Improved Understanding of Landuse Change using
Geospatial Technologies and Geovisualization:
Case Studies of Historical Ag...
“As a plot of ground that has for almost three hundred
years been devoted to agricultural pursuits or the
interpretation o...
Tommy Jordan
CGR Associate Director
Objectives:
1) Brief introduction to the Wormsloe Historic Site
and interdisciplinary research by the Wormsloe
Institute f...
Wormsloe State
Historic Site
Charleston, SC
Savannah, GA
Wormsloe
Historic Site
Wormsloe
Colonial Settlement
Slave Cabins
Main House
Rice Mill
Former Cotton Fields
Pine Bark Beetle Damage
1920s Dairy
Sh...
Wormsloe Historic Site, Isle of Hope, Georgia
“…the story of one family’s continuous land stewardship that has
lasted almo...
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” ...
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...
How does
1897
landuse
legacy
shape
vegetation
pattern
and
process
today?
Clearing
Evergreen
Mixed
Forest
Residential
33 Permanent
Vegetation
Plots
represent
current
vegetation
communities
located within
the 1897
landuse legacies
http://www...
North East
South West
Canopy
Placing a Historical Plantation in
an Ecological Context,
Geography M.S. Thesis by Carey
Burda (2011) determined effects
o...
Vegetation Plots
Vegetation
Plot
Landscape
perspective
LiDAR return types:
Type 1: singular return
Type 2: first of many returns
Type 3: intermediate returns
Type 4: last of man...
Used QCoherent LP360
extension to ArcGIS to
stratify the canopy
Strata
#
Class
Layers
Elevation
Range (m)
0 Ground ≤0
1 Li...
Description LiDAR
Type
Miura & Jones
(2010)
correlated field
variables
Formula
(adapted from Miura & Jones, 2010)
OG Openi...
1810 Hand drawn map, De Renne Family Collection Hargrett
1897 Hand drawn map, Hargrett Rare Book & Manuscript Library
1908...
Disturbance & Transition:
Antebellum (1810-1860)
Postbellum (1870-
1910)
Pine Beetle Infestation (1970-present)
Plot
No. 1870 1880 1890 1900 1910
Disturbance
Score
Disturbance
Class
1
Evergreen
forest Mixed forest Mixed forest Mixed f...
Plot No. Antebellum Postbellum Pine Beetle Transition Score Transition Class
1 high low low 1 moderate
2 high medium low 2...
DCA Ordination
LiDAR metrics input to Detrended
Correspondence Analysis (DCA)
Ordination – clustered plots are similar
Veg...
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,...
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 in...
Surface from Motion using multiple ground photos taken
at different angles uploaded to Autodesk 123D Catch
http://www.123d...
• Historical sites such as Wormsloe offer unique
opportunities to explore impacts of historical
landuses on current landsc...
Thank Wormsloe Institute for Environmental History, the
Wormsloe Foundation, UGA Graduate School and UGA
College of Enviro...
Marguerite Madden Improved Understanding of Landuse Change using Geospatial Technologies and Geovisualization
Marguerite Madden Improved Understanding of Landuse Change using Geospatial Technologies and Geovisualization
Marguerite Madden Improved Understanding of Landuse Change using Geospatial Technologies and Geovisualization
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Marguerite Madden Improved Understanding of Landuse Change using Geospatial Technologies and Geovisualization

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  • Objective 1
    -the land use legacies chosen to represent the plots included past human habitation, forest clearings, crop cultivation, and pest outbreaks.
    -before measuring the structure established the land use/land cover for each plot in 10-year intervals over a 200 year time line by examining historical maps, aerial photographs, and using written documents and assigning the land cover.
  • -Images will help communicate research activities being conducted on the Wormsloe to visitors so that they may better appreciate a state historic site.
  • -Next, the lidar data.
    -20 x 20m areas of point cloud lidar data representing each of the 33 study plots were extracted from larger data sets.
    -the forest characterization scheme used was based on another project by Miura and Jones, 2010. I classified the canopy in each plot by lidar elevation values into 8 strata in order to accommodate for growth forms of individual plants (Jennings, et al., 2009) and visual observations in point cloud of canopy characteristics in the plots
    -next, lidar returns from each stratum were sorted into types: Type 1, Type 2, etc…
  • -Next, the lidar data.
    -20 x 20m areas of point cloud lidar data representing each of the 33 study plots were extracted from larger data sets.
    -the forest characterization scheme used was based on another project by Miura and Jones, 2010. I classified the canopy in each plot by lidar elevation values into 8 strata in order to accommodate for growth forms of individual plants (Jennings, et al., 2009) and visual observations in point cloud of canopy characteristics in the plots
    -next, lidar returns from each stratum were sorted into types: Type 1, Type 2, etc…
  • -What can we do with these return types now that they’re sorted within each stratum?
    -Miura &amp; Jones put these types into ratios, and compared them with field collected data, and found there were correlations between the two data sets.
    -for example, in this first metric we are characterizing opening above the ground, which is correlated with total volume coarse wood debris. The accompanying ratio incorporates the stratum with the lidar type return, and divides it by total number of returns.
    -so, essentially, these return type ratios are characterizing densities, gaps, and openness throughout the canopy per stratum
  • -Next, classified each plot within each time period as having low, moderate, or high levels of disturbance based on their land covers.
    -did this by weighting each land cover based on how much impact they would presumably have on today’s vegetation structure. Field received the highest score, 3, evergreen forest 2, and mixed forest, 1.
    -assigned points to each land cover, totaled the points, and classified the plot based on the scores.
  • -Next, classified the plots based on their cumulative disturbance levels over all three time periods.
    -did this by assigning a score based on how many times a plot transitioned into a different disturbance level.
    -For example, Plot 1 received a score of 1. It transitioned once over the three time periods.
    -Plot 2 transitioned twice-it received a score of 2.
    -Pot 7 did not transition-its disturbance level remained low over the entire three periods. It received a 0.
    -Finally, classified the plots into low, moderate, or high transition levels based on their scores.
  • -How do we analyze the data sets for relationships between land use legacy and forest structure?
    -the lidar metrics were put into Detrended Correspondence Analysis ordination. --Ordinations are multivariate analyses that are commonly used in ecological studies where many variables are examined at once for relationships. What we get is a multidimensional visual with axes that represent some sort of gradient in the data. In this case we’re looking at strictly structural gradients. The closer the plots are the more likely there is a relationship between those plots.
    -What I found was that the lidar metrics, VH and OM are strongly correlated with Axis 1 (canopy depth in high vegetation, field derived opening above medium vegetation)
    -VM is strongly correlated with Axis 2 (canopy depth in medium vegetation)
  • -Finally, with the transition overlay the groups are significantly different along Axis 1.
    -with the transitional overlay, I was able to say that varying transitional levels indeed influenced current forest structure in the plots.
  • Marguerite Madden Improved Understanding of Landuse Change using Geospatial Technologies and Geovisualization

    1. 1. Improved Understanding of Landuse Change using Geospatial Technologies and Geovisualization: Case Studies of Historical Agricultural Landuse and Tornado Damage in a Forest Preserve Marguerite Madden Professor 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
    2. 2. “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.
    3. 3. Tommy Jordan CGR Associate Director
    4. 4. 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
    5. 5. Wormsloe State Historic Site Charleston, SC Savannah, GA Wormsloe Historic Site
    6. 6. Wormsloe Colonial Settlement Slave Cabins Main House Rice Mill Former Cotton Fields Pine Bark Beetle Damage 1920s Dairy Shell Middens Whiskey Stills
    7. 7. 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)
    8. 8. Shell Midden – Native American inhabitants 4000 BC
    9. 9. 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
    10. 10. Wormsloe Plantation House 1828
    11. 11. Silo from 1920s dairy barn
    12. 12. Formal gardens at Wormsloe opened for tourists 1930s
    13. 13. 1840s cabin
    14. 14. • 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
    15. 15. How does 1897 landuse legacy shape vegetation pattern and process today? Clearing Evergreen Mixed Forest Residential
    16. 16. 33 Permanent Vegetation Plots represent current vegetation communities located within the 1897 landuse legacies http://www.wormsloeinstitute.org/
    17. 17. North East South West Canopy
    18. 18. 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.
    19. 19. Vegetation Plots Vegetation Plot Landscape perspective
    20. 20. LiDAR return types: Type 1: singular return Type 2: first of many returns Type 3: intermediate returns Type 4: last of many returns Objective 1: Derive canopy stratification & LiDAR metrics according to Miura & Jones (2010)
    21. 21. Used QCoherent LP360 extension to ArcGIS to stratify the canopy Strata # Class Layers Elevation Range (m) 0 Ground ≤0 1 Litter >0.001 and ≤0.5 2 Low Veg1 >0.5 and ≤ 1.5 3 Low Veg 2 >1.5 and ≤ 5 4 Medium 1 >5 and ≤ 10 5 Medium 2 >10 and ≤20 6 High 1 >20 and ≤ 30 7 High 2 >30
    22. 22. 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 cover Medium 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
    23. 23. 1810 Hand drawn map, De Renne Family Collection Hargrett 1897 Hand drawn map, Hargrett Rare Book & Manuscript Library 1908 Hand drawn map, Hargrett Rare Book & Manuscript Library 1912 Topographic map, Army Corps of Engineers/USGS 1933 Hand drawn map, US Coast & Geodetic Survey/Air Photos 1937 Hand drawn Map, US Dept. of Agriculture 1945 Topographic Map, USGS 1957 Topographic Map, USGS 1971 Aerial Photograph, B&W, Skidaway Inst. for Oeanography 1976 Aerial Photograph, B&W, UGA Map Library 1988 Aerial Photograph, B&W, USGS-NHAP 1999 Aerial Photograph, CIR, USGS-NAPP 2009 Aerial Photograph, Color, NAIP-USDA Identified Vegetation at each Longterm Vegetation Plot over 200-year period:
    24. 24. Disturbance & Transition: Antebellum (1810-1860) Postbellum (1870- 1910) Pine Beetle Infestation (1970-present)
    25. 25. Plot No. 1870 1880 1890 1900 1910 Disturbance Score Disturbance Class 1 Evergreen forest Mixed forest Mixed forest Mixed forest Mixed forest 6 low 2 Evergreen 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.
    26. 26. Plot No. Antebellum Postbellum Pine Beetle Transition Score Transition Class 1 high low low 1 moderate 2 high medium low 2 high 3 medium high low 2 high 4 medium high low 2 high 5 high high medium 1 moderate 6 low low low 0 low 7 low low low 0 low Transition Score 2. Transition score = # times shift in disturbance level within the 3 time periods.
    27. 27. DCA Ordination LiDAR metrics input to Detrended Correspondence Analysis (DCA) Ordination – clustered plots are similar Veg Plot 21 DensetoSparseMid-Storey Low Canopy Ht/More Open to High Canopy Ht/Less Open Mid-Storey
    28. 28. Axis 1: P < 0.05 Axis 1: P < 0.05 (Significant Groups!)
    29. 29. Wormsloe: 1909 DeRenne Library
    30. 30. 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
    31. 31. X, Y, Z Point Cloud and Return Intensity
    32. 32. 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.
    33. 33. 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
    34. 34. • 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
    35. 35. 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
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