Improved Understanding of Landuse Change using Geospatial Technologies and Geovisualization:

Case Studies of Historical Agricultural Landuse and Tornado Damage in a Forest Preserve

Marguerite MaddenProfessor and Director

Center for Geospatial Research (CGR) Department of Geography, University of Georgia

Athens, Georgia USA www.crms.uga.edu

INTEREXPO GEO-SIBERIA-2014 - April 16-18, 2014

“As a plot of ground that has for almost three hundred years been devoted to agricultural pursuits or the

interpretation of historic agriculture, Wormsloe is an inviting case study to deal with regional themes of land use, the preservation of historic and natural landscapes, and the place of agriculture and people within the environment.”

“Wormsloe is a typical southern space, a place where cotton and cornfields were as prevalent as woods and

marshes and farm work was the most common way that people interacted with the environment.”

Drew Swanson, Remaking Wormsloe Plantation: The Environmental History of a Lowcountry Landscape (2013)The University of Georgia Press

Stresses the centrality of agroecosystems, especially in southern landscapes.

Tommy Jordan CGR Associate Director

Objectives:

1) Brief introduction to the Wormsloe Historic Site and interdisciplinary research by the Wormsloe Institute for Environmental History (WIEH)-UGA .

2) Use of LiDAR data and spatio-temporal data sets to assess current landscapes related to historical landuse legacy of disturbance/transition.

3) Demonstrate 3D reconstruction of historic buildings, landscapes and artifacts with cloud-based Surface from Motion photogrammetry and geovisualization

Wormsloe State Historic Site

Charleston, SC

Savannah, GA

WormsloeHistoric Site

Wormsloe

Colonial Settlement

Slave Cabins

Main House

Rice Mill

Former Cotton Fields

Pine Bark Beetle Damage

1920s Dairy

Shell Middens

Whiskey Stills

Wormsloe Historic Site, Isle of Hope, Georgia

“…the story of one family’s continuous land stewardship that has lasted almost three centuries to date.” (Swanson, 2012)

Shell Midden – Native American inhabitants 4000 BC

Tabby ruins of the fortified house - Noble and Sarah Jones, with children Mary and Noble Wimberly among the 22 “Trustees” who left England in 1732 to colonize Georgia

Wormsloe Plantation House 1828

Silo from 1920s dairy barn

Formal gardens at Wormsloe opened for tourists 1930s

1840s cabin

• 1800– Isle of Hope map

• 1828– Plan for original

Wormsloe house• 1870

– Hand drawn map of roads, fields and buildings

• 1871– Plan for proposed

causeway to Skidaway Island

• 1890– Hand drawn map of

roads, fields and buildings

– Stereo photo cards• 1897

– Hand drawn and colored map of roads, fields, fence lines, drainage ditches and buildings

– Trees and plantings with species labeled

• 1908– Crude map of fields and

land cover

Historical Data

How does1897landuselegacy shape vegetation pattern and process today?

Clearing

Evergreen

Mixed Forest

Residential

33 PermanentVegetation

Plots

represent current vegetation communities

located within the 1897landuse legacies

http://www.wormsloeinstitute.org/

North East

South West

Canopy

Placing a Historical Plantation in an Ecological Context, Geography M.S. Thesis by Carey Burda (2011) determined effects of historical land uses on vegetation structure.

Vegetation Plots

Vegetation Plot

Landscape perspective

LiDAR return types:Type 1: singular returnType 2: first of many returnsType 3: intermediate returnsType 4: last of many returns

Objective 1: Derive canopy stratification & LiDAR metrics according to Miura & Jones (2010)

Used QCoherent LP360 extension to ArcGIS tostratify the canopy

Strata #

ClassLayers

Elevation Range (m)

0 Ground ≤01 Litter >0.001 and ≤0.52 Low Veg1 >0.5 and ≤ 1.53 Low Veg 2 >1.5 and ≤ 54 Medium 1 >5 and ≤ 105 Medium 2 >10 and ≤206 High 1 >20 and ≤ 307 High 2 >30

Description LiDAR

Type

Miura & Jones

(2010)

correlated field

variables

Formula (adapted from Miura & Jones, 2010)

OG Opening above the ground

Ground Type 1

Total volume coarse woody debris

OL Opening above low vegetation

LowVeg Types 1 & 2

Field mean canopy cover

VL Presence of understory vegetation

Low Veg Types 1,2,3, & 4

LAI for vegetation < 1 meter

CC Canopy coverMedium Veg Types 1 & 2 and High Veg Types 1 & 2

Field derived canopy cover

OM Opening above medium vegetation

Medium Veg Types 1 & 2

Opening above

medium

vegetation

1810 Hand drawn map, De Renne Family Collection Hargrett1897 Hand drawn map, Hargrett Rare Book & Manuscript Library1908 Hand drawn map, Hargrett Rare Book & Manuscript Library1912 Topographic map, Army Corps of Engineers/USGS1933 Hand drawn map, US Coast & Geodetic Survey/Air Photos1937 Hand drawn Map, US Dept. of Agriculture1945 Topographic Map, USGS1957 Topographic Map, USGS1971 Aerial Photograph, B&W, Skidaway Inst. for Oeanography1976 Aerial Photograph, B&W, UGA Map Library1988 Aerial Photograph, B&W, USGS-NHAP1999 Aerial Photograph, CIR, USGS-NAPP2009 Aerial Photograph, Color, NAIP-USDA

Identified Vegetation at each Longterm Vegetation Plot over 200-year period:

Disturbance & Transition: Antebellum (1810-1860)

Postbellum (1870-1910)Pine Beetle Infestation (1970-present)

Plot No. 1870 1880 1890 1900 1910

Disturbance Score

Disturbance Class

1Evergreen forest Mixed forest Mixed forest Mixed forest Mixed forest 6 low

2Evergreen forest

Evergreen forest

Evergreen forest

Evergreen forest Evergreen forest 10 medium

3 Field Field Field Field Evergreen forest 14 high

4 Field Field Field Field Field 15 high

5 Field Field Field Field Field 15 high

6 Mixed forest Mixed forest Mixed forest Mixed forest Mixed forest 5 low

7 Mixed forest Mixed forest Mixed forest Mixed forest Mixed forest 5 low

Disturbance Score

1. Disturbance level= based on impact land cover would have on current vegetation structure, plots were classified as having low, moderate, high levels of disturbance.

Plot No. Antebellum Postbellum Pine Beetle Transition Score Transition Class1 high low low 1 moderate2 high medium low 2 high3 medium high low 2 high4 medium high low 2 high5 high high medium 1 moderate6 low low low 0 low7 low low low 0 low

Transition Score

2. Transition score = # times shift in disturbance level within the 3 time periods.

DCA OrdinationLiDAR metrics input to Detrended Correspondence Analysis (DCA) Ordination – clustered plots are similar

Veg Plot 21

Den

se

to

Sp

arse

Mid

-Sto

rey

Low Canopy Ht/More Open to High Canopy Ht/Less Open Mid-Storey

Axis 1: P < 0.05

Axis 1: P < 0.05 (Significant Groups!)

Wormsloe: 1909 DeRenne Library

Dr. CJ Jackson, GSU and UGA-SKIO, collected TLS data of existing cabin and building site with Riegl VZ-1000:@ 70 kHz, 29,000 pts/sec, to 1400m@ 300 kHz, 122,000 pts/sec, to 450m

One sigma at 100m, 8 mm accuracy, 5 mm precision

UGA Architects plan new cabins

Stores 32 Gb data, wireless data transfer

X, Y, Z Point Cloud and Return Intensity

Rapid, inexpensive and easy 3D surveys of buildings or small objects Image-based method requires little training and is inexpensive. Online SfM programs available (e.g., 123D Catch) Create high-resolution digital elevation models from ordinary

ground/aerial photographs with free and open source software. Process reconstructs objects/landscapes from SfM algorithms based

on the derived positions of the photographs in 3D space.

Surface from Motion or Structure from Motion (SfM)

Fonstad, et al. (2013) Topographic structure from motion: a new development in photogrammetric measurement, Earth Surfaces Processes and Landforms, 38 (4): 421-430.

Surface from Motion using multiple ground photos taken at different angles uploaded to Autodesk 123D Catch

http://www.123dapp.com/catch

Creates 3D point cloud and 3D image model downloaded for free (pay for 3D print), Video

• Historical sites such as Wormsloe offer unique opportunities to explore impacts of historical landuses on current landscapes.

• Future conservation and resource management will increasingly draw upon rich, multiscale geospatial data sets for landscape-scale assessments (with variable accuracies, temporal intervals).

• Integrated 3D geospatial data and geovisualization techniques can be used effectively to reconstruct historic landscapes shaping current conditions and investigate change.

Conclusions

Thank Wormsloe Institute for Environmental History, the Wormsloe Foundation, UGA Graduate School and UGA

College of Environmental Design for their support of Wormsloe researchers and students.

Craig and Diana Barrow, Sarah Ross, WIEH President Carey Burda, Andrew Parker, Nancy O’Hare, Carrie Jensen

Wormsloe Institute for Environmental History (WIEH), www.wieh.org