| | | | |
VNIR
| | |
SWIR
| |
|---|
| | | |
2016
|
2017
|
2018
|
2016
|
2017
|
2018
|
|---|
|
Modeling
|
Original data
|
CA (%)
|
73 ± 2
|
70 ± 2
|
77 ± 2
|
73 ± 2
|
81 ± 2
|
80 ± 2
|
|
TPR (%)
|
71 ± 2
|
73 ± 2
|
72 ± 2
|
70 ± 10
|
82 ± 5
|
74 ± 10
|
|
FPR (%)
|
29 ± 2
|
32 ± 2
|
22 ± 2
|
34 ± 9
|
26 ± 4
|
20 ± 7
|
|
Annotated data
|
CA (%)
|
92 ± 1
|
90 ± 1
|
94 ± 1
|
88 ± 1
|
95 ± 1
|
92 ± 1
|
|
TPR (%)
|
89 ± 1
|
90 ± 1
|
93 ± 1
|
86 ± 4
|
90 ± 1
|
100 ± 1
|
|
FPR (%)
|
0 ± 1
|
11 ± 1
|
5 ± 1
|
2 ± 7
|
6 ± 1
|
5 ± 1
|
|
Application per plant
|
Original data
|
CA (%)
|
81
|
73
|
88
|
74
|
84
|
95
|
|
TPR (%)
|
79
|
76
|
86
|
63
|
80
|
86
|
|
FPR (%)
|
19
|
27
|
12
|
23
|
16
|
5
|
|
Annotated data
|
CA (%)
|
78
|
75
|
91
|
79
|
91
|
90
|
|
TPR (%)
|
58
|
71
|
71
|
60
|
60
|
71
|
|
FPR (%)
|
17
|
25
|
72
|
21
|
8
|
8
|
- For modeling, all pixels were evaluated not considering spatial scales. Developed models were then applied on plant scale using all leaves for majority voting
- CA classification accuracy, TPR true-positive rate, FPR false-positive rate
