Your SlideShare is downloading. ×
0
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Post Accuracy Assessment Classification
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Post Accuracy Assessment Classification

939

Published on

Presented in AAG 2009, Las Vegas

Presented in AAG 2009, Las Vegas

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
939
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Rahul Rakshit Robert Gilmore Pontius Jr. PhD Candidate Asst. Professor Clark University Clark University Objectives1. 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. holmes, Graduate School of Geography, Clark University 1
  • 2. Traditional image Satellite Image/ Objectivesprocessing Aerial Photomethodology Image Classification 1. To use the high quality sampled information Accuracy that accuracy assessment reveals for creating Assessment a soft classified residential lawns map. Hard Classified MapOur Contribution Supplemental 2. To incorporate supplemental Virtual Variables variables for aiding the segregation of residential 3. To use virtual Fieldwork for lawns from fine- green fieldwork for validation. Accuracy (grassy) areas. Assessment Soft Classified Map holmes, Graduate School of Geography, Clark University 2
  • 3. Aerial Photos •4 Bands •Orthorectified •0.45 m Resolution Image Courtesy: Google Earthholmes, Graduate School of Geography, Clark University 2
  • 4. holmes, Graduate School of Geography, Clark University 3
  • 5. holmes, Graduate School of Geography, Clark University 4
  • 6. Image Courtesy: Google Earthholmes, Graduate School of Geography, Clark University 5
  • 7. holmes, Graduate School of Geography, Clark University 6
  • 8. Supplemental variables are selected based on the likelihood ofthem containing residential lawns. holmes, Graduate School of Geography, Clark University 7
  • 9. holmes, Graduate School of Geography, Clark University 8
  • 10. Hero Map, Graduate School of Geography, Clark University 9
  • 11. holmes, Graduate School of Geography, Clark University 10
  • 12. holmes, Graduate School of Geography, Clark University 11
  • 13. holmes, Graduate School of Geography, Clark University 12
  • 14. holmes, Graduate School of Geography, Clark University 13
  • 15. holmes, Graduate School of Geography, Clark University 14
  • 16. holmes, Graduate School of Geography, Clark University 15
  • 17. holmes, Graduate School of Geography, Clark University 16
  • 18. Image Courtesy:Google Earth holmes, Graduate School of Geography, Clark University 17
  • 19. Coniferous Fine-Green Fine-GreenImpervious Impervious Deciduous Images Courtesy: Google Earth holmes, Graduate School of Geography, Clark University 18
  • 20. Images Courtesy: Google Earth and MS Virtual Earth Street ViewGoogle EarthVirtual Earth 1 Virtual Earth 2 Virtual Earth 3 Virtual Earth 4 holmes, Graduate School of Geography, Clark University 19
  • 21. Percentage of Upper Percentage LowerStratum Fine-Green Near Buildings Zoned Res Res -1999 Study Area Bound of Lawn 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% holmes, Graduate School of Geography, Clark University 20
  • 22. holmes, Graduate School of Geography, Clark University 21
  • 23. Figure of Merit: The rate at which the classification is entirely correct Error of omission Correctly classified Error of comission Figure of MeritStratum 1U2U3U4 29 Stratum 1U2U3 41 Stratum 1U2 44 Stratum 1 37 0 5 10 15 20 holmes, Graduate School of Geography, Clark University 22
  • 24. 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. holmes, Graduate School of Geography, Clark University 23
  • 25. 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 theviews of the National Science Foundation. holmes, Graduate School of Geography, Clark University 24

×