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0ang20190922t192642_r0_c256_w512_h512
1ang20190922t192642_r10240_c0_w512_h512
2ang20190922t192642_r10752_c0_w512_h512
3ang20190922t192642_r2048_c0_w512_h512
4ang20190922t192642_r3270_c384_w151_h151
5ang20190922t192642_r4034_c360_w151_h151
6ang20190922t192642_r4578_c217_w151_h151
7ang20190922t192642_r4834_c257_w151_h151
8ang20190922t192642_r4928_c373_w151_h151
9ang20190922t192642_r512_c256_w512_h512
10ang20190922t192642_r6423_c113_w151_h151
11ang20190922t192642_r7680_c0_w512_h512
12ang20190922t192642_r9472_c0_w512_h512
13ang20190922t194340_r0_c256_w512_h512
14ang20190922t194340_r1953_c438_w151_h151
15ang20190922t194340_r2642_c324_w151_h151
16ang20190922t194340_r3328_c0_w512_h512
17ang20190922t194340_r5074_c444_w151_h151
18ang20190922t194340_r6144_c0_w512_h512
19ang20190922t194340_r7936_c0_w512_h512
20ang20190922t194340_r8448_c0_w512_h512
21ang20190922t194340_r9472_c0_w512_h512
22ang20190922t194340_r9984_c0_w512_h512
23ang20190922t203229_r10752_c512_w512_h512
24ang20190922t203229_r1280_c768_w512_h512
25ang20190922t203229_r256_c512_w512_h512
26ang20190922t203229_r3328_c512_w512_h512
27ang20190922t203229_r5632_c256_w512_h512
28ang20190922t203229_r7371_c312_w151_h151
29ang20190922t203229_r7396_c411_w151_h151
30ang20190922t203229_r7486_c72_w151_h151
31ang20190922t203229_r768_c512_w512_h512
32ang20190922t203229_r8192_c256_w512_h512
33ang20190923t163307_r0_c0_w512_h512
34ang20190923t163307_r1024_c0_w512_h512
35ang20190923t163307_r10752_c0_w512_h512
36ang20190923t163307_r11597_c539_w151_h151
37ang20190923t163307_r12822_c605_w151_h151
38ang20190923t163307_r13596_c639_w151_h151
39ang20190923t163307_r13801_c577_w151_h151
40ang20190923t163307_r1536_c0_w512_h512
41ang20190923t163307_r2796_c346_w151_h151
42ang20190923t163307_r4113_c198_w151_h151
43ang20190923t163307_r4370_c239_w151_h151
44ang20190923t163307_r5120_c256_w512_h512
45ang20190923t163307_r5958_c123_w151_h151
46ang20190923t163307_r6778_c561_w151_h151
47ang20190923t163307_r7168_c256_w512_h512
48ang20190923t163307_r7936_c256_w512_h512
49ang20190923t170747_r0_c0_w512_h512
50ang20190923t170747_r10240_c256_w512_h512
51ang20190923t170747_r10752_c256_w512_h512
52ang20190923t170747_r12288_c256_w512_h512
53ang20190923t170747_r14210_c160_w151_h151
54ang20190923t170747_r15616_c256_w512_h512
55ang20190923t170747_r2291_c472_w151_h151
56ang20190923t170747_r3144_c180_w151_h151
57ang20190923t170747_r3502_c419_w151_h151
58ang20190923t170747_r5120_c256_w512_h512
59ang20190923t170747_r512_c0_w512_h512
60ang20190923t170747_r6732_c289_w151_h151
61ang20190923t170747_r8220_c606_w151_h151
62ang20190923t170747_r8630_c560_w151_h151
63ang20190923t170747_r9537_c44_w151_h151
64ang20190923t172416_r0_c0_w512_h512
65ang20190923t172416_r10579_c413_w151_h151
66ang20190923t172416_r12122_c231_w151_h151
67ang20190923t172416_r13312_c256_w512_h512
68ang20190923t172416_r13824_c256_w512_h512
69ang20190923t172416_r15067_c399_w151_h151
70ang20190923t172416_r2048_c0_w512_h512
71ang20190923t172416_r3584_c0_w512_h512
72ang20190923t172416_r4608_c0_w512_h512
73ang20190923t172416_r9472_c0_w512_h512
74ang20190923t174142_r0_c0_w512_h512
75ang20190923t174142_r11264_c256_w512_h512
76ang20190923t174142_r11776_c256_w512_h512
77ang20190923t174142_r12544_c256_w512_h512
78ang20190923t174142_r13784_c155_w151_h151
79ang20190923t174142_r15306_c621_w151_h151
80ang20190923t174142_r15511_c283_w151_h151
81ang20190923t174142_r4096_c0_w512_h512
82ang20190923t174142_r512_c0_w512_h512
83ang20190923t174142_r5826_c168_w151_h151
84ang20190923t174142_r7561_c18_w151_h151
85ang20190923t174142_r7604_c458_w151_h151
86ang20190923t174142_r7936_c0_w512_h512
87ang20190923t174142_r9431_c547_w151_h151
88ang20190923t174142_r9678_c231_w151_h151
89ang20190923t181729_r0_c256_w512_h512
90ang20190923t181729_r10752_c0_w512_h512
91ang20190923t181729_r11776_c0_w512_h512
92ang20190923t181729_r13645_c146_w151_h151
93ang20190923t181729_r1984_c475_w151_h151
94ang20190923t181729_r2423_c148_w151_h151
95ang20190923t181729_r3963_c475_w151_h151
96ang20190923t181729_r4864_c256_w512_h512
97ang20190923t181729_r512_c256_w512_h512
98ang20190923t181729_r6905_c570_w151_h151
99ang20190923t181729_r8192_c256_w512_h512
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Paper

Overview

This repository hosts curated data products used for evaluation and training in the article "Optimizing Methane Detection Onboard Satellites: Speed, Accuracy, and Low-Power Solutions for Resource-Constrained Hardware."

The dataset consists exclusively of products generated from 72 hyperspectral channels within the wavelength range of 2122–2488 nm. These products served as the training data for the models available here.

The original raw hyperspectral data required to create these products is publicly accessible at: https://huggingface.co/collections/previtus/starcop-67f13cf30def71591f281a41

Sample Usage (Notebook Demos)

You can try out our demos directly in Google Colab:

Citation

If you use this dataset in your research, please cite our article:

@misc{herec2025optimizingmethanedetectionboard,
      title={Optimizing Methane Detection On Board Satellites: Speed, Accuracy, and Low-Power Solutions for Resource-Constrained Hardware}, 
      author={Jonáš Herec and Vít Růžička and Rado Pitoňák},
      year={2025},
      eprint={2507.01472},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2507.01472}, 
}
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