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
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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.Slide3Slide4Slide5Slide6
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.Slide8Slide9Slide10Slide11Slide12Slide13
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.Slide15Slide16Slide17
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
]Slide18Slide19
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.Slide21Slide22
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 CanopySlide24Slide25Slide26Slide27Slide28
Calculate urban forest canopy using randomly
generated points within study area interpreted by a technician - iTree Canopy
18.2%
±
3.88Slide29Slide30
Exiting data
Tree SpeciesSlide31