 Minimum Diameter Size at Breast Height for Cov3 MaxDiam3 Maximum Diameter Size at Breast Height for Cov3 Den3 Density for Cov3 PctCov3 Percent of Stand that Cov3 Occupies (not all townships include this) Cov4 Fourth Most Prevalent Cover Type MinDiam4 Minimum Diameter Size at Breast Height for Cov4 MaxDiam4 Maximum Diameter Size at Breast Height for Cov4 Den4 Density for Cov4 PctCov4 Percent of Stand that Cov4 Occupies (not all townships include this) Judgement Call Confusing Line Work, Missing Attribute, Missing Line, Poor Scan/Faint Lines Notes Labels, Unique Features, Details Regarding Judgement Calls Crown Cover Dominance: ○ Cov2, Min2, Max2 etc. indicates a secondary cover within a stand, there are up to 4 different cover types within a single polygon (Cov1..., Cov2..., Cov3..., Cov4...). Dominance is determined by the relative amount of space occupied by each type in the combination. Neither the size nor the 4 ● ● ● ● number of trees alone will indicate the correct result. It must be remembered that it requires many small trees, size 0-3, to occupy as much space from the site of a single 30 inch tree. Diameter Classes: ○ The approximate age and size of the forest growth is indicated on the map, in three-inch diameter classes, by the figures in type symbol. ■ 0-3 indicates that the -majority of the trees are less than three inches in diameter. ■ 3-6 indicates that the -majority of the trees are between three and six inches in diameter. ■ 6-9 indicates that the -majority of the trees are between six and nine inches in diameter. Density indicates the relative number of trees per acre and the completeness with which they utilize the available land and light. Young forest growth in any degree of stocking will have more trees per acre than a mature stand of the same degree of stocking. ○ 1-Good Stand = Trees are so numerous that there is little to no waste of land or light, the individual trees develop small crowns and tall, clean straight bowls. Such stands need no artificial seeding or planting to obtain full use of land and light by forest growth. ○ 2-Medium Stand = Trees are less numerous and openly spaced so that there is material waste of land and light. Some of the individual trees develop rather large, irregular crowns and knotty crooked bowls. Such stands may need some natural artificial seeding or planting to obtain full use of the land and light by forest growth. ○ 3-Poor Stand = Trees are so few and scattered that there is a very considerable waste of land and light. Many individual trees develop spreading, limby crowns and short knotty trunks. Such stands need much artificial seeding or planting to obtain full use of the land and light by forest growth. ○ 4-Scattered Stand Coded Symbol First letter (eg. A1, B2, C4) generally does not represent a specific land cover type. Coded Symbol Additional Letters (eg. C4b, D1u, D1uu) ○ b = Inferior (represented on the original map as one line ABOVE the coded symbol) ○ u = Unknown (represented on the original map as one or more lines BELOW the coded symbol) ○ A, R, RS, RX, RY, X, Y, Z = All appear to be variations of agricultural cover types (eg. CPP; CPPA, CPPR, CPPRX etc.) ○ Note that b does not always indicate inferior and little to no documentation can be found to the meanings of u, uu, uuu, and uuuu. These symbols appear as a line above the Cover Code for b, and one to four lines below the Cover Code for u on the original published maps. Lines: Field Description Line_Type Indicates the type of line represented Highway_Ty Indicates the type of highway; county, state, or federal Highway_Co Indicates the highway code. County Highways represented in letters, State and Federal Highways represented as a number Notes ● ● ● ● Labels, Judgement Calls, etc. Cliff heights are indicated in the Notes field (eg. ‘60). Banks are indicated with Line_Type = CL AND Note = Bank (ex. 20-50’ Bank). When more than one Highway_Ty covers a particular stretch of road, the secondary Highway_Co is indicated in the Notes field. Other labels including Railroads and Streams are indicated in the Notes field. 5 Points: Field Description Point_Type Indicates the type of point represented Num_of_Hou Indicates the number of houses in a group Dis_to_Roa Indicates the number of feet a building is located from the center of a road Notes Labels, Judgement Calls, etc. Land Cover Descriptions UPLAND FOREST ASSOCIATIONS: Basswood, birch, maple, ash, elm -- A1 - The forest association of the better hardwood site. Maple, birch, hemlock, balsam, fir -- B1 - The more common hardwood association in Upper Wisconsin. 1. Popple and white birch predominant -- C1 (i.e.) This association may seed in on almost any site. However, the popple appears almost pure, except on gravelly rolling sites, then white birch occasionally makes up the dominant part of the association. 2. Scrub oak predominant -- B1 (i.e.) Scrub oak frequently is the survival of frequent fires on Norway and white pine sites, i.e. it is sprout growth. Red maple and white birch frequently appear with scrub oak on the less severely burned areas. 3. Cheery predominant -- E1 (i.e.) Pin or so-called “fire” cherry in some areas is the immediate succession generally of a very severe burn following the logging of virgin hardwood hemlock stands. 4. Hemlock predominant with hardwoods and balsam –- A2 (i.e.) Hemlock predominant appears in very old stands where the hardwood was either logged or where decay eliminated many of the very old hardwoods and the hemlock of the under story became dominant. (Few Remain) 5. White pine predominant with some Norway -- B2 (i.e.) The association of white pine and Norway or either with for example, hardwood, and especially C1, is generally on the better white pine sites. 6. Norway pine predominant with some Jack pine – C2 (i.e.) Where Norway is predominant the site may still be capable of producing excellent white pine but frequent fires have destroyed the less resistant white pine and left the more resistant Norway pine. 7. Jack pine predominant with some Norway pine -- D2 (i.e.) Jack pine in natural forest successions falls out of the picture, following the logging of the virgin white pine and Norway pine. Followed by frequent burns, has occupied some areas almost completely due to its fire habit and early seeding potential. LOWLAND FOREST ASSOCIATIONS: 6 8. Elm, Black Ash, Red Maple, White Pine --A3 (i.e.) This Land association is not very extensive and quite variable being found on stream bottom lands and also in so-called black ash swamps where little other than black ash appears in the stand. 9. Cedar predominant with some Tamarack, Balsam and Spruce --B3 (i.e.) This association may appear on almost any naturally wet land where drainage is sufficient to keep the soil from becoming strongly acid. 10. Tamaracks predominant with some Cedar, Balsam and Spruce --C3 (i.e.) The more poorly drained lowland sites have this association. 11. Spruce, Balsam Predominant -- D3 (i.e.) This is the least desirable of wetland. Spruce has changed from white to black and the leather leaf bog is the final succession on much of this site. MARSH AND BOG VEGETATION TYPES: 12. High Shrub Type -- A4. Alder, Willow, Red Dogwood, etc. (i.e.) Alder, willow, the red dogwood, striped maple and numerous species of the honeysuckle family, appear in this association and sometimes completely occupy the site barring the possible seeding in of forest species. However, where this is true, such disturbing bionomic factors as for example, fire and lumbering operations are primarily casual in bringing about the successions. 13. Cat Tail Marsh -- B4. Grass Meadow -- C4. (i.e.) Cat Tail marshes are not numerous but-sometimes appear where water levels have been suddenly changed by beaver dams and also by power dams. Sudden drainage or the lowering of the water table is followed by the grass meadow. 14. Leather Leaf Bog -- D4. (i.e.) The leather leaf bog is always evidence of extremely toxic soil conditions and is the final succession with the Leather (heather) vegetation dominant. OPEN WILD TYPE OF GROUND COVER: 15. Raspberries, etc. – A5. Briars, sweet fern and grass – B5 Arbutus and winter-green, Blue berry, - Bear berry -- 05. Recent burn -- D5. (i.e.) These upland ground cover associations are in general an index of site. However, in some instances fire has been such a disturbing factor, that their presence may be a final survival. Again the condition of the soil has been changed by the fires, so that for example, sweet fern and even bracken thrives better than the more tolerant heather plants such as blue berry, bear berry, arbutus and winter-green. Funding/Credits This project was a result of a joint effort of the Forest Ecosystem and Landscape Ecology Lab (FLEL) and the State Cartographer's Office (SCO). 7 Funded by the Wisconsin Coastal Management Program and the National Oceanic and Atmospheric Administration, Office for Coastal Management under the Coastal Zone Management Act, Grant #NA16NOS4190108 The Bordner digitizing project has also received funding from the University of Wisconsin-Madison Graduate School, the UW-Madison College of Agricultural and Life Sciences, Wisconsin Alumni Research Foundation Research Fund, and the Wisconsin Alumni Research Foundation Kellett Mid-Career Faculty Award. Sources Koch, John. “Touching Every Forty: John Bordner and The Wisconsin Land Economic Inventory.” Wisconsin Magazine of History, 2006, pp. 14–25. “Land Economic Inventory Maps (Bordner Survey).” Wisconsin Historical Society, 24 Aug. 2012, www.wisconsinhistory.org/Records/Article/CS3338. “Wisconsin Land Economic Inventory Maps (The Bordner Survey).” Steenbock Library, 3 Nov. 2016, www.library.wisc.edu/steenbock/wisconsin-land-economic-inventory-the-bordner-survey-land-cover-maps “Wisconsin Land Economic Inventory Mapping Instructions for Vilas County, Wisconsin.” Vilas County, Wisconsin, 1930. 8 Point Feature Count Linear Feature Count Total Length(miles) Beaver Dam 9 Abandoned Railroad 618 652 Cannery/Canning Factory 1 Bog Shoreline 107 51 Cemetery 343 Civil Town Boundary 324 329 Cheese Factory 303 Cliff 256 126 Church 275 Drainage Ditch 932 742 Drivable Fire Lane 142 321 Country Club 1 Creamery 23 Hard Surfaced Road 745 1,430 Dam 24 Improved Dirt Road 6,808 5,187 Erosion 101 Improved Gravel Road 3,115 4,975 Farm Bldg. Less than 100 ft from center of Road 210 Intermittent Stream 1,703 886 Filling Station or Garage 214 Non-Drivable Fire Lane 26 56 Fire Tower 34 Power Line 3,313 4,222 Fish Hatchery 4 Railroad 543 1,549 Fur Farm 64 Shoreline 59 39 Golf Course 11 Stream 7,130 7,030 Gravel Pit 493 Telephone Line 3,690 5,150 Greenhouse 1 Trail 1,942 1,363 Grist Mill 9 Unimproved Dirt Road 4,486 2,662 Unimproved Gravel Road 1,882 2,230 29 18 37,850 39,021 Hotel Lime Kiln 27 1 Logging Camp 43 Nursery 31 Occupied House 38,086 Occupied School 830 Orchard Post Office Quarry Ranger Station Ruins 1,972 2 34 2 1 Saw Mill 36 Ski Jump 8 Spring Store Summer House 387 192 1,754 Tavern 431 Town Hall 58 Unknown 179 Vacant House 2,273 Vacant School 20 Total 48,487 Unknown Total 9 Code Code Description Polygon Count Acres Code Code Description A Abandoned A1 Upland Hardwoods A1u A1uu A2 Hemlock with Hardwood A3 Swamp Hardwoods A3u A3uu A4 Tagalder, Willow, Dogwood, Etc. A5 Raspberries, etc. AA AA 1 AC AC 19 AO AO 2 29 AP Abandoned Pasture 764 AR AR ARPT Airport ARX ARX AX Polygon Count Acres 1,057 18,067 C1b Inferior C1 4,083 290,917 25,419 776,637 C1uu C1uu 9 294 A1u 2 28 C2 Norway Pine 1,471 47,304 A1uu 4 59 C3 Tamarack 4,460 140,392 3,048 169,314 C3uu C3uu 1 66 19,251 627,720 C3uuu C3uuu 2 9 A3u 1 48 C4 Grass Marsh 20,207 537,556 A3uu 2 27 C4b Sedge Marsh 6,132 188,866 16,955 413,815 C4u C4u 87 4,062 49 3,193 CA Camp 16 258 7 CAT Catalpa Plantation 2 7 455 CC CC 1 52 CCC CCC 6 62 18,759 CL Clay Pit 126 8,976 8 315 CM Cemetery 706 3,033 12 587 CO County Farm 1 3 1 10 CP CP 22 291 AX 2 60 CPP Poor Land Previously Cropped 2,252 63,327 AY AY 2 42 CPPA CPPA 18 745 AZ AZ CPPR CPPR B Birch B1 Hardwood with Conifers B1b 6 152 4 194 902 18,402 CPPRX CPPRX 4 78 14,005 747,841 CPPRY CPPRY 4 133 Inferior B1 710 49,307 CPPRZ CPPRZ 2 78 B2 White Pine 2,904 79,073 CPPX CPPX 32 830 B2b B2b 2 25 CPPY CPPY 9 253 B3 White Cedar 9,367 326,776 CPPZ CPPZ 7 157 B4 Cat Tail Marsh 1,086 37,299 CR CR 74 2,749 B5 Briars, sweet fern and grass 1 16 CRS CRS 1 9 BA Ball Park 1 7 CRX CRX 38 1,666 BB Blueberry 30 1,298 CRY CRY 44 2,439 BD Beaver Dam 1 3 CRZ CRZ 16 694 BE Bee Farm BF Beaver Flowage BL 1 2 CS Cultivated Stump Land 18 444 CT City Blowdown 1 17 CUT BOG Bog 3 14 BP Beaver Pond 25 BU Bluff 1 BY Brick Yard C C1 245 2,903 1,526 240,042 Cutover 30 5,521 CV Urban Property 1 7 242 Cx Cx 723 46,243 5 CY CY 251 14,165 3 24 CZ CZ 42 1,953 Cleared Cropland 57,947 5,812,310 D Scrub Oak 3,292 150,711 Popple with White Birch 39,345 2,532,490 D1 Oak - Hickory 11,162 325,243 10 Code Code Description Polygon Count Acres D1b Inferior D1 D1u Code Code Description Polygon Count Acres 8 343 MF Mud Flats 29 822 Good Quality with White Oak 1,204 31,242 MP Marl Pit 1 4 D1uu Medium Gr. Mostly Red Oak D1uuu D1uuu 3,489 144 87,983 MY Mill Yard 13 359 2,298 NF National Forest 12 5,948 D2 Jack Pine 4,684 224,413 NP NP 2 39 D3 Black Spruce 12,097 363,808 NU Nusery 35 672 D3b Balsam D3u D3u 1,486 47,814 O Open 5,556 191,979 2 45 OA OA 3 39 D4 Leather Leaf 4,746 86,395 OC OC 3 38 D4b D4b 2 19 OP Open Pasture 5 58 D5 D5b Recent Burn 1,046 83,962 OPP OPP Dead Timber 125 6,104 OR Orchard DA DA 6 279 ORB Old River Bed DH DH 1 8 P Pasture Duu Duu 4 84 P.V. Duuu Duuu E1 Pin Cherry E2 2 21 2,587 19,377 21 424 18,448 262,002 P.V. 14 110 5 46 PA PA 79 1,142 1,498 76,132 PD Public Dump 63 870 E2 1 9 PG PG 1 4 E3 E3 5 114 PK Park 26 593 E4 Weedy Peat 366 15,931 PO PO EP EP 2 15 PP Permanent Pasture ER Erosion 408 1,977 PPR F F 32 202 F4 Cranberry Marsh 31 FF Fur Farm 57 FG Fair Grounds 2 FH FH FP Forest Plantation FX Fox Farm GC 1 14 10,969 163,319 PPR 5 86 PPRX PPRX 3 74 741 PPX PPX 31 354 1,470 PPY PPY 29 408 53 PPZ PPZ 17 234 1 12 PR PR 9 78 52 789 PRX PRX 2 56 2 26 PRY PRY 3 51 Golf Course 112 6,021 PRZ PRZ 2 20 GG GG 33 206 PS PS 1 4 GP Gravel Pit 160 1,457 PX PX 89 1,188 Gr Gravel 7 181 PY PY 59 895 IN IN - Indian Mounds 1 5 PZ PZ 82 987 IS Island 184 575 Qz Quarry 50 713 K K 2 71 RC Red Cedar 14 259 KC Kentucky Coffee Trees 1 1 RCT Recent Cut 3 166 LA Lake Dried Up 1 3 RE Reserve 2 71 LO Locust 2 15 Rec Recreation Area 57 1,999 MA Maple 17 333 RM RM 1 5 11 Code Code Description Polygon Count Acres RO Rock Outcrop 77 1,199 S Stump 1,250 32,241 Sand Sand 25 671 SB Sand Bar 10 55 SC SC 39 679 Sch.Gs Sch.Gs 1 4 SD SD 34 1,577 SF State Farm 1 78 SFH State Fish Hatchery 1 77 SFN State Forest Nursery 1 93 SL Slash 37 1,881 SLP Slag Pile 1 14 SN SN 57 4,741 Snags Snags 2 26 SP Stump Pasture 18,749 320,193 SPC SPC 1 47 SPRZ SPRZ 1 11 SPX SPX 25 483 SPY SPY 29 570 SPZ SPZ 9 100 SR SR 1 61 SRG Spring 4 19 St Shoal Bottom With Debris 17 745 STKYD Stock Yard 2 3 U U 86 3,153 UF UF 4,651 42,677 UG UG 2,328 20,875 UR UR 100 311 Urban Urban 312 9,670 WD Windfall 2 1 WE WE WO Open Water WR River Z Z Total 2 36 11,374 978,188 4,977 81,174 1 7 364,629 16,915,530
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