Geodataset Name:       LU_SF_WTLNDS_04
Geodataset Type:       SPATIAL VIEW
Geodataset Feature:    Polygon
Feature Count:         116701

DATA SOURCE(S):                    Photo Science, Inc.
SCALE OF ORIGINAL SOURCE MAPS:     12000
DATE OF AUTOMATION OF SOURCE:      20050209
GEODATASET EXTENT:                 Broward County, Charlotte County (Partial Coverage), 
Collier County, Desoto County (Partial Coverage), Glades County, Hardee County (Partial Coverage), 
Hendry County, Highlands County (Partial Coverage), Lake County (Partial Coverage), Lee County, 
Martin County, Miami-Dade County, Monroe County, Okeechobee County (Partial Coverage), 
Orange County (Partial Coverage), Osceola County (Partial Coverage), Palm Beach County,
Polk County (Partial Coverage), and St. Lucie County

FEATURE ATTRIBUTE TABLES:

Datafile Name: LU_SF_WTLNDS_04

FEATURE ATTRIBUTE TABLES CODES AND VALUES:

Item	Item Description
OBJECTID	Internal feature number.
FLUCCS	The land use and land cover classification code as defined in the Florida DOT's FLUCCS classification system. The following represents the original field from the source Water Management District layer. SFWMD = LUCODE - This attribute will be populated with a land use value based on the FLUCCS agreed upon in this contract. Where it appears that the land cover is more dominant than the land use, the land cover value will be used. In these cases the LUCODE will take on the same value as the LCCODE. This field will remain present in the final deliverable. LUCODE = Land Use Code.
OTHER	The following represents the original field from the source Water Management District Layer. SFWMD = LCCODE - This attribute will be populated with a land cover value based on the FLUCCS agreed upon in this contract. However, in cases where the land use value is a more accurate descriptor than cover the LCCODE will take on the same value as the LUCODE. The SFWMD and/or the PI Key will provide direction on how to apply LCCODE and LUCODE in the mapping effort. This field will remain present in the final deliverable. LCCODE = Land Cover Code.
UPDATE_STA	Field not defined by Source.
MELALEUCA	See the PI Key page for 4240 Melaleuca for a description of this species and its typical photo-signature and habitat. This field will be coded with "N/A" values when the FLUCCS codes are not appropriately 4240.MELALEUCA = Melaleuca. This exotic tree species occurs in almost pure stands. It is an aggressive competitor, invading and often taking over a site, forming a dense and impenetrable stand. It grows along roadsides, on ditch banks, in mesic prairies, in sawgrass marshes and on lake shorelines. Melaleuca generally is an indicator of a disturbed site. It becomes established more readily on sand than on marl but can survive on any disturbed soil in southern Florida. The canopy closure must be 25% or more with at least 67% or more dominance by Melaleuca for inclusion in this class. 0 = No present conditions of Melaleuca exist. 1 = Present conditions of Melaleuca exist. 2 = Present conditions of dead Melaleuca exist. Dead Melaleuca are normally found in areas where they have been treated for eradication mainly within the Everglades. They usually have a sparse, whitish gray signature. 3 = Present conditions of cleared Melaleuca exist. Collateral data such as the previous studies will be needed. These areas may be seen adjacent to dead Melaleuca within the Everglades. 4 = Present conditions of multiple Melaleuca exist.
BRAZILIAN	See the PI Key page for 4220 Brazilian Pepper for a description of this species and its typical photo-signature and habitat. This exotic, pestilent tree species is found on peninsular Florida from the Tampa Bay area southward. Brazilian Pepper grows on a broad range of sites in South Florida, ranging from mangroves to pinelands. It thrives on disturbed soils and in newly created habitats resulting from drainage and farming. It is an early invader of disturbed sites, and it also becomes established in the understory of dense forests, then capturing the site when gaps occur in the canopy. Brazilian Pepper is a potential canopy tree in almost any forest in Florida. The canopy closure must be 25 % or more with at least 67% or more dominance by Brazilian Pepper for inclusion in this class. 0 = No present conditions of Brazilian Pepper exist. 1 = Present conditions of Brazilian Pepper exist.
EXOTICS	Exotics are species introduced to Florida, either purposefully or by accident, from a natural range outside of Florida. This modifier will be used for species such as Australian Pine, Kudzu and Old World Climbing Fern (Lygodium microphyllum or japonicum)EXOTICS = Exotics 0 = No present conditions of Exotic Species exist. 1 = Present conditions of Exotic Species exist. 2 = Present conditions of dead Exotic Species exist. 3 = Present conditions of cleared Exotic Species exist. 4 = Present conditions of multiple Exotic Species exist.
TREE_ISLAN	Tree islands are the most distinct plant communities in the Everglades. In general, they consist of low trees, which are situated on slight elevations above the surrounding marsh areas. They range in size from small circular islands of one half to 5 or 6 acres, to larger, tear-drop shaped "strands", which can grow to over 300 acres in size. These are wetland communities in which species composition varies, and they may be classified variously as bay heads, hammocks, willows or cypress islands. The "tree islands" modifier is applied to both the forested and shrub portions of tree islands that contain both, and also to tree islands that are made up of only forest or only shrubs. The modifier is not applied to any surrounding marsh areas. 0 = No present conditions of Tree Islands exist. 1 = Present conditions of Tree Islands exist.
DEAD_TREES	Dead trees, also known as "snags", can be found in areas where normal water flow has been impounded, either naturally or through the building of dams. Trees killed by these methods commonly appear denuded, with whitish or grayish signatures.DEAD_TREES = Dead_Trees 0 = No present conditions of Dead Trees exist. 1 = Present conditions of Dead Trees exist.
ORV	Off-Road Vehicles (ORV) include a variety of land and water craft, ranging from all-terrain vehicles such as four-wheel motorbikes, swamp and dune buggies, and motorcycles, to personal watercraft such as jet and air boats. Evidence of ORV use usually appears as irregular, random trails through areas not accessible by roads. They can be found either on upland areas or through wetland areas such as prairies and marshes. They are particularly evident in the Big Cypress National Preserve in Collier County.ORV = Off Road Vehicles 0 = No present conditions of Off-Road Vehicles (ORV) exist. 1 = Present conditions of Off-Road Vehicles (ORV) exist.
BURNED	Burned areas are those affected by fire, either through natural means such as wildfire, or through the controlled use of fire to achieve land management goals. Fire is used to achieve a variety of objectives, such as enhancing forage for cattle, restoring a fire-dependent ecosystem, improving wildlife habitat or preparing sites for reforestation. Burned areas usually appear as a flat, bluish, or blue-green signature on the aerial photo.BURNED = Burned 0 = No present conditions of Burned Areas exist. 1 = Present conditions of Burned Areas exist.
PHOTO_INTE	Field not defined by Source.
SUPERVISIN	Field not defined by Source.
GENERAL_NO	Field not defined by Source.
DELIVERABL	Field not defined by Source.
MAPPING_CO	Field not defined by Source.
MMU_MATRIX	This field is not being utilized.MMU_MATRIX = Not used
HYPERLINK	Link to PI Key. Hyperlink = link to PI Key
SOURCE	Water Management District of Coverage/Origin.
SOURCE2	Agency of Origin: Photo Science, Inc.
FLUCCS_L1	The highest level (level 1) designation in a hierarchical coding scheme containing 4 levels.
LEVEL1	Level 1 land use description, based on the FDOT classification schema.
FLUCCS_L2	The second highest level (level 2) designation in a hierarchical coding scheme containing 4 levels.
LEVEL2	Level 2 land use description, based on the FDOT classification schema.
FLUCCS_L3	The third highest level (level 3) designation in a hierarchical coding scheme containing 4 levels.
LEVEL3	Level 3 land use description, based on the FDOT classification schema. There is a possibility that the FDOT Level 3 description does not match that of the Water Management District, for those occurrences this discrepancy has been identified in the FLUCCSCOMP field.
FLUCCSCOMP	This field represents a comparision between the dataset's FLUCCS code description and the FDOT FLUCCS code description. Where these two descriptions differed a number one was inserted.
ACRES	Number of Acres.
DESCRIPT	Based on the SFWMD FLUCCS number classification descriptions from the PI_Key.pdf
FGDLAQDATE	The date FGDL acquired the data from the Source.
AUTOID	GeoPlan Center feature identification number.
SHAPE	Feature geometry.
SHAPE.AREA	Area in meters
SHAPE.LEN	Perimeter in meters
SHAPE.FID	Internal feature number.

The FLUCCS uses numeric codes to represent the land use or land cover types within the classification system pertaining to wetlands, uplands, and anthropogenic features. The land cover code is defined in the lccode field and the land use code is defined in the lucode field of the PAT. SFWMD FLUCCS number classification descriptions from the PI_Key.pdf 1000 URBAN AND BUILT UP 1100 Residential, Low Density 1110 Fixed Single Family Units 1120 Mobile Home Units 1130 Mixed Units, Fixed and Mobile Home Units 1180 Rural Residential 1190 Low Density Under Construction 1200 Residential, Medium Density 1210 Fixed Single Family Units 1220 Mobile Home Units 1230 Mixed Units, Fixed and Mobile Home Units 1290 Medium Density Under Construction 1300 Residential, High Density 1310 Fixed Single Family Units 1320 Mobile Home Units 1330 Multiple Dwelling Units, Low Rise 1340 Multiple Dwelling Units, High Rise 1350 Mixed Units, Fixed and Mobile Home Units 1390 High Density Under Construction 1400 Commercial and Services 1410 Retail Sales and Services 1411 Shopping Centers 1420 Wholesale Sales & Services 1423 Wholesale Sales & Services - Junk Yards 1460 Oil and Gas Storage - not Industrial or Manufacturing. 1480 Cemeteries 1490 Commercial and Services Under Construction. 1500 Industrial 1540 Oil and Gas Processing 1550 Other Light Industry 1560 Other Heavy Industrial 1600 Extractive 1610 Strip mines 1620 Sand and Gravel Pits 1630 Rock Quarries 1640 Oil and Gas Fields 1650 Reclaimed Lands 1660 Holding Ponds 1670 Abandoned Mining Lands 1700 Institutional 1710 Educational Facilities 1730 Military 1760 Correctional 1800 Recreational 1810 Swimming Beach 1820 Golf Course 1830 Race Tracks 1840 Marinas and Fish Camps 1850 Parks and Zoos 1870 Stadiums: Not Academic 1900 Open Land 1920 Inactive Land with Street Pattern 2000 AGRICULTURE 2100 Cropland and Pastureland 2110 Improved Pastures 2120 Unimproved Pastures 2130 Woodland Pastures 2140 Row Crops 2150 Field Crops 2156 Sugar Cane 2160 Mixed Crops 2200 Tree Crops 2210 Citrus Groves 2220 Fruit Orchards 2230 Other Groves 2300 Feeding Operations 2310 Cattle Feeding Operations 2320 Poultry Feeding Operations 2400 Nurseries and Vineyards 2410 Tree Nurseries 2420 Sod Farms 2430 Ornamentals 2500 Specialty Farms 2510 Horse Farms 2520 Dairies 2540 Aquaculture 2600 Other Open Lands - Rural 2610 Fallow Cropland 3000 UPLAND NONFORESTED 3100 Herbaceous (Dry Prairie) 3200 Upland Shrub and Brushland 3210 Palmetto Prairies 3220 Coastal Shrub 3230 Abandoned Groves 3300 Mixed Rangeland 4000 UPLAND FORESTS 4100 Upland Coniferous Forests 4110 Pine Flatwoods 4120 Longleaf Pine - Xeric Oak 4130 Sand Pine 4140 Pine - Mesic Oak 4200 Upland Hardwood Forests 4210 Xeric Oak 4220 Brazilian Pepper 4240 Melaleuca 4270 Live Oak 4271 Oak - Cabbage Palm Forests 4280 Cabbage Palm 4300 Upland Mixed Forests 4340 Upland Mixed Coniferous / Hardwood 4370 Australian Pine 4400 Tree Plantations 4410 Coniferous Plantations 4420 Hardwood Plantations 4430 Forest Regeneration Areas 5000 WATER 5100 Streams and Waterways 5110 Natural River, Stream, Waterway 5120 Channelized Waterways, Canals 5200 Lakes 5250 Marshy Lake 5300 Reservoirs 5400 Bays and Estuaries 5410 Embayments Opening Directly to Gulf or Ocean 5420 Embayments Not Opening Directly to Gulf or Ocean 5430 Saltwater Ponds 5600 Slough Waters 5700 Ocean and Gulf 5710 Atlantic Ocean 5720 Gulf of Mexico 6000 WETLANDS 6100 Wetland Hardwood Forests 6110 Bay Swamps 6111 Bayhead 6120 Mangrove Swamp 6170 Mixed Wetland Hardwoods 6172 Mixed Shrubs 6180 Cabbage Palm Wetland 6190 Exotic Wetland Hardwoods 6191 Wet Melaleuca 6200 Wetland Coniferous Forests 6210 Cypress 6215 Cypress- Domes/Heads 6216 Cypress - Mixed Hardwoods 6240 Cypress - Pine - Cabbage Palm 6250 Wet Pinelands Hydric Pine 6260 Pine Savannah 6300 Wetland Forested Mixed 6400 Vegetated Non-Forested Wetlands 6410 Freshwater Marshes / Graminoid Prairie - Marsh 6411 Freshwater Marshes - Sawgrass 6420 Saltwater Marshes / Halophytic Herbaceous Prairie 6430 Wet Prairies 6440 Emergent Aquatic Vegetation 6500 Non-Vegetated Wetland 6510 Tidal Flats 7000 BARREN LAND 7200 Sand Other Than Beaches 7300 Exposed Rock 7400 Disturbed Land 7420 Borrow Areas 7430 Spoil Areas 7440 Levees 8000 TRANSPORTATION, COMMUNICATION & UTILITIES 8100 Transportation 8110 Airports 8113 Private Airports 8115 Grass Airports 8120 Railroads and Railyards 8140 Roads and Highways 8150 Port Facilities 8200 Communications 8300 Utilities 8310 Electrical Power Facilities 8320 Electrical Power Transmission Lines 8330 Water Supply Plants - Including Pumping Stations 8340 Sewage Treatment 8350 Solid Waste Disposal 8360 Other Treatment Ponds

USER NOTES:

Quality Control (QC) Photo Science performed QC on all project deliverables and verified the following: o Classification Accuracy o Positional and Line Work Accuracy o Attribute Accuracy Photo Science performed a through QC for classification accuracy, positional and line work accuracy and attribute accuracy on 100% of the polygons associated with the final delivery of this project. Photo Science randomly select a minimum of 10 - 20 polygons per DOQQ. Fifty percent of these polygons were targeted polygons updated by Photo Science. Half of the updated polygons selected targeted "difficult" or "confusing" classification codes. If, the QC process revealed problems with classification accuracy, positional and line work accuracy and, or attribute accuracy, the number of polygons per DOQQ scrutinized during Photo Science's QC increased up to 100 percent if needed. Feedback on all edit calls were provided to the individual photointerpreter assigned the specific DOQQ, decision rules reviewed and opportunities for process improvement investigated and implemented. Classification Accuracy. Photo Science assessed overall quality and classification accuracy using a standardized quality control process to meet accuracy criteria. Each section deliverable, as well as the pilot, had a minimum classification accuracy of 90% for each Level I category, 85% for each FLUCCS Level II category and 80% for FLUCCS Level III and IV categories at a confidence level of 90%. The overall accuracy of each section deliverable had a minimum classification accuracy of 90% at a confidence interval of 90%. Classification accuracy was assessed using photointerpretation techniques combined with ground truth field verification of randomly selected polygons. All polygons classified underwent a photointerpretation QC process to identify any critical defects which could have degraded the FLUCCS integrity of the LCLU map. These defects included, but were not limited to: o Improper selection of collateral data o Incorrect feature interpretation and coding o No feature consistency across project area o Features not labeled clearly or completely o Incorrect polygon annotations o Missing polygons o No adherence to minimum acreage size requirement Photo Science was aware that problems were identified by the SFWMD in the 1999-2000 LCLU dataset in regards to residential density classifications and the limited use of modifiers such as the exotic species attribute. Photo Science scrutinized the problematic classes and all modifiers. Further, Photo Science photointerpreters also documented any discernable discrepancies between the time of the source photography was acquired (2004-05) and current (2006-07) field conditions. Many of these types of discernable discrepancies between 2004-05 source imagery and current field conditions were associated with urban development on previously non-developed land. Although the source imagery typically takes priority on these types of situations, photointerpreters noted the discrepancy using a new or existing point feature class in the geodatabase so that the information is readily available to the end user and is accessible via GIS. Photo Science was aware that there may be several reasons why a LCLU feature may be misclassified. These reasons were typically related to the quality of the source imagery, potential signature variance, ambiguous decision rules and FLUCCS codes, the potential aggregation of mapping units, improper use of reference and ancillary data, etc. An example of some common photointerpretation misclassifications that Photo Science avoided are presented below: o Mixed rangeland areas (3300) may be misclassified as unimproved pasture areas (2120) o Light industrial (1550) may be misclassified as wholesale sales and service (1423) Photo Science continually referenced the PI Key to clarify the parameters for each FLUCCS code and engaged in extensive ground truth field verification to help avoid any misclassifications. Photo Science recommended modifications of the PI Key to the SFWMD to correct deficiencies found and additional modifiers to the FLUCCS and/or additional FLUCCS codes were added. During the photointerpretation and subsequent QC effort, it was imperative that all wetland classes were properly classified and were in compliance with a minimum mapping resolution of two acres (except wetlands isolated in an upland matrix which were mapped at a one acre MMU), and that all other upland LCLU types were properly delineated and classified and met the MMU of five acres (except uplands isolated in a wetland matrix that were mapped at a two acres MMU). Interpretation decisions were based on high-resolution stereoscopic viewing of the 2004-05 digital panchromatic source imagery using softcopy photogrammetric workstations in conjunction with required and optional reference data. The source data, required reference data, and optional reference data layers were integrated directly into the digital interpretation workspace wherever possible to coordinate these sources with feature extraction from source imagery. Regular internal coordination meetings were held between Photo Science's Project Manager, the QC Manager, and the photointerpreters to discuss any classification issue or anomaly. Reference was continually made to the PI Key to help guide the resolution of these issues. Photo Science also checked for coding accuracy for the non-FLUCCS classification fields.

Minimum mapping unit for land cover/land use polygons was 2 acres for wetlands and 5 acres for uplands. The study area boundaries for the project were defined by the SFWMD. Land use/land cover features were captured and classified according to the rules, conventions, and descriptions in the SFWMD LCLU 2006 Mapping Project Photointerpretation Classification Key. The LC/LU map was delivered with some wetland polygons under the two acre minimum mapping unit, the majority existing from the 1999 dataset. All 'Changed' wetlands below half acre were deleted.

GeoPlan relied on the integrity of the attribute information within the original data.

Photo Science Inc. of St. Petersburg, Florida was contracted by the South Florida Water Management District to produce a spatially, thematically, and technically accurate ArcGIS Land Cover/ Land Use (LCLU) dataset using the aerial photographs and Digital Orthophoto Quadrangles (DOQs) produced from the 2004-2005 National Aerial Photography Program (NAPP) Florida over-flight as the source imagery. Delineations were made on-screen and field reconnaissance was conducted to resolve classification and boundary problems encountered during the photointerpretation process. The new dataset registers to the Digital Orthophoto Quarter Quadrangles and reflects field conditions at the time of the imagery. The classification system used for this project was the Florida Land Use, Cover and Forms Classification System (FLUCCS), which was originally compiled by the Florida Department of Transportation, State Topographic Bureau. The classification system was amended by the District for use on this project and these amendments are described within this document. The following Photointerpretation Key was developed in order to document the decisions and mapping conventions applied during the photointerpretation process. The key was used to assist the photointerpreters in compiling the Land Cover/Land Use 2004-05 Mapping Project for the South Florida Water Management District and helped to ensure that the photointerpretation was consistent throughout the project. It was designed to provide descriptions of the visual and spatial distribution characteristics of the classification types used for the project. The Photointerpretation Key documents any special mapping conventions that were applied during the mapping effort. All photointerpretation was conducted in accordance with the Florida Land Use, Cover and Forms Classification System unless otherwise indicated within the Photointerpretation Key. The key also serves to provide insight for future users into the rationale for the delineations and classifications appearing within the database. The SFWMD LCLU 2004-05 Mapping Project PI Key was derived from a combination of materials relevant to land cover, land use mapping. The document was originally produced by Avineon, Inc. (formerly AGRA-Baymont, Inc. and Geonex Corporation) in 1995 as part of the St. Johns River Water Management District (SJRWMD) 1995 Land Use/Land Cover Mapping Project. The document has since been improved and updated by Photo Science to include additional reference information intended to assist users in accurately photointerpreting and mapping land cover and land use. Classification codes are based on the Florida Land Use, Cover, and Forms Classification System; Department of Transportation, State Topographic Bureau, Thematic Mapping Section; January 1999 Edition.

Creation of a 2004-05 landcover/landuse map from 1:12,000 scale CIR, RGB and Stereo Panchromatic photography and aligned to USGS DOQQ's. This data was produced for the SFWMD's "Land Cover/Land Use 2004-05 Mapping Update Project".

Positional and Line Work Accuracy for the final deliverable to the SFWMD met or exceeded the Map Accuracy Standards discussed in the SOW. Positional and line work accuracies were assessed by visually checking the FLUCCS code for mapping units by an independent quality control photointerpreter. This review also included ensuring that all coordinates were referenced to the State Plane Coordinate System, Florida East Zone, units survey feet, NAD 1983 (HARN). The LCLU delineations were performed in a heads-up digital environment relative to the 2004-05 color-infrared (CIR) or Natural Color 3.75' DOQQ's. Monoscopic screen viewing of imagery did not take place for mapping difficult features such as vegetation. In cases where stereoscopic viewing was required, the 2004-05 digital panchromatic imagery was stereoscopically viewed using softcopy photogrammetric workstations. All boundaries were captured through on screen digitizing or other methods to ensure accurate and coincident registration of LCLU data to the DOQQs. No positional shifts were found within horizontal accuracy range of features in 1999-2000 DOQQs and 2004-2005 DOQQs, The SFWMD provided a feature class within the geodatabase which was used as the basis for the 2004-05 LCLU dataset. The source for this layer was an exact copy of the 1999-2000 LCLU feature class. It included topological rules which were enforced, as well as domains and subtypes suitable to the project objectives. A summary of the Positional Accuracy standards Photo Science adhered to are presented as follows: o The Work Order deliverable feature datasets and feature classes were a derivative product from the existing 1999-2000 LCLU base layer. The persisting linework from this layer was not adjusted unless it was corrected or updated. o All coordinates was referenced to the State Plane Coordinate System, Florida East Zone, units survey feet, North American Datum (NAD) 1983 (HARN). The ESRI projection file for"NAD_1983_HARN_StatePlane_Florida_East_FIPS_0901_Feet" coordinate system was utilized and maintained to ensure compatibility with the SFWMD Enterprise GIS database. A detailed description of this information was attached as Appendix E). o Projection information was present in the metadata file and was accessible through ArcCatalog. o The linework of all features was within 20 feet of the coordinate position of the feature represented in the DOQQ.

This data is provided 'as is' and its vertical positional accuracy has not been verified by GeoPlan

THE DATA INCLUDED IN FGDL ARE 'AS IS' AND SHOULD NOT BE CONSTRUED AS LEGALLY BINDING. THE UNIVERSITY OF FLORIDA GEOPLAN CENTER SHALL NOT BE LIABLE FOR ANY DAMAGES SUFFERED AS A RESULT OF USING, MODIFYING, CONTRIBUTING OR DISTRIBUTING THE MATERIALS. A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html

REFERENCES:

South Florida Water Management District http://www.sfwmd.gov Photo Science, Inc. http://www.photoscience.com/index.html

DATA LINEAGE SUMMARY:

An overview of the mapping methodology and work flow which was utilized during the project is displayed in the Project Methodology Flow Chart presented above under Project Methodology. The typical daily workflow included the loading of data, syncing of computers and viewing/editing environments (softcopy and ArcMap digitizing), polygon review process, incorporation and use of ancillary data, etc. Photo Science photointerpreters utilized appropriate source and required reference data overlaid directly in the editing windows. The 2004-05 LCLU Template Geodatabase developed by the SFWMD contained the source 1999 LCLU base layer that was the source of the new features. It also contained the domains, subtypes, layerfiles and topology validation rules which help guide the photointerpreters in the production environment and in the appropriate formatting of the final deliverable. The 1999-2000 LCLU data provided by the SFWMD was used by Photo Science as a visual base over which to compare against the 2004-05 DOQQs. Changed polygons were delineated and attributed for the new (2004-05) LCLU feature class. Photo Science corrected any errors from the original 1999 LCLU dataset so as not to propagate these errors in the new dataset. Photo Science scrutinized problem such as limited use of modifiers such as exotics attributes in the 1999 LCLU dataset. Photo Science used the 1999-2000 layer as reference at all times during the delineation and quality control process and worked to maintain an appropriate level of consistency with that layer unless other information indicated to the contrary. This did not compromise accuracy. Inconsistencies between residential density codes in the 1999 LCLU dataset were recognized and the parcel data was utilized in an effort to alleviate these inconsistencies. SFWMD advised Photo Science to use county parcel data as reference material in the production process as visual overlays in the editing windows. The parcel data was symbolized according to the acres per dwelling and helped categorize neighborhood polygon densities. In areas of disagreement (e.g. empty lots) a five acre template was applied over the dataset, the dwellings were counted and calculated for appropriate code assignment. No line work was transferred from the county parcel data. Process Date: 20071204 The GeoPlan Center downloaded the original Land Cover Land Use 2004 dataset (lscndclu04.zip) from the South Florida Water Management GIS Data Catalog Website on April 10, 2008. http://my.sfwmd.gov/gisapps/sfwmdxwebdc/dataview.asp The zipped file was extracted and the land use layer was exported to shapefile format from the 2004_05_LCLU_SFWMD_Geodatabase.mdb The dataset was originally projected to: NAD_1983_HARN_StatePlane_Florida_East_FIPS_0901_Feet The dataset was reprojected to the FGDL NAD83 HPGN Albers projection. Next the records in the attribute table were UPPERCASED. Below is the original SFWMD file structure: ITEM NAME WIDTH TYPE Shape 0 Geometry LCCODE 4 Number LUCODE 4 Number UPDATE_STA 4 Number MELALEUCA 4 Number BRAZILIAN_ 4 Number EXOTICS 4 Number TREE_ISLAN 4 Number DEAD_TREES 4 Number ORV 4 Number BURNED 4 Number PHOTO_INTE 4 Number SUPERVISIN 4 Number GENERAL_NO 120 String DELIVERABL 4 Number MAPPING_CO 4 Number MMU_MATRIX 4 Number Hyperlink 200 String Below is the crosswalk table between the original file structure and the new file structure: ORIGINAL NAME NEW NAME Shape Same LCCODE OTHER LUCODE FLUCCS UPDATE_STA Same MELALEUCA Same BRAZILIAN_ BRAZILIAN EXOTICS Same TREE_ISLAN Same DEAD_TREES Same ORV Same BURNED Same PHOTO_INTE Same SUPERVISIN Same GENERAL_NO Same DELIVERABL Same MAPPING_CO Same MMU_MATRIX Same Hyperlink HYPERLINK Additionally GeoPlan added and populated the following fields: SOURCE SOURCE2 FLUCCS_L1 LEVEL1 FLUCCS_L2 LEVEL2 FLUCCS_L3 LEVEL3 FLUCCSCOMP ACRES DESCRIPT FGDLAQDATE AUTOID Process Date: 20080429 Spatial view created based on land use sde layer Process Date: 20080515 Metadata imported. Process Date:

MAP PROJECTION PARAMETERS:

Projection                          ALBERS
Datum                               HPGN
Units                               METERS
Spheroid                            GRS1980
1st Standard Parallel               24  0  0.000
2nd Standard Parallel               31 30  0.000
Central Meridian                   -84 00  0.000
Latitude of Projection's Origin     24  0  0.000
False Easting (meters)              400000.00000
False Northing (meters)             0.00000

DATA SOURCE CONTACT (S):

Name:
Abbr. Name:
Address:


Phone:

Web site:
E-mail:
Contact Person:
         Phone:
        E-mail:

Photo Science, Inc.

10033 Martin Luther King Street North
St. Petersburg, FL
33716
(727) 576-9500


http://www.photoscience.com/index.html
reastlake@photoscience.com
Richard Eastlake

Name:                   FLORIDA GEOGRAPHIC DATA LIBRARY
Abbr. Name:             FGDL
Address:                Florida Geographic Data Library
                        431 Architecture Building
                        PO Box 115706
                        Gainesville, FL  32611-5706
Web site:               http://www.fgdl.org

Contact FGDL: 

      Technical Support:	        http://www.fgdl.org/fgdlfeed.html
      FGDL Frequently Asked Questions:  http://www.fgdl.org/fgdlfaq.html
      FGDL Mailing Lists:		http://www.fgdl.org/fgdl-l.html
      For FGDL Software:                http://www.fgdl.org/software.html