post accuracy assessment classification
DESCRIPTION
Presented in AAG 2009, Las VegasTRANSCRIPT
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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
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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
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Aerial Photos•4 Bands•Orthorectified•0.45 m Resolution
holmes, Graduate School of Geography, Clark University
Study Area
2
Image Courtesy: Google Earth
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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
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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
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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
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Visiting Sample Points
Coniferous Fine-Green Fine-Green
Impervious Impervious Deciduous
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Images Courtesy: Google Earth
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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
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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
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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.
23
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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. : [email protected]
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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.