Derivation of ground surface and vegetation in a coastal 

Florida wetland with airborne laser technology 

By Ellen A. Raabe, Melanie S. Harris, Ramesh L. Shrestha, and William E. Carter 

Open-File Report 2008–1125 

U.S. Department of the Interior 

U.S. Geological Survey 
U.S. Department of the Interior 

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey 

Mark D. Myers, Director 

U.S. Geological Survey, Reston, Virginia 2008 

Revised and reprinted: 2008 

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Suggested citation:
 

Raabe, E.A., Harris, M.S., Shrestha, R.L., and Carter, W.E., 2008, Derivation of ground surface and
 

vegetation in a coastal Florida wetland with airborne laser technology, U.S. Geological Survey,
 

Open-File Report 2008-1125, Saint Petersburg , FL, 41 p.
 

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endorsement by the U.S. Government.
 

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ii 
Contents 

Figures................................................................................................................................................................................. iii
 

Photos ..................................................................................................................................................................................iv
 

Tables...................................................................................................................................................................................iv
 

Abstract.................................................................................................................................................................................1
 

Introduction ......................................................................................................................................................................1
 

Study Area........................................................................................................................................................................2
 

Methods................................................................................................................................................................................5
 

Ground Control ................................................................................................................................................................5
 

ALSM Data Acquisition and Processing ....................................................................................................................6
 

Digital-Surface Model ...................................................................................................................................................7
 

Results...................................................................................................................................................................................8
 

Bare-Earth DSM ..............................................................................................................................................................8
 

Vegetation-Canopy DSM.............................................................................................................................................16
 

Land-Cover Maps..........................................................................................................................................................21
 

Shoreline ........................................................................................................................................................................26
 

Geomorphic-Profile Transects ...................................................................................................................................27
 

Discussion ..........................................................................................................................................................................32
 

Acknowledgments ............................................................................................................................................................32
 

References Cited ..............................................................................................................................................................33
 

Appendix I...........................................................................................................................................................................35
 

Figures 

Figure 1. Locations of airborne laser-altimetry flights at Lukens Creek, Bird Creek, and Waccasassa,
 

August, 17, 1999. ..................................................................................................................................................................3
 

Figure 3a, b. Differences between field-surveyed and surface-model elevations using 2-, 5-, and 10-m
 

Figure 16. Transect A-A1 across Lukens Creek showing profile derived from bare-earth and canopy-


Figure 2. Example data cloud and break points for functional landscape units. ...................................................8
 

filters for a) marsh at Lukens Creek, b) forest and thick marsh. ................................................................................9
 

Figure 4. (a) Orthophotoquad, and (b) ground-surface DSM at Lukens Creek. .....................................................10
 

Figure 5. (a) Orthophotoquad, and (b) ground-surface DSM at Bird Creek and Waccasassa. .........................10
 

Figure 6. Bare-earth digital-surface model at Lukens Creek derived from ALSM. ..............................................12
 

Figure 7. Bare-earth digital-surface model at Bird Creek derived from ALSM....................................................13
 

Figure 8. Bare-earth digital-surface model at Waccasassa River derived from ALSM. ....................................14
 

Figure 9. Canopy-height digital-surface model at Lukens Creek derived from ALSM. .......................................17
 

Figure 10. Canopy-height digital-surface model at Bird Creek derived from ALSM. ..........................................18
 

Figure 11. Canopy-height digital-surface model at Waccasassa River derived from ALSM. ...........................19
 

Figure 12. Lukens Creek land-cover categories derived from ALSM. ....................................................................22
 

Figure 13. Bird Creek land-cover categories derived from ALSM. .........................................................................23
 

Figure 14. Waccasassa River land-cover categories derived from ALSM. ..........................................................24
 

Figure 15. ALSM-derived shoreline compared to 1:24,000 hydrography (USGS) shoreline at Bird Creek.......26
 

surface models..................................................................................................................................................................28
 

Figure 17. Transect B-B1 showing profile from Lukens Creek across tidal marsh and forest remnants.........29
 

Figure 18. Transect C-C1 showing profile from upper reach of Lukens Creek to forest and relict dunes. .....30
 

Figure 19. Transect D-D1 showing profile from Waccasassa River to a meander on Bird Creek....................31
 

iii 
Photos 

1. Low marsh at Site 1, Lukens Creek. ............................................................................................................................4
 

2. Black needlerush at Site 2, Bird Creek ......................................................................................................................4
 

3. Coastal forest at Site 3, Waccasassa River ..............................................................................................................5
 

4. Differential GPS roving antenna in high marsh at Lukens Creek..........................................................................6
 

5. Roving antenna and geodimeter in black-needlerush marsh ...............................................................................6
 

6. Transition from tidal marsh to forest at Bird Creek ...............................................................................................11
 

7. Morbid forest with standing dead Sabal palms at Lukens Creek .......................................................................11
 

8. Bird Creek levee with scrub and coastal-forest vegetation.................................................................................15
 

9. Sinkhole and sawgrass at Lukens Creek .................................................................................................................15
 

10. Thick sawgrass along tidal-creek tributary to Waccasassa River ...................................................................16
 

11. Tall, thick-canopied hydric hammock in summer ...............................................................................................20
 

12. Open-canopy oak and palmetto scrub in sand hills.............................................................................................20
 

13. Recovery of sand-hill oak scrub following fire management............................................................................21
 

14. Scrubby flatwood along open sand road at Trail 8..............................................................................................25
 

15. Game trails in high marsh at Lukens Creek...........................................................................................................25
 

Tables 

Table 1. Redundancy in DGPS ground survey. .............................................................................................................5
 

Table 2. Data collection and technical specifications................................................................................................7
 

Table 3. Orthometric heights (O.H.) of ground control points (GCP) and base stations. .....................................35
 

iv 
Derivation of ground surface and vegetation in a coastal

Florida wetland with airborne laser technology 

By Ellen A. Raabe, Melanie S. Harris, Ramesh L. Shrestha, and William E. Carter 

Abstract 

The geomorphology and vegetation of marsh-dominated coastal lowlands 

were mapped from airborne laser data points collected on the Gulf Coast of Florida 

near Cedar Key. Surface models were developed using low- and high-point filters to 

separate ground-surface and vegetation-canopy intercepts. In a non-automated 

process, the landscape was partitioned into functional landscape units to manage the 

modeling of key landscape features in discrete processing steps. The final digital 

ground surface-elevation model offers a faithful representation of topographic relief 

beneath canopies of tidal marsh and coastal forest. Bare-earth models approximate 

field-surveyed heights by + 0.17 m in the open marsh and + 0.22 m under thick 

marsh or forest canopy. The laser-derived digital surface models effectively delineate 

surface features of relatively inaccessible coastal habitats with a geographic coverage 

and vertical detail previously unavailable. 

Coastal topographic details include tidal-creek tributaries, levees, modest 

topographic undulations in the intertidal zone, karst features, silviculture, and relict 

sand dunes under coastal-forest canopy. A combination of laser-derived groundsurface and canopy-height models and intensity values provided additional mapping 

capabilities to differentiate between tidal-marsh zones and forest types such as mesic 

flatwood, hydric hammock, and oak scrub. Additional derived products include finescale shoreline and topographic profiles. The derived products demonstrate the 

capability to identify areas of concern to resource managers and unique components 

of the coastal system from laser altimetry. 

Because the very nature of a wetland system presents difficulties for access 

and data collection, airborne coverage from remote sensors has become an accepted 

alternative for monitoring wetland regions. Data acquisition with airborne laser 

represents a viable option for mapping coastal topography and for evaluating habitats 

and coastal change on marsh-dominated coasts. Such datasets can be instrumental in 

effective coastal-resource management. 

Introduction 

Airborne laser-swath mapping (ALSM) systems collect range data in the form of timed pulse returns 

from an airborne laser. The two-way travel time (TWTT) of the laser pulse represents an active 

measurement of the distance from the ground surface to the sensor (Fowler et al., 2001). The laser-ranging 

vectors can be processed with information from Differential Global Positioning System (DGPS) and aircraft 

position to derive three-dimensional coordinates (x, y, z values) of each ground position (Shrestha et al., 

1999). Objects on the Earth surface, such as buildings and trees, may reflect the laser pulse before it reaches 

the Earth surface (Kraus and Pfeifer, 1998). A series of post-processing steps is therefore required to 

extract a bare-earth digital-surface model (DSM) or vegetation characteristics from the cloud of points 

identified by the laser returns (Axelsson, 1999; Blair et al., 1999; Vosselman, 2000). The acquisition of 

1 
distance measurements with an airborne laser altimeter will be referred to as laser altimetry in this report. It is 

also known as Light Detection and Ranging (LIDAR). 

Since the very nature of a wetland presents difficulties for access, navigation, and data collection, 

airborne coverage from remote sensors has become a widely accepted alternative for monitoring wetland 

regions. Extensive work has been conducted in wetlands using aerial photography, satellite imagery, and 

airborne sensors, but the earlier body of work focuses on classification and change detection using spectral 

reflectance of the vegetation and land surface (Lee and Lunetta, 1995; Raabe and Stumpf, 1997). An 

essential but missing component is an accurate representation of the surface topography that dictates 

submergence, exposure, salinity, and habitats in coastal lowlands (Lyon and McCarthy, 1995; Mitsch and 

Gosselink, 2000). 

Wetlands are responsive to minor differences in surface-drainage network, flooding regime, 

topography, and sediment movement (Stoddard et al., 1989; Montague and Odum, 1997; Day et al., 1998). 

Currently available digital elevation along the marsh-dominated Gulf Coast of Florida has a horizontal 

resolution of 30 m and vertical resolution of 1.5 m, or 5 ft (USGS, 2007). This level of topographic detail is 

inadequate for understanding tidal processes in a coastal region, where elevation differences of centimeters to 

decimeters correspond to distinct tidal-flood zones and habitats (Clewell, 1997; Stumpf and Haines, 1998; 

Williams et al., 1999). Morphological characteristics for hydrodynamic modeling have been derived from 

airborne laser data (Gomes Pereira and Wicherson, 1999; Sallenger et al., 2003), but Baltsavias (1999) 

argued that the geomorphology derived from most laser-altimetry processing algorithms is ‘non-intelligent’ 

and eliminates important topographic features. 

Extraction of the ground surface to + 0.10 m under vegetation canopy has been achieved in some 

studies but required extensive mathematical modeling of the surface (Kraus and Pfeifer, 1998; Ackerman, 

1999). A 10-m grid has been used to determine the ground surface under a tree canopy but without field 

verification (Means et al., 2000). The typical vegetation cover of tidal marshes of Florida’s Gulf Coast is 0.3 

to 1.4 m tall (Clewell, 1997). Earlier laser-altimetry data on this marsh coast presented vertical errors on the 

order of + 0.40 m, attributable to laser-pulse detection errors and thick vegetation (Carter et al., 1999). Test 

flights with improved calibration methods over a bare road surface produced a vertical accuracy of + 0.10 m 

or better (Shrestha et al., 1999). 

Knowing the instrument accuracy that was achievable over a non-vegetated surface, a method was 

developed to derive a representation of ground surface in the coastal marsh and forest with more detail than 

the currently available digital models (Iavarone, 2002). In this non-automated approach, the coastal region 

was partitioned into unique landscape elements, and each element was processed separately. Low- and highpoint filters were used to extract ground-intercept and vegetation-intercept data points for bare-earth and 

vegetation-canopy surface models. Filter search space was adjusted to determine the optimal balance between 

generalizing elevation under canopy and preservation of topographic detail. We compared ground-surface 

DSM derived from 2-, 5-, and 10-m filters to field-collected orthometric heights (O.H.) NAVD88. 

This report covers several objectives: 

•	 to separate ground-surface intercepts from vegetation intercepts for each landscape element, 

•	 to model the ground surface from laser-derived O.H. to within + 0.2 m of ground-control O.H. with a 

horizontal resolution of 20 m or less, 

•	 to model the vegetation canopy across marsh and coastal forest, 

•	 to derive profiles, shoreline, habitat, and land-cover parameters. 

Study Area 

Tidal marshes stretch virtually unbroken along Florida’s Big Bend coast (Fig. 1). The coastal 

landscape is a mosaic of tidal creeks, tidal marsh, elevated coastal hammocks, and coastal forest inland of the 

marsh (Raabe and Stumpf, 1997). Underlying karst limestone is near surface or exposed, and the Floridan 

aquifer flows through seeps and springs into the tidal marshes (Rupert and Arthur, 1997; Raabe and 

Bialkowska-Jelinska, 2007). Relict sand deposits provide occasional relief in the coastal lowlands, and 

2 
surface features reflect underlying limestone-fracture patterns at some locations (Hine et al., 1988; Vernon, 

1951). The tide range is 1 m, and local topographic gradients are 1:1000 or less (Clewell, 1997; Raabe and 

Stumpf, 1997). Narrow elevation ranges of less than 0.5 m separate tidal submerged, emergent, and upland 

habitats (Clewell, 1997; Williams et al., 1999). Coastal-forest morbidity and expansion of the tidal marsh 

inland have been attributed to the relatively flat terrain and recent sea-level rise on this coast (Raabe et al., 

2004; Stumpf and Haines, 1998; Williams et al., 1999). 

Figure 1. Locations of airborne laser-altimetry flights at Lukens Creek, Bird Creek, and Waccasassa, 

August, 17, 1999. 

Airborne laser flights were undertaken in Levy County, Florida, near Cedar Key and Waccasassa 

River (Fig. 1). Flight paths included Lukens Creek (1), Bird Creek (2) and Waccasassa (3). Site 1 was 

selected for shallow tidal creeks, extensive low marsh, a recent burn, and relict sand dunes in the adjoining 

uplands (Photo 1). Site 2 was selected as representative of a deep, spring-fed tidal creek, near-surface 

limestone, and a thick cover of the high marsh, black needlerush, Juncus romerianus (Photo 2). Site 3 was 

selected to cover the transition zone between tidal marsh and coastal forest along the Waccasassa River 

(Photo 3). The sites lie within the Cedar Key Scrub State Reserve and the Waccasassa Bay State Preserve 

and were accessed via boat, airboat, and dirt road to obtain field-based ground elevations and 

reconnaissance. 

3 
Photo 1. Low marsh at Site 1, Lukens Creek. 

Photo 2. Black needlerush at Site 2, Bird Creek. 

4
 
Photo 3. Coastal forest at Site 3, Waccasassa River. 

Methods 

Ground Control 

Field surveys with DGPS and geodimeter were conducted in the salt marsh and adjoining forest to 

collect ground-control elevation measurements. Sites were selected to represent elevations from tidal 

wetlands to elevated uplands and from sparsely vegetated to thick-canopied habitats. DGPS data were 

collected with a roving kinematic antenna and a stationary base station linked to local vertical control (Raabe 

et al., 1996). The DGPS antennas were mounted on 2-m poles for unobstructed data acquisition above 

marsh vegetation (Photo 4). The geodimeter was employed to survey a closed-level loop from DGPS 

ground control in the open marsh to ground-control sites in the closed-canopy forest (Photo 5). Eighty-five 

horizontal, x, y-value (UTM 17R NAD83) and vertical, z-value (NAVD88) ground measurements were 

collected. Four positions were reoccupied for redundancy (Table 1). Position 001 was re-occupied twice. 

Overall DGPS survey vertical accuracy was 0.008 + 0.005 m. Surveyed field elevations ranged from 0.28 to 

1.7 m NAVD88. Vertical ground control was used to evaluate and to select an effective method for deriving 

a ground-surface model in a vegetated environment from laser altimetry (Appendix I). 

Table 1. Redundancy in DGPS ground survey. 

Position Northing Difference (m) Easting Difference (m) Vertical Difference (m) 

001 0.000 0.000 0.0170 

012 0.002 0.111 0.0010 

023 0.097 -0.020 0.0130 

037 0.000 0.001 0.0330 

Mean/Std 0.02/0.04 0.018/0.05 0.019/0.014 

5 
Photo 4 Differential GPS roving antenna in high marsh at Lukens Creek. 

Photo 5. Roving antenna and geodimeter in black-needlerush marsh. 

ALSM Data Acquisition and Processing 

ALSM data were collected at three pre-specified locations on August 17, 1999 (Fig. 1). Tide range 

for the day was –0.312 to 0.550 m, and the timing of the flights coincided with the lowest tides of the day in 

an effort to capture the details of the tidal-marsh-drainage network (Table 2). First and last return with 

intensity were recorded for each pulse. Base stations, part of a previously established DGPS vertical 

6 
network (Raabe et al., 1996), were occupied near Cedar Key and Waccasassa River. Accuracy, precision, 

and calibration of laser-instrument measurements are discussed by Shrestha et al. (1999). 

Laser-altimetry data were processed with proprietary software from Operational Technologies 

Corporation (Carter et al., 1999). Horizontal coordinates (x,y) were converted to Universal Transverse 

Mercator (UTM) 17R NAD83. Vector lengths were converted to elevation (z values) as NAVD88 

orthometric heights (O.H.). Intensities (I) for each laser pulse were recorded and included in the dataset. 

Table 2. Data collection and technical specifications. 

Data Collection Technical Specifications ALSM Specifications 

August 17, 1999 ALTM Model 1210, Optech Inc. 10kHz pulse repetition rate 

11:30 am to 2:10 pm 

Lukens Creek (6 km2) 

Bird Creek (4 km2) 

Waccasassa (4.5 km2) 

Mounted on Cessna 337 

Ashtech GPS and Aplanix INS 

Class IV Laser 

1064 nm Laser wavelength 

12 Hz scan rate 

+/-19 degree scan angle 

500 m flying altitude 

60 m/s average speed over ground 

Tide level -0.312 to -0.024 m MSL 10,000 pulse per second 344 m swath width; 65% overlap 

2 DGPS Base Stations Single return & intensity 30 cm diameter footprint 

Digital-Surface Model 

A bare-earth Digital-Surface Model (DSM) was developed in phases. Flight paths were pieced 

together to create a mosaic for each site. The team developed an interactive filter program to extract lowest or 

highest points (z values) from each mosaic with adjustable parameters specified by the analyst. Parameters 

included filter cell size, number of lowest or highest points per cell, and the option of defining an elevation 

minimum and/or maximum. Definition of a lower and upper limit for each pass allowed the analyst to 

develop layers representing functionally different portions of the landscape and to separate ground intercepts 

from vegetation intercepts. 

The choice of planar-grid spacing from fine (1 m) to coarse (20 m) in post-processing was 

fundamental to retaining detail where possible while modeling actual ground surface under vegetation 

canopy. Where true ground returns were closely spaced, fine-cell spacing could be used to model the ground 

surface without interference from vegetation canopy. Where suitable ground returns were sparsely 

distributed, a coarse-cell spacing optimized extraction of true ground returns and minimized interference 

from vegetation intercepts. By partitioning the landscape into functional units, the analyst could retain details 

of topographic features without modeling vegetation artifacts under thick canopy. 

An initial surface was created with ordinary kriging to interpolate low-point-filter (LPF) results to a 

1-m grid. Preliminary break points for landscape elements were identified in the z-value histogram and 

corroborated with field measurements of O.H. and vegetation height from previous elevation surveys (Raabe 

et al., 1996; Raabe et al., 2000; Williams et al., 1999). 

Break points for three zones were established, and a mask was created for each layer. Data points 

below -0.5 m were determined to be in error and were eliminated by setting –0.5 as the minimum elevation. 

Z values between -0.5 and 0.2 m represent the un-vegetated and submerged portions of tidal creeks, 

tributaries, and water bodies. The first mask was created to partition this tidal-drainage portion of the 

landscape. The initial 1-m DSM under this mask was retained to preserve maximum detail of tidal-creek 

morphology. 

The second mask was derived from a 2-m high-point-filter (HPF) where z values exceeded 1.9 m. 

This mask separated elevated ground and thickly forested areas from low-elevation features, marsh, and 

single-storied scrub habitat. The final mask was created to include landscape elements with elevations 

greater than 0.2 m and excluded from the 1.9-m HPF partition. This third partition included tidal marsh, 

grassland, and scrubland along the coast. An example of a data cloud and the three landscape partitions are 

shown in Figure 2. 

7 
Figure 2. Example data cloud and break points for functional landscape units. 

Subsequent surface models for each zone were derived from LPF series and evaluated against fieldsurveyed ground control. Parameters were varied one at a time to facilitate comparisons between interpolated 

surfaces and ground-control O.H. Filter cell size was varied sequentially to isolate laser-pulse returns that 

fully penetrated the vegetation, while maintaining as much detail of the topography as possible. Low-point 

filters of 2, 5, and 10 m were applied iteratively to each set of data points. Only one point per cell was 

selected for each 2-m pass. One, three, and five points per cell were selected and averaged for each 5- and 

10-m pass. Local topographic charts show no elevation in the area exceeded 4.6 m (15 ft). A corresponding 

ceiling of 5 m was set in the LPF extraction process. 

Results of each iteration of the LPF were interpolated to a 2-m grid using point kriging and a search 

ellipse of 15 (2 and 5 m) or 30 m (10 m). A surface was created by interpolating between the data points and 

by re-combining the layers to create a single elevation model. A comparison was made between modeled z 

values and corresponding field-survey elevations. The absolute difference between each set of points was 

calculated and summary statistics on the differences were obtained. 

Results 

Bare-earth and canopy-height models, land-cover categories, shoreline, and topographic profiles 

were derived from the laser-altimetry data. The development and selection of a bare-earth or ground-surface 

DSM was based on a “best-fit” approach to minimize differences between modeled z values and field-survey 

O.H. The data were further explored for the potential of identifying land-cover categories, geomorphology 

from profiles, and shoreline. 

Bare-Earth DSM 

Z values in the laser-acquired ground-surface DSM were compared with field-collected O.H. to 

assess correspondence of the DSM to ground-control elevations (Fig. 3). The 2-m LPF provides the “bestfit” model for the marsh ground surface at Lukens Creek with a correspondence of 0.11 + 0.06 m (Fig. 3a). 

8 
This filter resolution retains considerable detail of the marsh surface with little interference from vegetation 

intercepts. The variability in standard deviation is attributable to three factors: 1) the variability of true surface 

elevation within a 2-m plot, 2) the limited probability that a field-surveyed point corresponds precisely to the 

laser-ground intercept, and 3) interpolation and model artifacts. 

In thickly vegetated areas, the coarser 10-m filter achieved a 0.14 + 0.08-m correspondence with 

field-surveyed O.H. (Fig. 3b). The 10-m filter provided the “best-fit” ground-surface model under forest 

canopy at all sites, and thick marsh grasses at Bird Creek and Waccasassa. LPF extractions at 2 m and 5 m 

retained too many vegetation intercepts to represent the ground surface accurately. The DSM from the 10-m 

LPF retains the general topographic elements of the landscape. Although it lacks the detail obtained in the 

marsh at Lukens Creek, the model is an improvement over existing surface models (USGS, 2007). 

Figure 3a, b. Differences between field-surveyed and surface-model elevations using 2-, 5-, and 10-m 

filters for a) marsh at Lukens Creek, b) forest and thick marsh. 

Final model results were based on filters using one data point per filter cell. Filtered points were 

interpolated and combined in a 2-m grid to create a final DSM. Three grids, tidal creeks, marsh, and forest, 

were combined into one DSM for each area, showing details of tidal creeks, marsh-surface features, and the 

topography beneath the forest (Figs. 4, 5). 

9 
Figure 4. (a) Orthophotoquad, and (b) ground-surface DSM at Lukens Creek. 

Figure 5. (a) Orthophotoquad, and (b) ground-surface DSM at Bird Creek and Waccasassa. 

Color-coded versions of ground-surface DSM are shown in Figures 6, 7, and 8. The majority of 

tidal marsh occurs at elevations of 0.2 to 0.6 m. The transition from tidal marsh to forest begins at 

approximately 0.6 to 0.7 m (Photo 6). Morbid forested areas show as individual spikes scattered across the 

interior tidal marsh in the surface model (Fig. 6 and Photo 7). Where trees are still alive, soil and root 

10 
mounds, approximately 0.5 m high, contrast with the surrounding lowered land surface (Raabe et al., 2007; 

Raabe et al., 2004). Forest floor below ~0.9 m indicates low-elevation swamp areas susceptible to flooding 

and storm-surge influence. Relict sand dunes at Lukens Creek occupy the 1.7 to 4.6-m range (Fig. 6). 

Elevations in the Bird Creek and Waccasassa area do not exceed 1.6 m (Figs. 7, 8). Other important features 

include high levees along Bird Creek and Waccasassa River (Photo 8), silviculture activities, karst-controlled 

tidal creeks, and sinkholes (Photo 9). An August acquisition date resulted in intercepts with thick canopy 

forest and interfered with ground intercepts. Artifacts of the LPF process and intercepts with thick forest 

canopies are indicated in the forested areas as no data. 

Photo 6. Transition from tidal 

marsh to forest at Bird 

Creek. 

Photo 7. Morbid forest with 

standing dead Sabal palms 

at Lukens Creek. 

11 
Figure 6. Bare-earth digital-surface model at Lukens Creek derived from ALSM. 

12
 
Figure 7. Bare-earth digital-surface model at Bird Creek derived from ALSM. 

13
 
Figure 8. Bare-earth digital-surface model at Waccasassa River derived from ALSM. 

14
 
Photo 8. Bird Creek levee with scrub and coastal-forest vegetation. 

Photo 9. Sinkhole and sawgrass at Lukens Creek. 

15
 
Vegetation-Canopy DSM 

A vegetation-canopy DSM was derived from a maximum-intercept DSM and the bare-earth DSM to 

obtain a surface model of canopy height in two steps. The results of a 2-m HPF in marsh zones and a 5-m 

HPF in forested zones were interpolated to a 2-m grid to derive a surface model of maximum-intercept 

values. Next, the bare-earth DSM was subtracted from the maximum-intercept DSM to obtain a surface 

model of vegetation-canopy heights, as normally observed from ground level. 

Figures 9 - 11 show color-coded vegetation-canopy DSM. The boundary between the tidal marsh 

and the coastal forest is demarcated at canopy heights of ~1.4 m. Tall marsh types near this canopy height 

include black needlerush and sawgrass (Photo 10) and correspond to estimates of tidal-marsh canopy height 

made by Clewell (1997). Tall trees in hydric hammock exceeded 18 m in height (Photo 11). At Lukens 

Creek, considerable coastal-forest canopy is less than 7 m in height. This includes palmetto scrub, oak 

scrub, and scrubby flatwood on the sand hills (Photo 12). Data acquisition during August, with full-leaf 

cover, facilitated the extraction of the canopy-surface model from laser altimetry. Canopy-height 

characteristics can be obtained during summer when trees are fully leafed. However, winter-data acquisition 

would be preferable for a bare-earth model. 

Photo 10. Thick sawgrass along a tidal-creek tributary to Waccasassa River. 

16 
Figure 9. Canopy-height digital-surface model at Lukens Creek derived from ALSM. 

17
 
Figure 10. Canopy-height digital-surface model at Bird Creek derived from ALSM. 

18
 
Figure 11. Canopy-height digital-surface model at Waccasassa River derived from ALSM. 

19
 
Photo 11. Tall, thick-canopied hydric hammock in summer. 

Photo 12. Open-canopy oak and palmetto scrub in sand hills. 

20
 
Land-Cover Maps 

Preliminary habitat maps were created from unsupervised classifications of bare-earth and canopyheight surface models and intensity values. The land-cover and habitat categories were selected to 

correspond with management programs for Cedar Key Scrub Reserve and Waccasassa Bay State Preserve 

(FDEP, 2005). An unsupervised classification was conducted using the bare-earth DSM, canopy-height 

DSM, and intensity values from the laser-altimetry dataset. Preliminary maps were created for each area 

(Figs. 12 - 14). Categories were validated through field reconnaissance, comparison with existing maps, and 

aerial photography. Categories for tidal marsh at four different flooding zones correspond to the single 

management category of estuarine tidal marsh. Sawgrass or depression wetlands occur in low-elevation 

swales between sand hills. Categories of sand-hill oak scrub and palmetto scrub were added to mesic and 

scrubby-flatwood categories to delineate distinct elevation and canopy-cover differences at high points on the 

sand hills and the low palmetto cover in open areas. Hydric hammock and mesic flatwood were more 

difficult to separate due to similarities in canopy height and canopy composition. Canopy height plays a 

greater role in this type of classification. Thus, differences between old-growth stands and fire-management 

recovery may be monitored (Photo 13). Burn areas in the marsh at Lukens Creek, sinkholes, limestone 

highs, silviculture, roads (Photo 14), and trails (Photo 15) can be seen in this map product. 

Photo 13. Recovery of sand-hill oak scrub following fire management. 

21 
Figure 12. Lukens Creek land-cover categories derived from ALSM. 

22
 
Figure 13. Bird Creek land-cover categories derived from ALSM. 

23
 
Figure 14. Waccasassa River land-cover categories derived from ALSM. 

24
 
Photo 14. Scrubby flatwood along open sand road at Trail 8. 

Photo 15. Game trails in high marsh at Lukens Creek. 

25
 
Shoreline 

Detailed shorelines were also extracted from the bare-earth DSM at the 0.2-m contour. This shoreline 

is more comprehensive than existing digital shoreline as shown in Figure 15 (FGDL, 2008; USGS, 2008). 

In an environment susceptible to flooding, storm impact, and sea-level rise, the morphology of tidal-creek 

drainages and changes over time are critical. 

Figure 15. ALSM-derived shoreline compared to 1:24,000 hydrography (USGS) shoreline at Bird Creek. 

26 
Topographic-Profile Transects 

Topographic profiles across bare-earth and canopy DSM were prepared as illustrations of marsh and 

coastal-forest geomorphology. Transects A-A1, B-B1, and C-C1 are located at Lukens Creek (Fig. 6). 

Transect D-D1 is located at Bird Creek (Fig. 7). Elevation point data for each transect were extracted from 

ground- and canopy-surface models and filtered with a 6-m-centered moving average (Figs. 16-19). The 

vertical axis is exaggerated (VE) in each profile to highlight subtle topographic relief. Notable characteristics 

are indicated by red arrows on Figures 16-19 and are listed below. 

•	 Water level is depicted at 0.3 m for illustration purposes. 

•	 Tidal-marsh elevations range from 0.3 to 0.9 m MSL and are marked for reference. 

•	 The upper-elevation range of the tidal marsh, ~0.06 – 0.09 m, represents a transition from marine to 

terrestrial influence. Elevations below 0.9 m in the coastal-forest canopy indicate areas susceptible to 

flooding from both tidal and freshwater-surface flow. 

•	 Lukens Creek has distinct tidal-creek levees (Fig. 16), but they are considerably lower than levees on 

Bird Creek (Fig. 19). 

•	 Relict sand dunes are locally important, supporting an endemic oak-scrub habitat and associated faunal 

species (Figs. 16, 18). 

•	 Sinkholes (circular features by air) appear as water-filled depressions in the transects (Figs. 16, 17). 

•	 Forest remnants within the marsh: usually salt scrub and living or dead trees (Figs. 17, 18; Photos 7, 

15). 

•	 The absence of clearly defined surface drainage is characteristic of areas with thin sediment and nearsurface limestone (Fig. 17). 

•	 Where the transect crosses an historic shoreline or forest boundary, the historic-feature zone is marked 

(all figures; Raabe et al., 2004). 

•	 Notches just to the interior edge of tree stands occur in the landward forest stands. Forest remnants 

closer to the coast appear to be missing the feature. 

•	 Recent headward erosion of tidal creek is highlighted by low topography at the marsh interior (Fig. 18). 

Loss of forest soils and slow-sedimentation processes create a temporary topographic low during marine 

transgression (Raabe et al., 2004; Raabe et al., 2007). 

The profiles show variations between high- and low-marsh canopies, and different creek and shoreedge forms, such as sloping or steep banks. Two characteristics, a canopy height less than 1.5 m and an 

elevation range of 0.3 to 0.9 m MSL (NAVD88), are key parameters of the tidal marsh. Higher elevations in 

the marsh tend to be toward the gulf, along levees, and high-marsh inland. 

The coastal-forest elevation in these profiles ranges from about 0.5 to 2.5 m MSL (NAVD88). 

Forest-canopy height near the tidal marsh does not exceed 9 m. Game trails (Photo 15) and feral-hog ruts are 

common along this coast. Regardless of whether the forest-edge notches are the result of animal activity, a 

geomorphic process, or both, the coastal forest is vulnerable to flooding at these low points. Such notches 

are missing in forest remnants close to the coast, although a relict notch may be indicated where the forest 

has already converted to tidal influence. 

27 
VE = 40x 

10

 8

 6

 4

 2

 0 

0 

marsh/forest 

boundary circa 1858 

tidal-creek 

levees 

relict 

sand hill 

notch at 

forest edge 

notch at 

forest edge 

Bare-earth surface 

Coastal marsh 

Coastal forest 

Canopy height 

0.9 

0.3 

116 232 348 464 580 696 812 928 1044 1160 m 

A A1 sinkhole intersect Lukens Creek Gulf Cedar transect B-B1 and tributary of Key 

Mexico 

meters (MSL NAVD88) 

Figure 16. Transect A-A1 across Lukens Creek showing profile derived from bare-earth and canopy-surface models. 
VE = 40x 

8
 

6
 

4
 

2
 

meters (MSL NAVD88) 

coalescing 

sinkholes 

marsh/forest 

boundary 

circa 1858 

absence of 

defined drainage 

break in 

forest canopy 

forest 

remnant 

forest 

remnant 

Bare-earth surface 

Coastal marsh 

Coastal forest 

Canopy height 

Lukens Creek 

0.3-0.9 m 

0 

0 48 96 120 168 206 254 302 350 398 m
 

B B1

Gulf of Mexico north intersect transect A-A1 

Figure 17. Transect B-B1 showing profile from Lukens Creek across tidal marsh and forest remnants. 
VE = 40x 

meters

(MSL NAVD88) 

8 

6 

4 

2 notch at 

forest edge 

Bare-earth surface 

Coastal marsh 

Coastal forest 

Canopy height 

Lukens Creek 

forest 

slope to relict 

remnant 

forest edge 

circa 1858 

sand dune 

forest soil erosion & 

lowering of ground surface 

forest 

remnant 

0 48 96 144 192 240 288 336 384 432 480 m 

0.9 

0.3 

0 

C C1

Gulf of Mexico east 

Figure 18. Transect C-C1 showing profile across upper reach of Lukens Creek to forest and relict dunes. 
meters (MSL NAVD88) 

VE = 40x 

8 

Bare-earth surface 

6 

4 

2 

0 88 176 264 352 440 528 616 704 792 m 

tidal-creek 

levee 

Waccasassa River Bird Creek

levee 

vegetation 

historic 

shoreline 

circa 1858 tidal-creek 

tributary & levee 

Coastal marsh 

Coastal forest 

Canopy height 

0.9 

0.3 0 

D D1

Gulf of Mexico north 

Figure 19. Transect D-D1 showing profile from Waccasassa River to a meander on Bird Creek. 
Presence and absence of levees along tidal creeks can help distinguish areas with higher sediment 

supply. The Waccasassa River is situated at the head of an embayment that can serve to focus storm surge 

and suspended sediments at the river mouth. Higher river and creek levees near the mouth of the river could 

be attributed to sediment pulses focused in the embayment. This process may be exaggerated by logging 

activities in Gulf Hammock that have altered sediment supply and forest cover over the last 150 years (Raabe 

et al., 2004). The position of the historic shoreline at Bird Creek (Fig. 19) coincides with a topographic low. 

The apparent expansion of tidal marsh seaward may be attributable to the same process. Limestone control of 

the relatively deeper incised channels at Bird Creek and Waccasassa River also contributes to differing 

morphology from that at Lukens Creek. 

Discussion 

Previously unavailable topographic detail for this coastal environment was modeled successfully by 

sequential processing for three functionally unique landscape elements, using non-automated processing 

steps. The preservation of topographic features, such as tidal drainage, was feasible by partitioning the 

landscape into sections. Parameters for each feature were selected based on scale of feature, vegetation cover, 

and frequency of laser penetration to ground surface. Familiarity with local topography and landscape 

elements was key to modeling the surface in this way. 

At Lukens Creek, the shorter canopy of the low marsh and the thin plant cover in burn areas 

provided consistent penetration of the laser and the extraction of ground intercepts with a 2-m LPF. 

However, the limited laser returns with this early instrument resulted in infrequent ground penetration in 

thick vegetation, particularly at Bird Creek and Waccasassa. A 10-m LPF was used to model the surface 

under thick forest canopy and marsh vegetation. Some micro-topographic features in the marsh are 

smoothed away with the use of a 10-m filter, but the final DSM adds considerable detail to existing digitalelevation models for the region. 

Assessment of a DSM from field-survey O.H. is complicated by elevation variability across the area 

represented by a planar grid cell and the point represented by a field-surveyed O.H. We are confident that 

with new laser-altimeter instrumentation, multiple returns per pulse, and full-waveform systems (Brock et 

al., 2004; Lefsky et al., 1999), bare-earth models and canopy characteristics can be developed for coastal 

wetland and forested areas with ALSM. 

The scale of features and processes may be deceptively small in a low-lying coastal system. Coastal 

wetlands are responsive to minor differences in the surface-drainage network, tidal flow, topography, and 

sediment supply. Currently available topography shows little or no geomorphic detail for this low-lying 

coastal zone and is too coarse to depict morphology where vertical difference between adjacent features is 

less than 0.5 m. 

Laser-altimetry data were used to derive surface elevations for three areas of the coastal marsh in 

Levy County, Florida, where a combination of sediment deposition and erosion, limestone control, and 

human activities have helped to shape the coast. Processing of the ALSM data resulted in ground-surface 

models, detailed delineation of tidal-drainage patterns, vegetation-canopy heights, and preliminary land-cover 

maps. Topographic profiles extracted from both the bare-earth and canopy-height DSMs, show details of the 

coastal landscape. The geomorphic characteristics are important to understanding the evolution, stability, and 

vulnerability of this coastal system. Management efforts, such as control burn and recovery monitoring, can 

be enhanced with subsequent data acquisition. The results demonstrate the use of airborne laser-altimetry 

data to model the ground surface beneath vegetated coastal marsh and forest. The results further demonstrate 

the capacity to derive additional vegetative and geomorphic characteristics from ALSM data. 

Acknowledgments 

Jeffery DiMaggio, manager at Cedar Key Scrub Preserve, provided invaluable field assistance and 

expert knowledge. Elzbieta Bialkowska-Jelinska provided editorial and mapping support. Michael Sartori, a 

graduate student with University of Florida Civil Engineering Department, provided technical support. 

32 
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34 
Appendix I 

Table 3. Orthometric heights (O.H.) of ground control points (GCP) and base stations. 

GCP# Eastings Northings 

O.H. (m) MSL 

NAVD88 

Re-occupy1 

O.H. (m) Description 

Plant height (m), if 

given 

Base 1 302055.826 3231090.068 0.531 0.531/0.498 rebar 

1 302031.132 3231096.593 0.452 sawgrass 1.1 

2 302022.295 3231103.066 0.448 Juncus 0.9 

3 302018.445 3231116.658 0.449 Distichlis 0.3 

4 302013.666 3231127.162 0.446 S. alterniflora 0.2 

5 302011.809 3231132.294 0.436 sawgrass 1.1 

6 302010.656 3231138.745 0.442 sawgrass 1.1 

7 302008.626 3231145.099 0.436 Juncus 1.2 

8 301999.216 3231146.593 0.441 Juncus 1.0 

9 301991.783 3231144.283 0.447 Juncus 1.1 

10 301986.098 3231141.831 0.444 Batis maritima 0.2 

11 301976.551 3231135.456 0.549 0.562 Borrichia/B. maritima 0.2 

12 301971.283 3231134.549 0.615 Batis maritima 0.1 

13 301969.698 3231132.914 0.654 J. coriaceae 0.5 

14 301968.322 3231126.508 0.746 Iva/Baccharus salt scrub 1.4 

15 301965.411 3231115.693 0.739 Iva/Baccharus salt scrub and Sabal 1.4 

16 301953.474 3231117.342 0.516 Batis maritima 0.2 

17 301950.712 3231154.419 0.459 Distichlis/B. maritima 0.3 

18 301956.363 3231171.726 0.462 S. alterniflora 0.2 

19 301952.754 3231187.975 0.433 Distichlis 0.4 

20 301941.592 3231211.894 0.435 Distichlis/B. maritima 0.3 

21 301937.022 3231228.825 0.443 Batis maritima/Distichlis 0.3 

22 301932.097 3231242.103 0.469 0.470 Dead Sabal/B. maritima/S. alterniflora 0.3 

23 301929.396 3231249.024 0.447 S. alterniflora 0.2 

24 301916.816 3231275.295 0.359 S. alterniflora flooded 0.2 

25 301909.965 3231289.716 0.344 S. alterniflora flooded 0.4 

26 301888.210 3231319.805 0.385 S. alterniflora flooded 0.3 

27 301877.378 3231334.627 0.399 S. alterniflora flooded 0.4 

28 301872.716 3231346.238 0.399 Distichlis 0.3 

29 301862.988 3231363.037 0.392 Juncus 1.5 

30 301847.966 3231377.488 0.346 S. alterniflora 0.3 

31 301822.329 3231396.891 0.419 Distichlis 0.3 

35 
32 301873.255 3231422.171 0.404 S. alterniflora/Juncus 1.1 

33 301878.926 3231418.193 0.894 

Dead Sabal trunk; root base 0.6 m above 

surrounding ground surface 6.0 

34 301905.180 3231411.972 0.466 Distichlis 0.3 

35 301939.941 3231447.511 0.551 Forest edge/transition with Distichlis 0.3 

36 301937.492 3231446.555 0.554 0.537 Forest edge/transition with dry Distichlis 0.3 

37 302073.243 3231099.418 0.285 Sawgrass edge 

38 302080.383 3231103.660 0.488 High marsh mix 

39 302085.899 3231106.574 0.549 Palmetto 

40 302086.827 3231107.441 0.819 50% Canopy mixed wood 

41 302098.045 3231113.550 0.846 Pine mixed forest 

42 302129.326 3231131.164 1.302 Thick oak and mix canopy 

43 302159.966 3231148.283 1.654 Thick scrub oak 

44 302061.522 3231093.215 0.457 Juncus marsh 

45 302068.842 3231097.356 0.482 Juncus marsh 

46 302076.347 3231101.123 0.478 Juncus marsh 

47 302084.951 3231105.621 0.532 Open palmetto and pine 

48 302092.682 3231111.146 0.842 Hydric hammock mixed 

49 302100.925 3231114.804 0.862 Pine/palmetto 

50 302108.784 3231118.941 0.997 Pine scrub 

51 302116.453 3231124.144 1.208 Palmetto oak scrub 

52 302124.847 3231128.864 1.193 Pine and oak scrub 

53 302133.589 3231133.741 1.375 Palmetto oak scrub 

54 302142.147 3231138.495 1.509 Oak scrub 

55 302149.817 3231142.728 1.580 Oak palmetto scrub 

56 302157.447 3231147.133 1.700 Thick scrub oak 

57 302162.512 3231149.897 1.701 Thick scrub oak 

Base 2 324093.641 3227528.102 0.861 0.861/0.861 

Juncus/S. alterniflora boundary - base station 

on Lone Cedar Island 

58 324310.805 3228342.773 0.736 0.736 levee: Juncus/Distichlis 

59 324312.117 3228329.977 0.593 levee: Juncus boundary 

60 324313.852 3228315.391 0.494 wrack barren 

61 323951.578 3229001.766 0.542 wrack barren 

62 323965.188 3229001.234 0.501 Juncus clump 

63 323970.203 3229003.328 0.612 Distichlis at tree edge 

64 323708.531 3229160.438 0.493 0.496 levee: Juncus edge 

65 323711.906 3229160.078 0.566 levee: Iva/sedge 

66 323714.234 3229163.352 0.493 levee edge: S. patens/Juncus 

66 323720.836 3229167.977 0.373 thick Juncus 

36 
67 323262.781 3229394.141 0.363 0.362 Juncus 

68 323257.805 3229394.195 0.341 wetter Juncus 

69 323253.625 3229394.648 0.322 wetter Juncus 

70 323105.828 3229964.828 0.252 Juncus 

71 323107.891 3229950.461 0.247 Juncus 

72 327205.930 3228549.805 0.322 0.325 wet Juncus 

73 327214.359 3228536.367 0.311 wet Juncus - last of drainage 

74 327229.508 3228503.094 0.447 short dry Juncus spp. 

75 327146.328 3228617.359 0.373 Sawgrass 

76 324176.688 3228436.555 0.581 0.582 levee edge - dry mud 

77 324180.648 3228443.438 0.792 levee hammock/mud boundary 

78 324189.445 3228450.383 0.761 levee hammock 

79 324196.430 3228471.992 0.549 back edge of levee hammock 

80 324200.617 3228475.984 0.574 high marsh salt scrub 

81 324210.672 3228482.125 0.536 Juncus 

82 324213.844 3228487.242 0.500 Juncus 

83 324094.654 3227542.190 0.629 

Distichlis/Juncus/Salicornia/Iva/dead palm on 

Cedar Island. 

84 323992.809 3227752.155 0.791 Sabal/cedar/Iva no seedlings 

85 323997.911 3227767.596 0.868 Hammock interior/Sabal seedlings/Cedar/wrack 

1

Repeat occupation of a ground control site or base station 

37