Applying Spatial Data Mining, Logistic Filtering, Classification Error Analysis and Man-Machine Interactive Interpretation Methods in Formosat-II Image Interpretation

Spatial Information Research Center, CS, National Taiwan University

Prof. Tzu-How Chu

(Clusters)

(Spatial Data Mining) Roddick &Spilioporlou1999Shekhar& Chawla2003

GIS Machine learning

Rule 1

Rule 2 Rule 3

Rule 4

(Maximum Likelihood Classification)

Maximum Likelihood Classification

UAV

95

1/5000

NDVI

NDVI

1/5000

1/5000

1. 1

2.

2

3. 1

4. 5

5. 1

10

1200

4116 729 4845 84.95% 365 25861 26226 98.61% 4481 26590 31071

91.85% 97.26% 96.48%kappa 0.8620

()

93.9996.48

0.80.5()

UAV 2

UAV 2

+

281/5000

3-4

5-48

(210)(112)

93.64%

103 47 150 31.33% 68.67%

7 0 7 100.00% 65.61%

110 47 157 157 6.36%

93.64% 0.00% 65.61% 31.33%

IM

1.

2.

3.

92.16%

47 1 48 2.08% 97.92%

4 0 4 100.00% 90.38%

51 1 52 52 7.84%

92.16% 0.00% 90.38% 2.08%

IM

()

()

()

16 2.00 -

2 0.25 -

NDVI 2 0.25 -

NDVI 2 0.25 -

2 0.25 -

10 1.25 -

4 0.50 -

16 2.00 -

/ 18 2.25 -

72() 9() 782()

98% -

(24,7254,985)8

()

()

()

16 2.00 -

2 0.25 -

NDVI 2 0.25 -

NDVI 2 0.25 -

2 0.25 -

10 1.25 -

4 0.50 -

16 2.00 -

/ 50 6.00 -

104() 12.75() 782()

98% -

(24,7254,985)8

NDVI

- (dNDVI)

2009118NDVI

20081220NDVI

[]

IF

&& &&

&&

?

?

?

(4)

?

?

?

(2)

(1)

(3)

N Y

Y

Y

YY

Y

N

N N

NNN Y

1.2.3.4.

306668385.553659029.78

UAV

UAV

1/250001/5000

36

1

SPOT

1-44-77-10

()()

UAV

100102103102

791558

()

0

100

200

300

400

500

600

700

APP

103

102

100%

101~102

994

Thank you