Photo Science, Inc.UnknownSFWMD 2004-05 Land Use vector digital dataServer=gissde; Service=5151; User=base; Version=SDE.DEFAULTBASE.SFWMD_LANDUSE_2004_05This data set serves as documentation of land cover and land use within the South Florida Water Management District as it existed in 2004-05. Land cover/land use data was photo interpreted from 2004-05 1:12,000 scale CIR, RGB and stereo panchromatic aerial photography and classified using the SFWMD modified FLUCCS classification system. Features were stereoscopically interpreted from the aerial photography and the 1999 vector data was updated on screen over corresponding USGS DOQQ's. Horizontal accuracy of the data corresponds to the positional accuracy of the USGS DOQQ's. The minimum mapping unit for classification was 2 acres for wetlands and 5 acres for uplands.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".en2004111820050209Source photography date.Updated approximately every 5 years.-82.347126-79.92059128.57658124.454872567432.231250798394.27500056746.247250508992.963500noneLCLULULCLand CoverLand UseFLUCCSvegetationagricultureurban built upupland forestswetlandsbarren landtransportationcommunicationutilitiesleveesleveemelaleucadead treesoff road vehiclesorvexoticsburned areasfield check pointserrors 1999brazillian pepperPlanning and DevelopmentnoneSFWMDSouth Florida Water Management DistrictCountyBrowardCollierCharlotteGladesHendryHighlandsLeeMartinMiami DadeMonroeOkeechobeeOrangeOsceolaPalm BeachPolkSt. LucieFloridaUSAUnitedStatesAmerica20042005This database is made available to the public in response to the Florida Public Records Law, Florida Statutes, Chapter 119.Acknowledgement of South Florida Water Management District would be appreciated in products derived from this data.The positional accuracy of this data meets USGS NMAS for 1:12000 scale maps. This data has 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 classification accuracy was calculated as a weighted average of all classes for each deliverable (weighted by total area covered by each class).SFWMDMichael BrokerGIS Data Steward, Sr.mailing and street3301 Gun Club RoadWest Palm BeachFL33406USA(561) 682-6936(561) 681-6318mbroker@sfwmd.gov8am-5pm M-FPhoto Science, Inc. was contracted in May 2006 to map all deliverables associated with the 2004-05 Land Cover / Land Use Mapping Update projectMicrosoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 9.3.1.4000SDE Feature ClassAttribute Accuracy
The attribute tables contained their contract specified fields in the correct order and were
defined correctly. There were no superfluous attribute tables or attribute fields in the final
deliverable. All fields were coded correctly and completely. There was a value in every
polygon for every attribute. Guidelines for use of LUCODE, LCCODE and modifiers were
specified in the PI Key and correctly applied. The use of dual-coding persisted, for
instance, the land use code may be 1730 (Military Installation) while the land cover code may be
4270 (Live Oak).
P.I. Decision Notes and General Notes were filled out whenever deemed useful or appropriate
by the Photointerpreter and were standardized by utilizing a geodatabase domain which allowed
identical comments/issues to be identified easily. There was a value in every polygon. Where
no value applies the default was 'N/A'.
The following attributes were associated with each of the digitized polygons:
o LCCODE: this attribute was populated with a land cover value based on the
FLUCCS agreed upon in this contract. However, in cases where the land use value
was a more accurate descriptor than cover the LCCODE took on the same value as
the LUCODE. The SFWMD and/or the PI Key provided direction on how to apply
LCCODE and LUCODE in the mapping effort. This field remained present in the
final deliverable.
o LUCODE: this attribute was populated with a land use value based on the
FLUCCS agreed upon in this contract. Where it appeared the land cover was
dominant over the land use, the land cover value was used. In these cases the
LUCODE took on the same value as the LCCODE. This field remained present
in the final deliverable.
o UPDATE_STATUS: this attribute denoted if the polygon has been inspected for
change and if so the status.
Modifiers: these attribute types were used to add additional detail to the classification, such as
temporary conditions, minor features, or management factors, that was of particular
interest to the SFWMD but did not warrant adding new classes to the FLUCCS system. This
provided some extra opportunity for the SFWMD to customize the classification without
affecting overall consistency. They were divided into the three classes below: Impact
(Burned, ORV: Off-Road Vehicles), Vegetation (Dead Trees, Exotics, Tree Islands), and
Species (Melaleuca, Brazilian Pepper). See the respective Modifier Key pages for
descriptions of these modifiers and information on their use in this data layer. The
SPECIES modifiers were added to all LCLU polygons to indicate the presence of these
conditions or species as identifiable on the aerial photograph to a degree that did not meet
the criteria for classification as the dominant land cover. There was no minimum mapping unit
for the application of these modifiers; they were applied to all LCLU polygons as observed
on the aerial photograph.
o MELALEUCA: See the PI Key page for 4240 Melaleuca for a description of this
species and its typical photo-signature and habitat. This field was coded with "N/A"
values when the FLUCCS codes were not appropriately 4240.
o BRAZILIAN_PEPPER: See the PI Key page for 4220 Brazilian pepper for a
description of this species and its typical photo-signature and habitat. This field was coded with "N/A" values when the FLUCCS codes were not appropriately 4220.
o EXOTICS: Exotics are species introduced to Florida, either purposefully or by
accident, from a natural range outside of Florida. This modifier was used for
species such as Australian Pine, Kudzu and Old World Climbing Fern (Lygodium
microphyllum or japonicum)
o TREE_ISLANDS: 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 have been classified variously as bay heads,
hammocks, willows or cypress islands. The "tree islands" modifier was applied to both
the forested and shrub portions of tree islands that contained both, and also to tree
islands that were made up of only forest or only shrubs. The modifier was not applied to
any surrounding marsh areas.
o DEAD_TREES: Dead trees, also known as "snags", were 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.
o 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 appeared as irregular, random trails through areas not accessible by
roads. They were found either on upland areas or through wetland areas such as
prairies and marshes. They were particularly evident in the Big Cypress National
Preserve in Collier County.
o 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.
o PHOTO_INTERPRETER_CODE: the photointerpreter responsible for the land cover
and land use determination was identified by this code value. This field was
present in the final deliverable.
o SUPERVISING_PSM: the name and license number of the supervising registered
professional surveyor and mapper in whose responsible charge the photo
interpreters performed the mapping and updates.
o GENERAL NOTE: Decisions that record uncertainties or level of confidence were recorded in this note field. Also general notes for anecdotal data unrelated to the
PI decision was referenced here. This field and its value remained present in the
final deliverable.
o DELIVERABLE_SECTION: SFWMD staff created this field to designate in
which section deliverable each polygon was to be mapped.
The following work accuracy specifications also applied:
o Polygon linework was not to be generalized along sinuous features. Linework properly characterized the shapes of boundaries appropriate to the resolution of the
DOQQ base image and in accordance with the PI Key.
o The existing linework derived from the 1999-2000 LCLU base layer that had no
errors and no land cover or land use change possessed coincident coordinates
with the original polygons.
o Minimum dimensions of mapped features conformed to the Minimum Mapping
Standards.
o Identically coded polygons were not adjacent to each other within a polygon
feature class.
o There were no duplicate features.
o Topology rules provided in the template geodatabase were validated and defined.Errors were completely corrected prior to delivery of each deliverable.
o All processing tolerances were consistent across all deliverables and were not
cause movement of geometries affecting polygon linework accuracy requirement
(#1) or coordinate coincidence requirement (#2).Tolerance values were recorded in the metadata.
o Each deliverable included all features of the previously mapped sections and were representative of the entire data set that had been completed to date. The
geographic extent of the data was maintained in a production cut of the database
that was spatially comprehensive of all work completed to date.
o The data was integrated so that boundaries between each section deliverable did not split feature polygons.
Additional Photointerpretation conventions Photo Science adhered to are defined as follows:
o Rivers, streams, waterways, and canals were delineated where they average
approximately 50-feet or greater in width and mapped as continuous features in
those segments.
o Levees that were 40-feet or greater in width were mapped when they were distinct and
continuous landscape features.
o Transportation corridors, including roads and rail yards were mapped when they
exceeded an average of 100-feet in width over substantial segments.
o Only roadways that have four lanes and a substantial median were mapped. The width was determined based on the full extent of the right-of-way, including mowed
areas, as visible on the aerial photography.
o Median strips in excess of 150-feet in width were delineated and classified for land cover.
o Utility corridors were delineated when they were approximately 150-feet or greater in width. In those corridor segments where the land cover was identical to adjacent areas such as through pasture and rangelands, the utility feature was not mapped.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.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.USGSUnknownUnknownCIR,RGB and Stereo Panchromatic1:12000CIR,RGB, and Panchromatic stereo DOQQ's2004-05ground conditionnonephotographic signature for interpretation of land use/land cover data.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 recognised and the parcel data was utilised 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 (eg. 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.12/04/07Michael BrokerSFWMDGIS Data Steward, Sr.mailing and physical address3301 Gun Club RoadWest Palm BeachFL33406USA(561) 682-6936(561) 681-6318mbroker@sfwmd.govGeodatabase obtained from SFWMD. Shapefile extracted.20080320Projected from State Plane East (Feet) to FDEP Custom FL Albers projection (Meters). Created Level1, Level2, Level3 and Level4 landuse fields. By WRM/GIS Subsection staff member April 1, 2008.20080401MMU_MATRIX field deleted.20080417Metadata modified along with layer file (.lyr). NOTE: Layer file corresponds to LCCODE field.
Submitted as new FDEP OTIS/GIS SDE layer.20080428Obtained new data form WRM and inserted in ArcSDE and published in DataCatalog and DataMiner. Metadata updated.20080505VectorSimple4FALSE0FALSEFALSEcoordinate pair0.0002500.000250metersD_North_American_1983_HARNGeodetic Reference System 806378137.000000298.257222GCS_North_American_1983_HARNFDEP Albers HARN1.000000Explicit elevation coordinate included with horizontal coordinatesSTL_LC04_SS2004_05 Land Cover/Land Use datasetSFWMDFeature Class0FIDFIDOID400Internal feature number.ESRISequential unique whole numbers that are automatically generated.LAND_COVERLAND_COVERSmallInteger440FID_STL_LCFID_STL_LCInteger990SHAPEFeature geometry.ESRICoordinates defining the features.ShapeGeometry000SHAPE_AREASHAPE_AREADouble1900Area of feature in internal units squared.ESRIPositive real numbers that are automatically generated.Kim_acresKim_acresDouble191817AREASYMBOLAREASYMBOLString2000MUSYMMUSYMString600MUKEYMUKEYString3000MUNAMEMUNAMEString17500MUACRESMUACRESInteger990FARMLNDCLFARMLNDCLString25400BROCKDEPMIBROCKDEPMISmallInteger440WTDEPANNMIWTDEPANNMISmallInteger440PONDFREQPRPONDFREQPRString25400HYDCLPRSHYDCLPRSString25400COMPPCT_LCOMPPCT_LSmallInteger440COMPPCT_RCOMPPCT_RSmallInteger440COMPPCT_HCOMPPCT_HSmallInteger440COMPNAMECOMPNAMEString6000COMPKINDCOMPKINDString25400MAJCOMPFLAMAJCOMPFLAString300OTHERPHOTHERPHString4000SLOPE_LSLOPE_LDouble191811SLOPE_RSLOPE_RDouble191811SLOPE_HSLOPE_HDouble191811TFACTTFACTSmallInteger440WEGWEGString25400HYDRICONHYDRICONString25400HYDRICRATIHYDRICRATIString25400DRAINAGECLDRAINAGECLString25400HYDGRPHYDGRPString25400CORCONCORCONString25400CORSTEELCORSTEELString25400TAXCLNAMETAXCLNAMEString12000TAXORDERTAXORDERString25400TAXSUBORDETAXSUBORDEString25400TAXGRTGROUTAXGRTGROUString25400TAXSUBGRPTAXSUBGRPString25400FLECOLOMNUFLECOLOMNUString500FLHEFLHEString300FLPHEFLPHEString300FLSOILLEACFLSOILLEACString25400FLSOIRUNOFFLSOIRUNOFString25400COKEYCOKEYString3000MONTHSEQMONTHSEQSmallInteger440MONTH_MONTH_String5000FLODFREQCLFLODFREQCLString25400FLODDURCLFLODDURCLString25400PONDFREQCLPONDFREQCLString25400PONDDURCLPONDDURCLString25400PONDDEP_LPONDDEP_LSmallInteger440PONDDEP_RPONDDEP_RSmallInteger440PONDDEP_HPONDDEP_HSmallInteger440DLYAVGPRECDLYAVGPRECSmallInteger440DLYAVGPR_1DLYAVGPR_1SmallInteger440DLYAVGPR_2DLYAVGPR_2SmallInteger440DLYAVGPOTEDLYAVGPOTESmallInteger440DLYAVGPO_1DLYAVGPO_1SmallInteger440DLYAVGPO_2DLYAVGPO_2SmallInteger440RESKINDRESKINDString25400RESHARDRESHARDString25400RESDEPT_LRESDEPT_LSmallInteger440RESDEPT_RRESDEPT_RSmallInteger440RESDEPT_HRESDEPT_HSmallInteger440RESDEPB_LRESDEPB_LSmallInteger440RESDEPB_RRESDEPB_RSmallInteger440RESDEPB_HRESDEPB_HSmallInteger440ECOCLASSIDECOCLASSIDString3000ECOCLASSNAECOCLASSNAString25400HYDRICCRITHYDRICCRITString25400KFFACTKFFACTString25400CHKEYCHKEYString3000TEXTURETEXTUREString3000STRATEXTSFSTRATEXTSFString300RVINDICATORVINDICATOString300TEXDESCTEXDESCString25400FID_SFWMD_FID_SFWMD_Integer990SHAPE_LENSHAPE_LENDouble1900SLRWPP_wshSLRWPP_wshString5000The 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.
Classification List
* Classes marked with an asterisk are not used for LCCODE or LUCODE classification in this dataset.
Note: For more descriptive information about these classifications, contact SFWMD for Photointerpretation Key (PI Key) Information.
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 and Services
1423 Wholesale Sales and 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 and 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
Addendum (9/19/06):
The following classes have been deleted from the key:
5250-Marshy Lakes
The following classes have been added to the key:
3230-Abandoned Groves
7440-Levees
The following descriptions were modified:
5200-Lakes - references to saltwater and coastal waters were deleted.
5430-Saltwater Ponds - title changed from 'Enclosed Saltwater Ponds within
Salt Marsh'
7440-Levees-minimum width was reduced from 90 to 40 feet.
The following domain values have been added to the Melaleuca field within
the Species modfiers:
Code Description
0 No
1 Yes
2 Dead
3 Cleared
4 Multiple
Addendum (3/07/07):
The following classes have been added to the key:
5250-Marshy Lakes
The following descriptions were deleted:
4220-Brazilian Pepper
NOTE: This class includes Brazilian pepper in both wetland and upland
locations. Wet Brazilian pepper is noted by the term WET entered in the
NOTE field of the polygon label.
The following descriptions were added:
4220-Brazilian pepper
Brazilian pepper wetland communities are coded as 6172 (Mixed Shrubs) with
the Brazilian Pepper modifier applied.
6172-Mixed shrubs
Brazilian Pepper upland communities are coded as 4220(Brazilian Pepper)
The following descriptions were deleted:
4280-Cabbage Palm
NOTE: This class also includes wetland cabbage palm communities that do not
meet the criteria for inclusion in either of the following classes; 6180 Cabbage
Palm Savannah or 6240 Cypress-Pine-cabbage palm.
The following descriptions were added:
6180-Cabbage Palm Savannah
The name and description of this class were changed to 6180 Cabbage Palm
Wetland.
Similar classes were added to 4220,4271,4280,5200,6410,6172 and 6180
Verbiage was changed in 4271,4280,6180,6430 and 8100.
Document updated by Richard Eastlake, Photo Science, Inc., St. Petersburg,
FloridaUser should refer to the Florida Department of Transportation FLUCCS and the SFWMD Photointerpretation Classification Key for full definition of the class codes and their application.Live Data and Maps20121024Florida Department of Environmental Protection (FDEP) OTIS/GIS Sectionmailing and physical address2600 Blair Stone RdMS 6520TallahasseeFL32399-2400USAGIS.Librarian@dep.state.fl.usFGDC Content Standards for Digital Geospatial MetadataFGDC-STD-001-1998local timeen2012120412535300FALSE20121204115820002012120411582000FGDCSTL_LC04_SS002567432.231250798394.27500056746.247250508992.9635001file://\\gisraid\gissub\Escribano_Y\Requests\Katie_Hallas_StLucie_BMAP\Test\STL_LC04_SS.shpLocal Area Network0.000ProjectedGCS_North_American_1983_HARNLinear Unit: Meter (1.000000)FDEP Albers HARN<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.0'><WKT>PROJCS["FDEP Albers HARN",GEOGCS["GCS_North_American_1983_HARN",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",400000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-84.0],PARAMETER["Standard_Parallel_1",24.0],PARAMETER["Standard_Parallel_2",31.5],PARAMETER["Latitude_Of_Origin",24.0],UNIT["Meter",1.0]]</WKT><XOrigin>-19550100</XOrigin><YOrigin>-7526400</YOrigin><XYScale>225743210.67916927</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem>Clip "SFWMD 2004-05 Land Use" SubBasins R:\2012December\2004LU_Cliiped_2subbasins.shp #Clip 2004LU_Cliiped_2subbasins "St Lucie BMAP" R:\2012December\KATIEHALLAS\LU2004_extent.shp #Identity LU2004_extent SubBasins R:\2012December\KATIEHALLAS\2004LU_WithSubbasins.shp ALL # NO_RELATIONSHIPSIdentity STL_LC04_withSubBasins "SSURGO Soils (SFWMD)" A:\Requests\Katie_Hallas_StLucie_BMAP\Test\STL_LC04_SS.shp ALL # NO_RELATIONSHIPS1.0FGDC CSDGM MetadataMicrosoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcGIS 10.0.2.3200SFWMD 2004-05 Land Use 567432.23125798394.275508992.963556746.247251-82.347126-79.92059128.57658124.4548721Creation 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".<DIV STYLE="text-align:Left;"><DIV><P><SPAN>This data set serves as documentation of land cover and land use within the South Florida Water Management District as it existed in 2004-05. Land cover/land use data was photo interpreted from 2004-05 1:12,000 scale CIR, RGB and stereo panchromatic aerial photography and classified using the SFWMD modified FLUCCS classification system. Features were stereoscopically interpreted from the aerial photography and the 1999 vector data was updated on screen over corresponding USGS DOQQ's. Horizontal accuracy of the data corresponds to the positional accuracy of the USGS DOQQ's. The minimum mapping unit for classification was 2 acres for wetlands and 5 acres for uplands.</SPAN></P></DIV></DIV>Photo Science, Inc. was contracted in May 2006 to map all deliverables associated with the 2004-05 Land Cover / Land Use Mapping Update projectLCLULULCLand CoverLand UseFLUCCSvegetationagricultureurban built upupland forestswetlandsbarren landtransportationcommunicationutilitiesleveesleveemelaleucadead treesoff road vehiclesorvexoticsburned areasfield check pointserrors 1999brazillian pepperPlanning and DevelopmentAcknowledgement of South Florida Water Management District would be appreciated in products derived from this data.The positional accuracy of this data meets USGS NMAS for 1:12000 scale maps. This data has 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 classification accuracy was calculated as a weighted average of all classes for each deliverable (weighted by total area covered by each class).1-82.347126-79.92059128.57658124.454872002ISO 19115 Geographic Information - MetadataDIS_ESRI1.0dataset002Server=gissde; Service=5151; User=base; Version=SDE.DEFAULTArcSDE ConnectionSDE Feature ClassShapefile0.000FDEP Albers HARN0020121204/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK
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