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Slide1

Remote Sensing of Natural Resources and Environment | FR 5262 | University of Minnesota

Philip J Potyondy

A Comparative Analysis of Urban Tree Canopy Assessment Methods in MinnesotaSlide2

Digitize urban forest canopy cover using image classification remote sensing techniques and software over study areas.Slide3
Slide4
Slide5
Slide6

Digitize urban forest canopy cover using image classification remote sensing techniques and software over study areas.

24.71%Slide7

Digitize urban forest canopy cover via technician photo interpretation over study area.Slide8
Slide9
Slide10
Slide11
Slide12
Slide13

Digitize urban forest canopy cover via technician photo interpretation over study area.

18.03%Slide14

Digitize urban forest canopy cover via technician photo interpretation within stratified random sampled blocks.Slide15
Slide16
Slide17

Definition of variables: 

Village X (vX); Area of Village X = A vX

  Zone Q (

zQ

); Area of

zQ

= A

zQ

      Study Block 1 (sb1); Area of sb1 = A sb1

      Study Block 2 (sb2); Area of sb2 = A sb2

      Study Block 3 (sb3); Area of sb3 = A sb3

  Zone R (

zR

); Area of

zR

= A

zR

      Study Block 4 (sb4); Area of sb4 = A sb4

      Study Block 5 (sb5); Area of sb5 = A sb5

  Zone S (

zS

); Area of

zS

= A

zS

      Study Block 6 (sb6); Area of sb6 = A sb6

      Study Block 7 (sb7); Area of sb7 = A sb7

Equations:

Geographic Weight of Study Block 1 = (A sb1 /A

zQ

)

Percent Canopy of Study Block 1 = C sb1

Estimated Percent Canopy of Zone Q = C

zQ

= [(A sb1 / A

zQ

) * C sb1]  +  [(A sb2 / A

zQ

) * C sb2]  +  [(A sb3 / A

zQ

) * C sb3]

Estimated Percent Canopy of Zone R = C

zR

= [(A sb4 / A

zR

) * C sb4]  +  [(A sb5 / A

zR

) * C sb5]

Estimated Percent Canopy of Zone S = C

zS

= [(A sb6 / A

zS

) * C sb6]  +  [(A sb7 / A

zS

) * C sb7]

Estimated Percent Canopy of Village X = C

vX

= [(A

zQ

/ A

vX

) * C

zQ

]  +  [(A

zR

/ A

vX

) * C

zR

]  +  [(A

zS

/ A

vX

) * C

zS

]Slide18
Slide19

Digitize urban forest canopy cover via technician photo interpretation within stratified random sampled blocks.

17.28%Slide20

Calculate urban forest canopy using field

collected tree canopy width measurements within stratified random sampled blocks.Slide21
Slide22

Calculate urban forest canopy using field

collected tree canopy width measurements within stratified random sampled blocks.16.32%Slide23

Calculate urban forest canopy using randomly

generated points within study area interpreted by a technician - iTree CanopySlide24
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Slide28

Calculate urban forest canopy using randomly

generated points within study area interpreted by a technician - iTree Canopy

18.2%

±

3.88Slide29
Slide30

Exiting data

Tree SpeciesSlide31

By: tatyana-admore
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Type: Public

Remote Sensing of Natural Resources and Environment | FR - Description


Philip J Potyondy A Comparative Analysis of Urban Tree Canopy Assessment Methods in Minnesota Digitize urban forest canopy cover using image classification remote sensing techniques and software over study areas ID: 530162 Download Presentation

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