Post on 16-Jan-2015
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Post Accuracy Assessment Soft Classification Using Virtual Globes
1. To use the high quality sampled information that accuracy assessment reveals for creating a soft classified residential lawns map.
2. To incorporate supplemental variables for aiding the segregation of residential lawns from fine- green (grassy) areas.
3. To use virtual fieldwork for validation.
Objectives
Rahul RakshitPhD CandidateClark University
Robert Gilmore Pontius Jr.Asst. ProfessorClark University
holmes, Graduate School of Geography, Clark University 1
holmes, Graduate School of Geography, Clark University 2
Supplemental VariablesVirtual
Fieldwork for Accuracy
Assessment
Soft Classified Map
Our Contribution
Satellite Image/Aerial Photo
Hard Classified Map
Accuracy Assessment
Traditional image processing methodology
Image Classification
1. To use the high quality sampled information that accuracy assessment reveals for creating a soft classified residential lawns map.
2. To incorporate supplemental variables for aiding the segregation of residential lawns from fine- green (grassy) areas.
3. To use virtual fieldwork for validation.
Objectives
Aerial Photos•4 Bands•Orthorectified•0.45 m Resolution
holmes, Graduate School of Geography, Clark University
Study Area
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Image Courtesy: Google Earth
Land-Cover Map: Created by object oriented classification
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Residential Lawns
Residential Lawns are: grassy areas associated with a private residence
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All Fine-Greens are not Residential Lawns
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Image Courtesy: Google Earth
Fine-Green Boolean - 15% of the area
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Using Supplemental Variables
Supplemental variables are selected based on the likelihood of them containing residential lawns.
1. Building Footprints
2. Residential Zoning
3. Historic Residential Land-use
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Building Footprints
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Near Buildings Boolean
Hero Map, Graduate School of Geography, Clark University 9
Residential Zoning Boolean
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Residential Land-use 1999 Boolean
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Stratum Fine-Green
Near Buildings Res-Zoned Res -1999 Percentage of
Study Area
1 TRUE TRUE TRUE TRUE 5
2 TRUE TRUE TRUE FALSE 6
3 TRUE TRUE FALSE UN-USED 1
4 TRUE FALSE UN-USED UN -USED 6
5 FALSE TRUE TRUE TRUE 12
6 FALSE UN-USED UN-USED UN-USED 70
Total 100
Stratification
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Mutually Exclusive and Collectively Exhaustive Strata
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Sampling Tool: Stratified Random Sampling
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Sampling
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Why use Virtual Globes for Virtual Fieldwork
Better Science : We can do stratified truly random sampling that is temporally matching.
Saves time and money.
Imagery available at very high resolution aiding in easy identification of land-cover classes.
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Plotting samples on Google Earth
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Image Courtesy: Google Earth
Visiting Sample Points
Coniferous Fine-Green Fine-Green
Impervious Impervious Deciduous
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Images Courtesy: Google Earth
Google Earth
Street View
Virtual Earth 1 Virtual Earth 2 Virtual Earth 3 Virtual Earth 4
Multiple Views on Virtual Globes
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Images Courtesy: Google Earth and MS Virtual Earth
Stratum Fine-Green Near Buildings Zoned Res Res -1999 Percentage of Study Area
Upper Bound
Percentage of Lawn
Lower Bound
1 TRUE TRUE TRUE TRUE 5 64% 76 88%
2 TRUE TRUE TRUE FALSE 6 24% 38 52%
3 TRUE TRUE FALSE UN -USED 1 1% 6 13%
4 TRUE FALSE UN -USED UN -USED 6 0% 0 0%
5 FALSE TRUE TRUE TRUE 12 1% 10 19%
6 FALSE UNUSED UN -USED UN -USED 70 1% 2 6%
Total 100 5% 8 12%
Number of Samples per Strata = 50
Percentage of Fine-Green = 15%Percentage of Residential Lawns = 8%
Sampling Results
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Residential Lawn - 8% of the area
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Stratum 1
Stratum 1U2
Stratum 1U2U3
Stratum 1U2U3U4
0 2 4 6 8 10 12 14 16 18 20
Error of omission Correctly classified Error of comission
29
41
44
37
Percent of Study Area
Har
d D
efini
tion
of L
awn
Figure of Merit
Observations
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Figure of Merit: The rate at which the classification is entirely correct
Objectives
holmes, Graduate School of Geography, Clark University
1. To use the high quality sampled information that accuracy assessment reveals for creating a soft classified residential lawns map.
2. To incorporate supplemental variables for aiding the segregation of residential lawns from fine- green (grassy) areas.
3. To use virtual fieldwork for validation.
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AcknowledgementsI sincerely thank:
Prof. Robert Gilmore Pontius Jr., Clark University
Prof. Colin Polsky, Clark University
holmes team: Albert Decatur, Jenner Alpern and Nick Giner
MassGIS
Town of Ipswich
Google Earth
MS Virtual Earth
Rahul’s contact Info. : rahulbabaji@gmail.com
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This material is based upon work supported by the National Science Foundation under Grant No. 0709685Any opinions, findings, & conclusions or recommendations expressed in this material are those of the author(s) & do not necessarily reflect the views of the National Science Foundation.