Table 6 Reevaluating RaVAEn. The final change predictions were derived by using \(\min ()\) on the change predictions from the memory. In RaVAEn-Floods, the geo-index used was NDWI; in RaVAEn-Wildfires, the NBR; and in RaVAEn-Landslides and RaVAEn-Hurricanes, NDVI. Highlighted are the best scores for STTORM-CD and RaVAEn models for each metric. All values of the evaluation metrics are reported as percentages.

From: STTORM-CD low-demand and high-impact disaster monitoring onboard satellites using change detection

Dataset

RaVAEn-Landslides

RaVAEn-Wildfires

RaVAEn-Hurricanes

RaVAEn-Floods

Tiles count

626

27865

11773

11253

Changed tiles [%]

23.64

57.89

27.57

21.70

Metric

AUPRC \(\uparrow\)

F1 \(\uparrow\)

AUPRC \(\uparrow\)

F1 \(\uparrow\)

AUPRC \(\uparrow\)

F1 \(\uparrow\)

AUPRC \(\uparrow\)

F1 \(\uparrow\)

Geo-index

71.69

67.92

95.16

88.60

79.12

72.27

52.53

50.76

Cosine baseline

68.06

67.48

92.52

87.40

69.55

70.57

65.63

70.30

RaVAEn – small

83.26

75.74

93.16

89.88

75.87

67.06

70.92

66.91

RaVAEn – medium

84.72

75.91

93.18

89.95

73.52

65.24

69.73

65.33

RaVAEn – large

83.12

74.68

93.49

90.07

71.85

63.52

68.11

64.86

STTORM-CD – small

80.72

75.79

90.46

89.30

63.88

56.88

81.67*

71.99*

STTORM-CD – medium

82.22

73.13

89.15

88.32

69.05

62.73

79.04*

72.02*

STTORM-CD – large

82.60

74.29

93.42

89.33

70.75

64.36

79.79*

71.84*

  1. *Used as a validation dataset.