Using Lidar to Identify and Measure Forest Gaps on the William B. Bankhead National

Forest, Alabama

Jeffrey Stephens1, Dr. Luben Dimov1, Dr. Wubishet Tadesse1, and Dr. Callie Schweitzer2

1Alabama A&M University, Center for Forestry, Ecology, and Wildlife

2USDA Forest Service, Southern Research Station, Ecology and Management of Southern Appalachian Hardwoods,

Alabama A&M University

Importance of Forest Gaps

• Size and spatial properties of gaps influence forest regeneration and species composition of forests (Watt 1947)

• Forest regeneration is mainly confined to gaps and is dependent on gap size (Watt 1947)

Objectives

• Quantifying forest gap attributes– Size – Shape – Heterogeneity– Pattern

– Collected July and September, 2005

– Flown for selected William B. Bankhead stands

– Separated into two point clouds

– Bare Earth

– Vegetation

Lidar Data Collection

Study Area

Methods

• Interpolated Lidar data

– Bare Earth (ground)• Inverse Distance Weighted (IDW), Universal Kriging, and

Ordinary Kriging

– First Return (vegetation surface)• Ordinary Kriging

Digital Terrain Models (DTM)

IDW Universal Kriging

Mean: 0.004135Root-Mean-Square: 0.2458

Mean: 0.0008619Root-Mean-Square: 0.2647Average Standard Error: 0.2118Mean Standardized: 0.009038Root-Mean-Square Standardized: 1.248

Digital Terrain Models (DTM) - continued

Mean: 0.000017Root-Mean-Square: 0.1977Average Standard Error: 0.2011Mean Standardized: 0.0007143Root-Mean-Square Standardized: 0.9829

Predicated vs. Measured

Error vs. Measured

Standardized Error vs. Normal Value

Ordinary Kriging

Digital Surface Models

(Vegetation Heights)Canopy Height Model

Surface ModelTerrain Model_ =

Forest Gap Identification

• Gaps were defined as:

– Areas with a slope greater than 60 degrees

– Vegetation heights below 12 meters

• Note: Gaps were considered in this study as any area that met the above characteristics

Gap Locations

• Slope and vegetation height images were merged

• Vegetation height mode value,11.27m

Gap Measurements

Gap Size• Area and perimeter

Gap Shape• Gap Shape Complexity

Index (GSCI) (Blackburn and Milton 1996, Koukoulas and Blackburn 2004)

Gap Height Diversity (Shannon and Weaver 1962)

Gap Distribution• Dispersed or clustered

xArea

erGapPerimetGSCI

2

ii ppGHDn

i

ln1

Results

Area– Count:443– Minimum: 0.40– Maximum: 8359.26– Mean: 23.54– Standard Deviation: 396.91

Gaps covered 10.25% of the 25 acre study area

Gap Shape

• GSCI– Count:443– Minimum: 2– Maximum: 9.36– Mean: 2.34– Standard Deviation:

0.37

Height Variation within Gaps

Gap Height Diversity 1.57

– Count:15710– Minimum: 0.02– Maximum: 11.27– Mean: 4.9– Standard Deviation:

3.46

Gap Distribution within Study Area

• Gap locations were clustered– Observed Mean Distance/Expected Mean Distance = 0.76– Z Score = -9.54– Significance level 0.01

• The complexity of the gaps was randomly distributed within the study area– Moran’s I index = 0 – Z score = 0.24

• Vegetation height distribution within gaps is clustered– Moran’s I index = 0.09 – Z score = 554.97– Significance level 0.001

Conclusions• Lidar allows for gap identification and provides

forest gap characteristics that other imagery can not describe

• Important information for regeneration and ecological processes

• Future work could examine the vegetation type within gaps through multispectral or hyperspectral remote sensing techniques

References Blackburn, G. A., and Milton, E. J., 1996 Filing the gaps: remote sensing meets

woodland ecology. Global ecology and Biogeography, 5, 175-191.

Koukoulas, S., and Blackburn, G. A., 2004. Quantifying the spatial properties of forest canopy gaps using LiDAR imagery and GIS. International Journal of Remote Sensing, 25, 3049- 3071.

Shannon, C. E., and Weaver, W., 1962. The Mathematical Theory of Communication. Urbana: University of Illinois Press.

Watt, A.S., 1947. Pattern and process in the plant community. Journal of Ecology, 35, 1-22.

Acknowledgements

Support was provided by National Science Foundation, CREST-Center forEcosystems Assessment, Award No. 0420541; the Center for Forestry, Ecology,and Wildlife, Alabama A&M University; USDA Forest Service, Southern ResearchStation, Ecology and Management of Southern Appalachian Hardwoods ResearchWork Unit. We thank our partners the USDA Forest Service William B. Bankhead

National Forest and the Bankhead Liaison Panel.