FLORIDA GEOGRAPHIC DATA LIBRARY DOCUMENTATION
VERSION 2004

TITLE: FLORIDA SOIL PROPERTIES 

Geodataset Name:       FLSOILPROPERTIES
Geodataset Type:       SHAPEFILE
Geodataset Feature:    POINT
GENERAL DESCRIPTION: 




The Florida Soil Profile geodataset is the result of georeferencing and processing 1296 soil profiles and 8325 horizons distributed in 58 of 67 counties in Florida,  collected from the early 1970's to early 1990's. An extensive data mining project was conducted, in order to convert the data into digital format. The sample data typically include profile characteristics (descriptions of the site, soil classification, etc.), a large number of laboratory parameters and a description of each horizon. Georeferencing and post-processing of some these parameters, gave result to this dataset, that includes hydric status, depth to sand, dept to rock and indirect distance to water table.






DATA SOURCE(S):                    Soil and Water Science Department
                                   Institute of Food and Agricultural Sciences (IFAS)
                                   University of Florida
SCALE OF ORIGINAL SOURCE MAPS:     1:20,000
DATE OF AUTOMATION OF SOURCE:      Source 1970 - 1990  Automated 2004
GEODATASET EXTENT:                 State of Florida

FEATURE ATTRIBUTE TABLES: 

Datafile Name: FLSOILPROPERTIES.DBF
ITEM NAME WIDTH TYPE N. DECIMAL DEGREES
FID
4 OID ---
Shape
0 Geometry ---
ID
254 String ---
SOILNAME
254 String ---
LATDECDEG
19 Number 11
LONGDECDEG
19 Number 11
ALBERS_X
19 Number 11
ALBERS_Y
19 Number 11
MAXDEPTHS
10 Number ---
MINDEPTHR
10 Number ---
HYDRICSTA
254 String ---
HYDRICRAT
254 String ---
INDIRECTW
10 Number ---
DESCRIPT
60 String ---

FEATURE ATTRIBUTE TABLES CODES AND VALUES:

Item

Item Description





FID

Internal feature number.
















Shape

Feature geometry.
















ID

Soil Profile Unique Number


















SOILNAME

Soil Name
















LATDECDEG

Latitude in decimal degrees
















LONGDECDEG

Longitude in decimal degrees
















ALBERS_X

Albers X coordinate
















ALBERS_Y

Albers Y coordinate
















MAXDEPTHS

Maximum Depth to Sand




0-999 = Values for this attribute were derived from soil sample data. In order to determine whether or not a hydric soil exists from a soil sample, two steps wer taken; using, (1) soil taxonomy (2) Florida soil series names. Details about the methodology to generate these values are in the Process Description section.













MINDEPTHR

Minimum Depth to Rock
















HYDRICSTA

Hydric Status




Hydric = Indicates if profile follows criteria for Hydric Soil

Non Hydric = Indicates if profile does not follows criteria for Hydric Soil













HYDRICRAT

Hydric Criteria




HH = Indicates that a profile does follows both criteria for Hydric Soil (first - soil name, and second - taxomony)

HN = The soil name follows first criteria (is it in the FDEP list) but not the second (taxonomy indicated otherwise).

NH = The soil name does not follow the first criteria (it is not found in the FDEP list) but it follows the second (the taxonomy indicate that the soil is hydric)

NN = Nonhydric for both criteria













INDIRECTW

Using the soil profile taxonomy  for horizons a search was conducted in the database for the first horizon at which "gleying" occurs.  Gleying being a redox product of a soil having been waterlogged for an extended period of time. Gleying is commonly denoted as a lower-case "g"  in a horizon description (i.e., Bg) The first horizon from the surface to contain a gleying indicator in its nomenclature would hint at the strong possibility of waterlogging at this depth. Note that some hydric soils might have a water table which comes to the surface of the soil, where the entire soil profile would be inundated with water.
















DESCRIPT

FGDL added field based on SOILNAME
















USER NOTES:







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












The Accelerated Soil Survey Program from the early 1970s until 1991 funded extensive soil mapping in 58 out of 67 counties Florida. 1296 soil profiles and 8325 horizons were sampled and analyzed at the Environmental Pedology Laboratory, Soil and Water Science Department, University of Florida. These samples were collected and analyzed to gain a better understand of Florida's soils. These data were stored mainly in hardcopy format and a now oupdated database system (RAMIS), which restricts the use to a very few scientists familiar with the dataset. The data collected was documented in hard copy format. There are 7 books containing around 2500 pages of data. The aim of this data mining project was to convert the data into digital format to facilitate global delivery via the Internet. Soil data had to be standardized and Meta data sets created. The Florida Soil Characterization Data Retrieval System (FSCDRS) is an interactive web based spatial database application that provides scientific information about the soil classification and soil-landscape in Florida. This platform will enable universal sharing with resource managers, transportation specialists, environmental scientists, consultants and all people in need of the soil data for planning and analyses.
The Principal Investigator (PI) of the FSCDRS project is Dr Sabine Grunwald, Assistant  Professor, Soil and Water Science department (SWS), University of Florida. The Scientific Project Team included Dr. W.G Harris, Soil & Water Science, UF and Mr. Wade Hurt, NRCS National Soil Survey Center, University of Florida. Additional team members included: Programming & Database Development, Dr. S. A. Bloom, Soil & Water Science, UF;  Data Assembly & GIS, Rosanna Rivero, V. Rammasundaram, M. Gao, B. Murphy, and K. Bloom.


Soil properties were estimated based on sample data collected, that typically include profile characteristics (descriptions of the site, soil classification, etc.), a large number of laboratory parameters and a description of each horizon.


Geospatial data could not be generated for these counties: Monroe, Sarasota, Manatee, Hillsborough, Pinellas, Gadsen, Lake, Seminole, Escambia, and Holmes. Sample data was not collected for any of these counties. 
Data from these three counties, Dixie, Calhoun, and Hamilton, was georeferenced based on Latitude and Longitude data, since there were not Soil Survey books avaialble for these counties.














A note concerning data scale:

Scale is an important factor in data usage. Certain scale 
datasetsare not suitable for some project, analysis, or
modelling 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.

1:250000 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 analyses. Every 
effort has been made to supply the user with data 
documentation. For additional information, see the 
References sectionand the Data Source Contact section of 
this documentation. For more information regarding scale 
and accuracy, see our web pages at:

http://www.geoplan.ufl.edu/education.html






REFERENCES: 






University of Florida Soil and Water Science Dept.:
http://grunwald.ifas.ufl.edu







DATA LINEAGE SUMMARY: 









Georeference process: 
Latitude and longitude for each sample point was 
derived from various possible methods:  
* The latitude and longitude as provided by the field team; 
* Soil Survey Maps on which the sampling locations were 
   marked, and coordinates in Albers projection extracted 
   from a custom developed tool.  Also a search tool based 
   on township, section and range was used to facilitated this 
   process;
* Utilization of the sample location description metadata to 
   project the described point onto a township, section and 
   range system from which the latitude and longitude could 
   be found 

Given the locations, both in geographic (Latitude/Longitude) 
and Albers projection, both pair of coodinates were added to 
the attribute table, along with a set of derived parameters that 
were created, based on existing lab data. The profile ID 
(example S01_001)  was used as a unique identifier to link with 
the soil database, and generate the rest of the attributes. These were:

HYDRICSTA = hydric status

MAXDEPTHSAND = maximum depth of sand (sand & 
loamy sand) in the profile
 
MINDEPTHROCK = depth at which bedrock was found 

INDIRECTWATERTABLE = depth of an indirect marker 
of the 'average' water table 

A detailed description of how each of these parameters 
was developed is shown, with more details in each of the 
entity attributes description. 

 ***HYDRICSTA, HYDRICRAT: HYDRIC CLASSIFICATION***

HYDRICCRAT Values: HH, NH, HN, NN
HYRDRICSTA Values: Hydric, Non-hydric 

In order to determine whether or not a hydric soil exists 
from a soil sample, two steps wer taken; using, (1) soil 
taxonomy (2) Florida soil series names. After having the 
soil classification for each soil, the taxonomic word itself 
was separated for each soil name into three parts: great 
group, suborder and order.

For example, the soil haplosaprists would result in haplo- 
(great group), -sapr- (suborder) and -ist (order). All soils 
follow this taxonomic structure. Using NRCS's methodology 
for their SSURGO hydric soil determination, it was concluded 
that a soil would be hydric using the following rules:
"	All histosols, except folists
"	Soils in the aquic suborder
"	Soils in the albolls suborder
"	Soils in the Salorthids great group

Other rules (i.e. using  aquic, pell, pachic and cumulic 
subgroups)  were mentioned in SSURGO's criteria; however, 
they did not apply to these samples.

Also included in the soil sample data is a soil name which 
is (i.e. Wachula Sandy Varient Fine Sand). F.D.E.P. has a 
list of soil names which they have determined to be "hydric" 
soils.  Using a search criteria looking for these names in the 
data will result in quality control for  the results from the first 
search method (using scieintific nomenclature).

The list is as follows:

Bessie,  Brighton, Croatan, Dania, Dirego, Dasher, Dorovan, 
Durbin, Everglades, Gator, Handsboro, Hontoon, Islamorada, 
Istokpoga, Kaliga, Kenner, Keylargo, Kingsland, Lauderhill, 
Maurepas, Montverde, Micco, Ocoee, Okeechobee, Okeelanta, 
Oklawaha,  Pahokee, Pamlico, Samsula, Shenks, Tamiami, 
Tavernier, Terra, Ceia, Timbalier, Tisonia, Tomoka, Torry, 
Weekiwachee, Wulfert, Ariaquolls, Buccaneer, Chobee, Copeland, 
Delray, Favoretta, Floridana, Gentry, Manatee, Nittaw, Santee, 
Humaquepts, Bakersville, Denaud, Johnston, Pickney, Placid, 
Rutlege, Sanibel, Sellers, Torhunta, Umbraqualfs, Brookman, 
Fellowship, Harbeson, Hicoria, Martel, Popash, Stockade, 
Bohicket, Homosassa, Peckish, Pellicer, Tidewater, McKee, 
Riomar, Turnbull, Pocomoke, Portsmouth

Using these criteria, the data were tagged  as hydric or 
non-hydric, using the two methods as described above. 
For a soil which was characterized as hydric in the first 
method, but not the second, an "HN" value can be seen 
in the HYDRICCRAT field. In contrast, if a soil did not follow 
the first method's criterea, then the field would show as an 
"NH" value. For soils not falling within either hydric method, 
an "NN" value would be generated, representing a non-hydric 
soil. Values of "HH" would represent a soil which was 
catergorized as a hydric soil by both means.  

***MAXDEPTHS, SANDY SOIL DEPTH***

Unit: Centimeters (cm)
Values: 0-999, a 999 indicating unknown depth, and a 
0 indicating no depth

To generate the layer, there were three steps to follow: 
a) Define what we mean by "Deep sandy"; b) Determine 
the soil type for any given horizon in a given profile, and 
c) Determine if a given profile matches the definition.

Rather than setting some arbitrary limit, e.g., the top x 
cm belonging to a specified set of  soil types, the data 
was expressed as the depth in a given profile to which 
soils of a defined set extend.

DETAILED DESCRIPTION OF PROCEDURE

To determine the maximum depth of sand in any given 
profile requires:

(1) that each horizon in the profile be categorized by using 
the sand, silt and clay values to place the horizon on the 
standard texture triangle; and (2) that the profile be scanned 
from the surface downwards horizon by horizon for membership 
in the 'sand' and 'loamy sand' categories. When a horizon is 
found not to fall into one of these two categories, the upper 
depth of that horizon was taken as the 'maximum depth of sand' 
in that profile. If all horizons sampled fell into the two categories, 
the value '999' was assigned and should be taken to mean that 
the maximum depth of sand was unknown but exceeded the 
maximum depth sampled. In all cases, the units associated with 
depth are centimeters. 
 
The categorization of a horizon required:  

(1) The development of an algorithm that can project a 
point based on the composition percentages into the 
triangle and, conversely, can convert a point in the triangle 
into an equivalent point in a Cartesian coordinate system; 
(2) The conversion of the vertices of the polygons in the 
triangle for all soil types into such a coordinate system; 
The mapping of those coordinates into a graphic system 
such that each soil type was uniquely colored; and 

(3) The projection of a given horizon into that graphic 
system using the composition percentages to determine 
the color of the pixel at that location which, in turn, 
indicates the soil type. 

Details and derivation of the algorithm can be found at 
http://flsoils.ifas.ufl.edu/Texture.htm.  

***INDIRECTW, LOCATION OF WATER TABLE, *****

Unit: Centimeters (cm)
Values: 0-999, a 999 indicating unknown depth, and a 
0 indicating no depth

Using the soil profile taxonomy  for horizons a search was 
conducted in the database for the first horizon at which 
"gleying" occurs.  Gleying being a redox product of a soil 
having been waterlogged for an extended period of time. 
Gleying is commonly denoted as a lower-case "g"  in a 
horizon description (i.e., Bg) The first horizon from the surface 
to contain a gleying indicator in its nomenclature would hint 
at the strong possibility of waterlogging at this depth. Note 
that some hydric soils might have a water table which comes 
to the surface of the soil, where the entire soil profile would 
be inundated with water. 

****MINDEPTHR, DEPTH OF BEDROCK *******

Unit: Centimeters (cm)
Values: 0-999, a 999 indicating unknown depth.

By searching the profile data, looking for an "R" horizon 
will determine the depth at which bedrock occurs.
Process Date: June 2003 - February 2004


GeoPlan received this dataset from The Soil and Water Science 
Department - Institute of Food and Agricultural Sciences (IFAS) - 
University of Florida (http://grunwald.ifas.ufl.edu) in 2004. The 
data was received on CD and was in shapefile format. The shapefile 
was in the following projection: FGDL Albers HPGN

- Added DESCRIPT field based on SOILNAME
- 27 points fell in the Gulf of Mexico and were deleted from the 
shapefile. These points had an ID equal to the  following: 
S01_105, S07_003, S15_016, S19_019, S23_012, S23_206, 
S23_207, S23_211, S24_001, S24_002, S24_003, S25_200, 
S25_201, S25_202, S30_001, S30_002, S30_003, S30_004, 
S30_005, S30_006, S35_001, S35_002, S35_003, S35_004, 
S35_005, S38_030, S66_200.
Process Date: 20040000









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:			Institute of Food and Agricultural Science (IFAS)
			Soil and Water Science Department - GIS Laboratory
Abbr. Name:		Florida County Soil Survey
Address:		McCarty Hall A 1184,
			Soil and Water Science Department, 
			Institute of Food and Agricultural Sciences (IFAS) 
			University of Florida
			Gainesville, Florida
			32611-0290
Phone:			(352) 392-1951

Web site:		http://grunwald.ifas.ufl.edu
E-mail:			SGrunwald@mail.ifas.ufl.edu







FGDL CONTACT:

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