Table S1: Parameters of all 172 tests
Contents
Table S1: Parameters of all 172 tests¶
These tests consist of four satellite image pairs, each with 43 distinct parameter combinations. The machine-readable CSV file is available at notebooks/manifest.csv
.
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import pandas as pd
pd.set_option('display.max_rows', None)
df = pd.read_csv('../manifest.csv', dtype=str)
df = df.drop(columns=['Vx', 'Vy']) # Vx and Vy are file paths
df
Date | Duration (days) | Template size (px) | Template size (m) | Pixel spacing (px) | Pixel spacing (m) | Prefilter | Subpixel | Software | |
---|---|---|---|---|---|---|---|---|---|
0 | Sen2-20180304-20180314 | 10 | 48 | 480 | 12 | 120 | Gau | 16-node oversampling | CARST |
1 | Sen2-20180304-20180314 | 10 | 48 | 480 | 12 | 120 | NAOF | 16-node oversampling | CARST |
2 | Sen2-20180304-20180314 | 10 | 48 | 480 | 12 | 120 | None | 16-node oversampling | CARST |
3 | Sen2-20180304-20180314 | 10 | 48 | 480 | 1 | 10 | Gau | 16-node oversampling | CARST |
4 | Sen2-20180304-20180314 | 10 | 48 | 480 | 1 | 10 | NAOF | 16-node oversampling | CARST |
5 | Sen2-20180304-20180314 | 10 | 48 | 480 | 1 | 10 | None | 16-node oversampling | CARST |
6 | Sen2-20180304-20180314 | 10 | 48 | 480 | 4 | 40 | Gau | 16-node oversampling | CARST |
7 | Sen2-20180304-20180314 | 10 | 48 | 480 | 4 | 40 | NAOF | 16-node oversampling | CARST |
8 | Sen2-20180304-20180314 | 10 | 48 | 480 | 4 | 40 | None | 16-node oversampling | CARST |
9 | Sen2-20180304-20180314 | 10 | 64 | 640 | 12 | 120 | Gau | 16-node oversampling | CARST |
10 | Sen2-20180304-20180314 | 10 | 64 | 640 | 12 | 120 | NAOF | 16-node oversampling | CARST |
11 | Sen2-20180304-20180314 | 10 | 64 | 640 | 12 | 120 | None | 16-node oversampling | CARST |
12 | Sen2-20180304-20180314 | 10 | 64 | 640 | 1 | 10 | Gau | 16-node oversampling | CARST |
13 | Sen2-20180304-20180314 | 10 | 64 | 640 | 1 | 10 | NAOF | 16-node oversampling | CARST |
14 | Sen2-20180304-20180314 | 10 | 64 | 640 | 1 | 10 | None | 16-node oversampling | CARST |
15 | Sen2-20180304-20180314 | 10 | 64 | 640 | 4 | 40 | Gau | 16-node oversampling | CARST |
16 | Sen2-20180304-20180314 | 10 | 64 | 640 | 4 | 40 | NAOF | 16-node oversampling | CARST |
17 | Sen2-20180304-20180314 | 10 | 64 | 640 | 4 | 40 | None | 16-node oversampling | CARST |
18 | LS8-20180304-20180405 | 32 | 32 | 480 | 1 | 15 | Gau | 16-node oversampling | CARST |
19 | LS8-20180304-20180405 | 32 | 32 | 480 | 1 | 15 | NAOF | 16-node oversampling | CARST |
20 | LS8-20180304-20180405 | 32 | 32 | 480 | 1 | 15 | None | 16-node oversampling | CARST |
21 | LS8-20180304-20180405 | 32 | 32 | 480 | 4 | 60 | Gau | 16-node oversampling | CARST |
22 | LS8-20180304-20180405 | 32 | 32 | 480 | 4 | 60 | NAOF | 16-node oversampling | CARST |
23 | LS8-20180304-20180405 | 32 | 32 | 480 | 4 | 60 | None | 16-node oversampling | CARST |
24 | LS8-20180304-20180405 | 32 | 32 | 480 | 8 | 120 | Gau | 16-node oversampling | CARST |
25 | LS8-20180304-20180405 | 32 | 32 | 480 | 8 | 120 | NAOF | 16-node oversampling | CARST |
26 | LS8-20180304-20180405 | 32 | 32 | 480 | 8 | 120 | None | 16-node oversampling | CARST |
27 | LS8-20180304-20180405 | 32 | 64 | 960 | 1 | 15 | Gau | 16-node oversampling | CARST |
28 | LS8-20180304-20180405 | 32 | 64 | 960 | 1 | 15 | NAOF | 16-node oversampling | CARST |
29 | LS8-20180304-20180405 | 32 | 64 | 960 | 1 | 15 | None | 16-node oversampling | CARST |
30 | LS8-20180304-20180405 | 32 | 64 | 960 | 4 | 60 | Gau | 16-node oversampling | CARST |
31 | LS8-20180304-20180405 | 32 | 64 | 960 | 4 | 60 | NAOF | 16-node oversampling | CARST |
32 | LS8-20180304-20180405 | 32 | 64 | 960 | 4 | 60 | None | 16-node oversampling | CARST |
33 | LS8-20180304-20180405 | 32 | 64 | 960 | 8 | 120 | Gau | 16-node oversampling | CARST |
34 | LS8-20180304-20180405 | 32 | 64 | 960 | 8 | 120 | NAOF | 16-node oversampling | CARST |
35 | LS8-20180304-20180405 | 32 | 64 | 960 | 8 | 120 | None | 16-node oversampling | CARST |
36 | Sen2-20180508-20180627 | 50 | 48 | 480 | 12 | 120 | Gau | 16-node oversampling | CARST |
37 | Sen2-20180508-20180627 | 50 | 48 | 480 | 12 | 120 | NAOF | 16-node oversampling | CARST |
38 | Sen2-20180508-20180627 | 50 | 48 | 480 | 12 | 120 | None | 16-node oversampling | CARST |
39 | Sen2-20180508-20180627 | 50 | 48 | 480 | 1 | 10 | Gau | 16-node oversampling | CARST |
40 | Sen2-20180508-20180627 | 50 | 48 | 480 | 1 | 10 | NAOF | 16-node oversampling | CARST |
41 | Sen2-20180508-20180627 | 50 | 48 | 480 | 1 | 10 | None | 16-node oversampling | CARST |
42 | Sen2-20180508-20180627 | 50 | 48 | 480 | 4 | 40 | Gau | 16-node oversampling | CARST |
43 | Sen2-20180508-20180627 | 50 | 48 | 480 | 4 | 40 | NAOF | 16-node oversampling | CARST |
44 | Sen2-20180508-20180627 | 50 | 48 | 480 | 4 | 40 | None | 16-node oversampling | CARST |
45 | Sen2-20180508-20180627 | 50 | 64 | 640 | 12 | 120 | Gau | 16-node oversampling | CARST |
46 | Sen2-20180508-20180627 | 50 | 64 | 640 | 12 | 120 | NAOF | 16-node oversampling | CARST |
47 | Sen2-20180508-20180627 | 50 | 64 | 640 | 12 | 120 | None | 16-node oversampling | CARST |
48 | Sen2-20180508-20180627 | 50 | 64 | 640 | 1 | 10 | Gau | 16-node oversampling | CARST |
49 | Sen2-20180508-20180627 | 50 | 64 | 640 | 1 | 10 | NAOF | 16-node oversampling | CARST |
50 | Sen2-20180508-20180627 | 50 | 64 | 640 | 1 | 10 | None | 16-node oversampling | CARST |
51 | Sen2-20180508-20180627 | 50 | 64 | 640 | 4 | 40 | Gau | 16-node oversampling | CARST |
52 | Sen2-20180508-20180627 | 50 | 64 | 640 | 4 | 40 | NAOF | 16-node oversampling | CARST |
53 | Sen2-20180508-20180627 | 50 | 64 | 640 | 4 | 40 | None | 16-node oversampling | CARST |
54 | LS8-20180802-20180818 | 16 | 32 | 480 | 1 | 15 | Gau | 16-node oversampling | CARST |
55 | LS8-20180802-20180818 | 16 | 32 | 480 | 1 | 15 | NAOF | 16-node oversampling | CARST |
56 | LS8-20180802-20180818 | 16 | 32 | 480 | 1 | 15 | None | 16-node oversampling | CARST |
57 | LS8-20180802-20180818 | 16 | 32 | 480 | 4 | 60 | Gau | 16-node oversampling | CARST |
58 | LS8-20180802-20180818 | 16 | 32 | 480 | 4 | 60 | NAOF | 16-node oversampling | CARST |
59 | LS8-20180802-20180818 | 16 | 32 | 480 | 4 | 60 | None | 16-node oversampling | CARST |
60 | LS8-20180802-20180818 | 16 | 32 | 480 | 8 | 120 | Gau | 16-node oversampling | CARST |
61 | LS8-20180802-20180818 | 16 | 32 | 480 | 8 | 120 | NAOF | 16-node oversampling | CARST |
62 | LS8-20180802-20180818 | 16 | 32 | 480 | 8 | 120 | None | 16-node oversampling | CARST |
63 | LS8-20180802-20180818 | 16 | 64 | 960 | 1 | 15 | Gau | 16-node oversampling | CARST |
64 | LS8-20180802-20180818 | 16 | 64 | 960 | 1 | 15 | NAOF | 16-node oversampling | CARST |
65 | LS8-20180802-20180818 | 16 | 64 | 960 | 1 | 15 | None | 16-node oversampling | CARST |
66 | LS8-20180802-20180818 | 16 | 64 | 960 | 4 | 60 | Gau | 16-node oversampling | CARST |
67 | LS8-20180802-20180818 | 16 | 64 | 960 | 4 | 60 | NAOF | 16-node oversampling | CARST |
68 | LS8-20180802-20180818 | 16 | 64 | 960 | 4 | 60 | None | 16-node oversampling | CARST |
69 | LS8-20180802-20180818 | 16 | 64 | 960 | 8 | 120 | Gau | 16-node oversampling | CARST |
70 | LS8-20180802-20180818 | 16 | 64 | 960 | 8 | 120 | NAOF | 16-node oversampling | CARST |
71 | LS8-20180802-20180818 | 16 | 64 | 960 | 8 | 120 | None | 16-node oversampling | CARST |
72 | LS8-20180304-20180405 | 32 | varying: multi-pass | varying: multi-pass | 15.13 | 242.1 | NAOF | interest point groups | GIV |
73 | LS8-20180304-20180405 | 32 | varying: multi-pass | varying: multi-pass | 4.009 | 60.14 | NAOF | interest point groups | GIV |
74 | LS8-20180304-20180405 | 32 | varying: multi-pass | varying: multi-pass | 15.13 | 242.1 | Gau | interest point groups | GIV |
75 | LS8-20180304-20180405 | 32 | varying: multi-pass | varying: multi-pass | 4.009 | 60.14 | Gau | interest point groups | GIV |
76 | LS8-20180304-20180405 | 32 | varying: multi-pass | varying: multi-pass | 15.13 | 242.1 | None | interest point groups | GIV |
77 | LS8-20180304-20180405 | 32 | varying: multi-pass | varying: multi-pass | 4.009 | 60.14 | None | interest point groups | GIV |
78 | LS8-20180802-20180818 | 16 | varying: multi-pass | varying: multi-pass | 15.13 | 242.1 | NAOF | interest point groups | GIV |
79 | LS8-20180802-20180818 | 16 | varying: multi-pass | varying: multi-pass | 4.009 | 60.14 | NAOF | interest point groups | GIV |
80 | LS8-20180802-20180818 | 16 | varying: multi-pass | varying: multi-pass | 15.13 | 242.1 | Gau | interest point groups | GIV |
81 | LS8-20180802-20180818 | 16 | varying: multi-pass | varying: multi-pass | 4.009 | 60.14 | Gau | interest point groups | GIV |
82 | LS8-20180802-20180818 | 16 | varying: multi-pass | varying: multi-pass | 15.13 | 242.1 | None | interest point groups | GIV |
83 | LS8-20180802-20180818 | 16 | varying: multi-pass | varying: multi-pass | 4.009 | 60.14 | None | interest point groups | GIV |
84 | Sen2-20180304-20180314 | 10 | varying: multi-pass | varying: multi-pass | 16.04 | 160.4 | NAOF | interest point groups | GIV |
85 | Sen2-20180304-20180314 | 10 | varying: multi-pass | varying: multi-pass | 4.003 | 40.03 | NAOF | interest point groups | GIV |
86 | Sen2-20180304-20180314 | 10 | varying: multi-pass | varying: multi-pass | 16.04 | 160.4 | Gau | interest point groups | GIV |
87 | Sen2-20180304-20180314 | 10 | varying: multi-pass | varying: multi-pass | 4.003 | 40.03 | Gau | interest point groups | GIV |
88 | Sen2-20180304-20180314 | 10 | varying: multi-pass | varying: multi-pass | 16.04 | 160.4 | None | interest point groups | GIV |
89 | Sen2-20180304-20180314 | 10 | varying: multi-pass | varying: multi-pass | 4.003 | 40.03 | None | interest point groups | GIV |
90 | Sen2-20180508-20180627 | 50 | varying: multi-pass | varying: multi-pass | 16.04 | 160.4 | NAOF | interest point groups | GIV |
91 | Sen2-20180508-20180627 | 50 | varying: multi-pass | varying: multi-pass | 4.003 | 40.03 | NAOF | interest point groups | GIV |
92 | Sen2-20180508-20180627 | 50 | varying: multi-pass | varying: multi-pass | 16.04 | 160.4 | Gau | interest point groups | GIV |
93 | Sen2-20180508-20180627 | 50 | varying: multi-pass | varying: multi-pass | 4.003 | 40.03 | Gau | interest point groups | GIV |
94 | Sen2-20180508-20180627 | 50 | varying: multi-pass | varying: multi-pass | 16.04 | 160.4 | None | interest point groups | GIV |
95 | Sen2-20180508-20180627 | 50 | varying: multi-pass | varying: multi-pass | 4.003 | 40.03 | None | interest point groups | GIV |
96 | LS8-20180304-20180405 | 32 | 31 | 465 | 1 | 15 | Gau | parabolic | Vmap |
97 | LS8-20180304-20180405 | 32 | 65 | 975 | 1 | 15 | Gau | parabolic | Vmap |
98 | LS8-20180802-20180818 | 16 | 31 | 465 | 1 | 15 | Gau | parabolic | Vmap |
99 | LS8-20180802-20180818 | 16 | 65 | 975 | 1 | 15 | Gau | parabolic | Vmap |
100 | Sen2-20180304-20180314 | 10 | 31 | 310 | 1 | 10 | Gau | parabolic | Vmap |
101 | Sen2-20180304-20180314 | 10 | 65 | 650 | 1 | 10 | Gau | parabolic | Vmap |
102 | Sen2-20180508-20180627 | 50 | 31 | 310 | 1 | 10 | Gau | parabolic | Vmap |
103 | Sen2-20180508-20180627 | 50 | 65 | 650 | 1 | 10 | Gau | parabolic | Vmap |
104 | LS8-20180304-20180405 | 32 | 31 | 465 | 1 | 15 | None | parabolic | Vmap |
105 | LS8-20180304-20180405 | 32 | 65 | 975 | 1 | 15 | None | parabolic | Vmap |
106 | LS8-20180802-20180818 | 16 | 31 | 465 | 1 | 15 | None | parabolic | Vmap |
107 | LS8-20180802-20180818 | 16 | 65 | 975 | 1 | 15 | None | parabolic | Vmap |
108 | Sen2-20180304-20180314 | 10 | 31 | 310 | 1 | 10 | None | parabolic | Vmap |
109 | Sen2-20180304-20180314 | 10 | 65 | 650 | 1 | 10 | None | parabolic | Vmap |
110 | Sen2-20180508-20180627 | 50 | 31 | 310 | 1 | 10 | None | parabolic | Vmap |
111 | Sen2-20180508-20180627 | 50 | 65 | 650 | 1 | 10 | None | parabolic | Vmap |
112 | LS8-20180304-20180405 | 32 | 31 | 465 | 1 | 15 | LoG | parabolic | Vmap |
113 | LS8-20180304-20180405 | 32 | 31 | 465 | 1 | 15 | LoG | affine adaptive | Vmap |
114 | LS8-20180304-20180405 | 32 | 31 | 465 | 1 | 15 | LoG | affine | Vmap |
115 | LS8-20180802-20180818 | 16 | 31 | 465 | 1 | 15 | LoG | parabolic | Vmap |
116 | LS8-20180802-20180818 | 16 | 31 | 465 | 1 | 15 | LoG | affine adaptive | Vmap |
117 | LS8-20180802-20180818 | 16 | 31 | 465 | 1 | 15 | LoG | affine | Vmap |
118 | Sen2-20180304-20180314 | 10 | 31 | 310 | 1 | 10 | LoG | parabolic | Vmap |
119 | Sen2-20180304-20180314 | 10 | 31 | 310 | 1 | 10 | LoG | affine adaptive | Vmap |
120 | Sen2-20180304-20180314 | 10 | 31 | 310 | 1 | 10 | LoG | affine | Vmap |
121 | Sen2-20180508-20180627 | 50 | 31 | 310 | 1 | 10 | LoG | parabolic | Vmap |
122 | Sen2-20180508-20180627 | 50 | 31 | 310 | 1 | 10 | LoG | affine adaptive | Vmap |
123 | Sen2-20180508-20180627 | 50 | 31 | 310 | 1 | 10 | LoG | affine | Vmap |
124 | LS8-20180304-20180405 | 32 | 32 | 480 | 4 | 60 | None | pyrUP | autoRIFT |
125 | LS8-20180304-20180405 | 32 | 32 | 480 | 8 | 120 | None | pyrUP | autoRIFT |
126 | LS8-20180304-20180405 | 32 | 64 | 960 | 4 | 60 | None | pyrUP | autoRIFT |
127 | LS8-20180304-20180405 | 32 | 64 | 960 | 8 | 120 | None | pyrUP | autoRIFT |
128 | LS8-20180304-20180405 | 32 | 32 | 480 | 4 | 60 | Gau | pyrUP | autoRIFT |
129 | LS8-20180304-20180405 | 32 | 32 | 480 | 8 | 120 | Gau | pyrUP | autoRIFT |
130 | LS8-20180304-20180405 | 32 | 64 | 960 | 4 | 60 | Gau | pyrUP | autoRIFT |
131 | LS8-20180304-20180405 | 32 | 64 | 960 | 8 | 120 | Gau | pyrUP | autoRIFT |
132 | LS8-20180304-20180405 | 32 | 32 | 480 | 4 | 60 | NAOF | pyrUP | autoRIFT |
133 | LS8-20180304-20180405 | 32 | 32 | 480 | 8 | 120 | NAOF | pyrUP | autoRIFT |
134 | LS8-20180304-20180405 | 32 | 64 | 960 | 4 | 60 | NAOF | pyrUP | autoRIFT |
135 | LS8-20180304-20180405 | 32 | 64 | 960 | 8 | 120 | NAOF | pyrUP | autoRIFT |
136 | LS8-20180802-20180818 | 16 | 32 | 480 | 4 | 60 | None | pyrUP | autoRIFT |
137 | LS8-20180802-20180818 | 16 | 32 | 480 | 8 | 120 | None | pyrUP | autoRIFT |
138 | LS8-20180802-20180818 | 16 | 64 | 960 | 4 | 60 | None | pyrUP | autoRIFT |
139 | LS8-20180802-20180818 | 16 | 64 | 960 | 8 | 120 | None | pyrUP | autoRIFT |
140 | LS8-20180802-20180818 | 16 | 32 | 480 | 4 | 60 | Gau | pyrUP | autoRIFT |
141 | LS8-20180802-20180818 | 16 | 32 | 480 | 8 | 120 | Gau | pyrUP | autoRIFT |
142 | LS8-20180802-20180818 | 16 | 64 | 960 | 4 | 60 | Gau | pyrUP | autoRIFT |
143 | LS8-20180802-20180818 | 16 | 64 | 960 | 8 | 120 | Gau | pyrUP | autoRIFT |
144 | LS8-20180802-20180818 | 16 | 32 | 480 | 4 | 60 | NAOF | pyrUP | autoRIFT |
145 | LS8-20180802-20180818 | 16 | 32 | 480 | 8 | 120 | NAOF | pyrUP | autoRIFT |
146 | LS8-20180802-20180818 | 16 | 64 | 960 | 4 | 60 | NAOF | pyrUP | autoRIFT |
147 | LS8-20180802-20180818 | 16 | 64 | 960 | 8 | 120 | NAOF | pyrUP | autoRIFT |
148 | Sen2-20180304-20180314 | 10 | 32 | 320 | 4 | 40 | None | pyrUP | autoRIFT |
149 | Sen2-20180304-20180314 | 10 | 32 | 320 | 8 | 80 | None | pyrUP | autoRIFT |
150 | Sen2-20180304-20180314 | 10 | 64 | 640 | 4 | 40 | None | pyrUP | autoRIFT |
151 | Sen2-20180304-20180314 | 10 | 64 | 640 | 8 | 80 | None | pyrUP | autoRIFT |
152 | Sen2-20180304-20180314 | 10 | 32 | 320 | 4 | 40 | Gau | pyrUP | autoRIFT |
153 | Sen2-20180304-20180314 | 10 | 32 | 320 | 8 | 80 | Gau | pyrUP | autoRIFT |
154 | Sen2-20180304-20180314 | 10 | 64 | 640 | 4 | 40 | Gau | pyrUP | autoRIFT |
155 | Sen2-20180304-20180314 | 10 | 64 | 640 | 8 | 80 | Gau | pyrUP | autoRIFT |
156 | Sen2-20180304-20180314 | 10 | 32 | 320 | 4 | 40 | NAOF | pyrUP | autoRIFT |
157 | Sen2-20180304-20180314 | 10 | 32 | 320 | 8 | 80 | NAOF | pyrUP | autoRIFT |
158 | Sen2-20180304-20180314 | 10 | 64 | 640 | 4 | 40 | NAOF | pyrUP | autoRIFT |
159 | Sen2-20180304-20180314 | 10 | 64 | 640 | 8 | 80 | NAOF | pyrUP | autoRIFT |
160 | Sen2-20180508-20180627 | 50 | 32 | 320 | 4 | 40 | None | pyrUP | autoRIFT |
161 | Sen2-20180508-20180627 | 50 | 32 | 320 | 8 | 80 | None | pyrUP | autoRIFT |
162 | Sen2-20180508-20180627 | 50 | 64 | 640 | 4 | 40 | None | pyrUP | autoRIFT |
163 | Sen2-20180508-20180627 | 50 | 64 | 640 | 8 | 80 | None | pyrUP | autoRIFT |
164 | Sen2-20180508-20180627 | 50 | 32 | 320 | 4 | 40 | Gau | pyrUP | autoRIFT |
165 | Sen2-20180508-20180627 | 50 | 32 | 320 | 8 | 80 | Gau | pyrUP | autoRIFT |
166 | Sen2-20180508-20180627 | 50 | 64 | 640 | 4 | 40 | Gau | pyrUP | autoRIFT |
167 | Sen2-20180508-20180627 | 50 | 64 | 640 | 8 | 80 | Gau | pyrUP | autoRIFT |
168 | Sen2-20180508-20180627 | 50 | 32 | 320 | 4 | 40 | NAOF | pyrUP | autoRIFT |
169 | Sen2-20180508-20180627 | 50 | 32 | 320 | 8 | 80 | NAOF | pyrUP | autoRIFT |
170 | Sen2-20180508-20180627 | 50 | 64 | 640 | 4 | 40 | NAOF | pyrUP | autoRIFT |
171 | Sen2-20180508-20180627 | 50 | 64 | 640 | 8 | 80 | NAOF | pyrUP | autoRIFT |
Abbreviations in Table S1¶
LS8: Landsat 8
Sen2: Sentinel-2
px: pixels
Gau: Gaussian high-pass filter
NAOF: Near anisotropic orientation filter
LoG: Laplacian of Gaussian filter
Subpixel: Sub-pixel matching method
pyrUP: Laplacian pyramid method