Hugging Face's logo

Datasets:
tacofoundation
/
cloudsen12

Modalities:
Geospatial
Languages:
English
Tags:
clouds
sentinel-2
image-segmentation
deep-learning
remote-sensing
License:
Dataset card Files Community
csaybar commited on
Commit
f604646
·
verified ·
1 Parent(s): b6e1a30

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +148 -45
README.md CHANGED
@@ -47,15 +47,18 @@ repository.
47
  - **`cloudsen12-l2a`**: Similar to cloudsen12-l1c but based on Sentinel-2 Level-2A data as processed by Google Earth Engine.
48
 
49
  - **`cloudsen12-extra`**: A supplementary collection of metadata to enhance contextual understanding of landscapes. Cloud masks from multiple sources have been normalized to align with the CloudSEN12 class schema. This mode includes:
50
- - **`s1_vv:`** Normalized Sentinel-1 Global Backscatter Model Land Surface (VV polarization).
51
- - **`s1_vh:`** Normalized Sentinel-1 Global Backscatter Model Land Surface (VH polarization).
52
- - **`elevation:`** Elevation data (meters) sourced from the MERIT Hydro dataset.
53
- - **`LC10:`** ESA WorldCover 10m v100 land cover product.
54
- - **`cloudmask_qa:`** Cloud mask from Sentinel-2 Level-1C.
55
  - **`cloudmask_sen2cor:`** Cloud mask from Sentinel-2 Level-2A.
56
- - **`cloudmask_cloudscore:`** Cloud detection results from Google Cloud Masking.
57
  - **`cloudmask_s2cloudless:`** Cloud mask generated by Sentinel Hub Cloud Detector.
58
- - **`cloudmask_unetmobv2:`** A cloud mask produced by a UnetMobV2 model trained on the CloudSEN12 dataset.
 
 
 
 
59
 
60
  - Changelog:
61
  Version 1.1.0:
@@ -92,7 +95,6 @@ repository.
92
  respectively. `high`, `scribble`, and `nolabel` refer to the types of expert-labeled annotations*
93
 
94
 
95
-
96
  ## 🔄 Reproducible Example
97
 
98
  <a target="_blank" href="https://colab.research.google.com/drive/1U9n40rwdnn73bdWruONA3hIs1-H3f74Q">
@@ -106,11 +108,12 @@ Load this dataset using the `tacoreader` library.
106
  import tacoreader
107
  import rasterio as rio
108
 
109
- print(tacoreader.__version__) # 0.5.2
110
 
111
  # Remotely load the Cloud-Optimized Dataset
112
  dataset = tacoreader.load("tacofoundation:cloudsen12-l1c")
113
  #dataset = tacoreader.load("tacofoundation:cloudsen12-l2a")
 
114
 
115
  # Read a sample
116
  sample_idx = 2422
@@ -243,40 +246,140 @@ The dataset contains four classes: clear, thick cloud, thin cloud, and cloud sha
243
 
244
  ## 🌈 Optical Bands
245
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
246
 
247
- Spectral bands related to the sensor: L1C
248
-
249
- |**Name**|**Common Name**|**Description**|**Center Wavelength**|**Full Width Half Max**|**Index**|
250
- | :--- | :--- | :--- | :--- | :--- | :--- |
251
- |B01|coastal aerosol|Band 1 - Coastal aerosol - 60m|443.5|17.0|0|
252
- |B02|blue|Band 2 - Blue - 10m|496.5|53.0|1|
253
- |B03|green|Band 3 - Green - 10m|560.0|34.0|2|
254
- |B04|red|Band 4 - Red - 10m|664.5|29.0|3|
255
- |B05|red edge 1|Band 5 - Vegetation red edge 1 - 20m|704.5|13.0|4|
256
- |B06|red edge 2|Band 6 - Vegetation red edge 2 - 20m|740.5|13.0|5|
257
- |B07|red edge 3|Band 7 - Vegetation red edge 3 - 20m|783.0|18.0|6|
258
- |B08|NIR|Band 8 - Near infrared - 10m|840.0|114.0|7|
259
- |B8A|red edge 4|Band 8A - Vegetation red edge 4 - 20m|864.5|19.0|8|
260
- |B09|water vapor|Band 9 - Water vapor - 60m|945.0|18.0|9|
261
- |B10|cirrus|Band 10 - Cirrus - 60m|1375.5|31.0|10|
262
- |B11|SWIR 1|Band 11 - Shortwave infrared 1 - 20m|1613.5|89.0|11|
263
- |B12|SWIR 2|Band 12 - Shortwave infrared 2 - 20m|2199.5|173.0|12|
264
-
265
- Spectral bands related to the sensor: L2A
266
-
267
- | Band | Name | Description | Center Wavelength (nm) | Bandwidth (nm) | Index |
268
- | :--- | :----------- | :------------------------------------------------------------------------------------------- | :--------------------- | :------------ | :---- |
269
- | B01 | Coastal aerosol | Band 1 - Coastal aerosol - 60m | 443.5 | 17.0 | 0 |
270
- | B02 | Blue | Band 2 - Blue - 10m | 496.5 | 53.0 | 1 |
271
- | B03 | Green | Band 3 - Green - 10m | 560.0 | 34.0 | 2 |
272
- | B04 | Red | Band 4 - Red - 10m | 664.5 | 29.0 | 3 |
273
- | B05 | Red edge 1 | Band 5 - Vegetation red edge 1 - 20m | 704.5 | 13.0 | 4 |
274
- | B06 | Red edge 2 | Band 6 - Vegetation red edge 2 - 20m | 740.5 | 13.0 | 5 |
275
- | B07 | Red edge 3 | Band 7 - Vegetation red edge 3 - 20m | 783.0 | 18.0 | 6 |
276
- | B08 | NIR | Band 8 - Near infrared - 10m | 840.0 | 114.0 | 7 |
277
- | B8A | Red edge 4 | Band 8A - Vegetation red edge 4 - 20m | 864.5 | 19.0 | 8 |
278
- | B09 | Water vapor | Band 9 - Water vapor - 60m | 945.0 | 18.0 | 9 |
279
- | B11 | SWIR 1 | Band 11 - Shortwave infrared 1 - 20m | 1613.5 | 89.0 | 10 |
280
- | B12 | SWIR 2 | Band 12 - Shortwave infrared 2 - 20m | 2199.5 | 173.0 | 11 |
281
- | AOT | - | Aerosol Optical Thickness | - | - | 12 |
282
- | WVP | - | Water Vapor Pressure. The height the water would occupy if the vapor were condensed into liquid and spread evenly across the column | - | - | 13 |
 
47
  - **`cloudsen12-l2a`**: Similar to cloudsen12-l1c but based on Sentinel-2 Level-2A data as processed by Google Earth Engine.
48
 
49
  - **`cloudsen12-extra`**: A supplementary collection of metadata to enhance contextual understanding of landscapes. Cloud masks from multiple sources have been normalized to align with the CloudSEN12 class schema. This mode includes:
50
+ - **`elevation:`** Elevation data (meters) sourced from the Copernicus DEM GLO-30.
51
+ - **`lc10:`** ESA WorldCover 10m v100 land cover product.
52
+ - **`vv:`** Normalized Sentinel-1 Global Backscatter Model Land Surface (VV polarization).
53
+ - **`vh:`** Normalized Sentinel-1 Global Backscatter Model Land Surface (VH polarization).
54
+ - **`cloudmask_qa60:`** Cloud mask from Sentinel-2 Level-1C.
55
  - **`cloudmask_sen2cor:`** Cloud mask from Sentinel-2 Level-2A.
 
56
  - **`cloudmask_s2cloudless:`** Cloud mask generated by Sentinel Hub Cloud Detector.
57
+ - **`cloudmask_cloudscore_cs_v1:`** Cloud mask generated by [Pasquarella et al. 2023](https://openaccess.thecvf.com/content/CVPR2023W/EarthVision/html/Pasquarella_Comprehensive_Quality_Assessment_of_Optical_Satellite_Imagery_Using_Weakly_Supervised_CVPRW_2023_paper.html).
58
+ - **`cloudmask_cloudscore_cs_cdf_v1:`** Cloud mask generated by [Pasquarella et al. 2023](https://openaccess.thecvf.com/content/CVPR2023W/EarthVision/html/Pasquarella_Comprehensive_Quality_Assessment_of_Optical_Satellite_Imagery_Using_Weakly_Supervised_CVPRW_2023_paper.html).
59
+ - **`cloudmask_unetmobv2_v1:`** Cloud mask generated by [Aybar et al. 2022](https://www.nature.com/articles/s41597-022-01878-2).
60
+ - **`cloudmask_unetmobv2_v2:`** Cloud mask generated by [Aybar et al. 2024](https://www.sciencedirect.com/science/article/pii/S2352340924008163).
61
+ - **`cloudmask_sensei_v2:`** Cloud mask generated by [Alistair Francis 2024](https://ieeexplore.ieee.org/document/10505181).
62
 
63
  - Changelog:
64
  Version 1.1.0:
 
95
  respectively. `high`, `scribble`, and `nolabel` refer to the types of expert-labeled annotations*
96
 
97
 
 
98
  ## 🔄 Reproducible Example
99
 
100
  <a target="_blank" href="https://colab.research.google.com/drive/1U9n40rwdnn73bdWruONA3hIs1-H3f74Q">
 
108
  import tacoreader
109
  import rasterio as rio
110
 
111
+ print(tacoreader.__version__) # 0.5.3
112
 
113
  # Remotely load the Cloud-Optimized Dataset
114
  dataset = tacoreader.load("tacofoundation:cloudsen12-l1c")
115
  #dataset = tacoreader.load("tacofoundation:cloudsen12-l2a")
116
+ #dataset = tacoreader.load("tacofoundation:cloudsen12-extra")
117
 
118
  # Read a sample
119
  sample_idx = 2422
 
246
 
247
  ## 🌈 Optical Bands
248
 
249
+ No data value is always: **99**
250
+
251
+ ### `cloudsen12-l1c`
252
+
253
+ A sample has:
254
+
255
+ - `s2l1c`
256
+
257
+
258
+ |**Name**|**Common Name**|**Description**|**Center Wavelength** (nm)|**Full Width Half Max** (nm)|**Index**|**Scale Factor**|
259
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
260
+ |B01|Coastal aerosol|Band 1 - Coastal aerosol - 60m|443.5|17.0|0|0.0001|
261
+ |B02|Blue|Band 2 - Blue - 10m|496.5|53.0|1|0.0001|
262
+ |B03|Green|Band 3 - Green - 10m|560.0|34.0|2|0.0001|
263
+ |B04|Red|Band 4 - Red - 10m|664.5|29.0|3|0.0001|
264
+ |B05|Red edge 1|Band 5 - Vegetation red edge 1 - 20m|704.5|13.0|4|0.0001|
265
+ |B06|Red edge 2|Band 6 - Vegetation red edge 2 - 20m|740.5|13.0|5|0.0001|
266
+ |B07|Red edge 3|Band 7 - Vegetation red edge 3 - 20m|783.0|18.0|6|0.0001|
267
+ |B08|NIR|Band 8 - Near infrared - 10m|840.0|114.0|7|0.0001|
268
+ |B8A|Red edge 4|Band 8A - Vegetation red edge 4 - 20m|864.5|19.0|8|0.0001|
269
+ |B09|Water vapor|Band 9 - Water vapor - 60m|945.0|18.0|9|0.0001|
270
+ |B10|Cirrus|Band 10 - Cirrus - 60m|1375.5|31.0|10|N/A|
271
+ |B11|SWIR 1|Band 11 - Shortwave infrared 1 - 20m|1613.5|89.0|11|0.0001|
272
+ |B12|SWIR 2|Band 12 - Shortwave infrared 2 - 20m|2199.5|173.0|12|0.0001|
273
+
274
+ - `target`
275
+
276
+ |**Name**|**Common Name**|**Description**|**Center Wavelength**|**Full Width Half Max**|**Index**|**Scale Factor**|
277
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
278
+ |B01|Cloud Label|Cloud labels annotated by humans|-|-|0|1|
279
+
280
+ ### `cloudsen12-2a`
281
+
282
+ A sample has:
283
+
284
+ - `s2l2a`
285
+
286
+
287
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
288
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
289
+ |B01|Coastal aerosol|Band 1 - Coastal aerosol - 60m|443.5|17.0|0|0.0001|
290
+ |B02|Blue|Band 2 - Blue - 10m|496.5|53.0|1|0.0001|
291
+ |B03|Green|Band 3 - Green - 10m|560.0|34.0|2|0.0001|
292
+ |B04|Red|Band 4 - Red - 10m|664.5|29.0|3|0.0001|
293
+ |B05|Red edge 1|Band 5 - Vegetation red edge 1 - 20m|704.5|13.0|4|0.0001|
294
+ |B06|Red edge 2|Band 6 - Vegetation red edge 2 - 20m|740.5|13.0|5|0.0001|
295
+ |B07|Red edge 3|Band 7 - Vegetation red edge 3 - 20m|783.0|18.0|6|0.0001|
296
+ |B08|NIR|Band 8 - Near infrared - 10m|840.0|114.0|7|0.0001|
297
+ |B8A|Red edge 4|Band 8A - Vegetation red edge 4 - 20m|864.5|19.0|8|0.0001|
298
+ |B09|Water vapor|Band 9 - Water vapor - 60m|945.0|18.0|9|0.0001|
299
+ |B11|SWIR 1|Band 11 - Shortwave infrared 1 - 20m|1613.5|89.0|10|0.0001|
300
+ |B12|SWIR 2|Band 12 - Shortwave infrared 2 - 20m|2199.5|173.0|11|0.0001|
301
+ |AOT|-|Aerosol Optical Thickness|-|-|12|0.001|
302
+ |WVP|-|Water Vapor Pressure. The height the water would occupy if the vapor were condensed into liquid and spread evenly across the column|-|-|13|0.001|
303
+
304
+ - `target`
305
+
306
+ |**Name**|**Common Name**|**Description**|**Center Wavelength**|**Full Width Half Max**|**Index**|**Scale Factor**|
307
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
308
+ |B01|Cloud Label|Cloud labels annotated by humans|-|-|0|1|
309
+
310
+ ### `cloudsen12-2a`
311
+
312
+ A sample has:
313
+
314
+ - elevation
315
+
316
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
317
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
318
+ |B01|elevetion| Elevation data (meters) sourced from the Copernicus DEM GLO-30. |-|-|0|1|
319
+
320
+ - lc10
321
+
322
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
323
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
324
+ |lc10|landcover| ESA WorldCover 10m v100 land cover product. |-|-|0|1|
325
+
326
+ - **VV**
327
+
328
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
329
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
330
+ |VV|Vertical-Vertical Polarization|Normalized Sentinel-1 Global Backscatter Model (VV polarization).|-|-|0|0.1|
331
+
332
+ - **VH**
333
+
334
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
335
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
336
+ |VH|Vertical-Horizontal Polarization|Normalized Sentinel-1 Global Backscatter Model (VH polarization).|-|-|0|0.1|
337
+
338
+
339
+ - **Cloud Mask: QA60**
340
+
341
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
342
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
343
+ |CloudMask_QA60|QA60|Cloud mask from Sentinel-2 Level-1C.|-|-|0|N/A|
344
+
345
+ - **Cloud Mask: Sen2Cor**
346
+
347
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
348
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
349
+ |CloudMask_Sen2Cor|Sen2Cor|Cloud mask from Sentinel-2 Level-2A.|-|-|0|N/A|
350
+
351
+ - **Cloud Mask: S2Cloudless**
352
+
353
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
354
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
355
+ |CloudMask_S2Cloudless|S2Cloudless|Cloud mask generated by Sentinel Hub Cloud Detector.|-|-|0|N/A|
356
+
357
+ - **Cloud Mask: CloudScore CD v1**
358
+
359
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
360
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
361
+ |CloudMask_CloudScore_CS_v1|CloudScore v1|Cloud mask generated by [Pasquarella et al. 2023](https://openaccess.thecvf.com/content/CVPR2023W/EarthVision/html/Pasquarella_Comprehensive_Quality_Assessment_of_Optical_Satellite_Imagery_Using_Weakly_Supervised_CVPRW_2023_paper.html) (v1).|-|-|0|N/A|
362
+
363
+ - **Cloud Mask: CloudScore CDF v1**
364
+
365
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
366
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
367
+ |CloudMask_CloudScore_CS_CDF_v1|CloudScore CDF v1|Cloud mask generated by [Pasquarella et al. 2023](https://openaccess.thecvf.com/content/CVPR2023W/EarthVision/html/Pasquarella_Comprehensive_Quality_Assessment_of_Optical_Satellite_Imagery_Using_Weakly_Supervised_CVPRW_2023_paper.html) (CDF v1).|-|-|0|N/A|
368
+
369
+ - **Cloud Mask: UNetMobV2 v1**
370
+
371
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
372
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
373
+ |CloudMask_UNetMobV2_v1|UNetMobV2 v1|Cloud mask generated by [Aybar et al. 2022](https://www.nature.com/articles/s41597-022-01878-2).|-|-|0|N/A|
374
+
375
+ - **Cloud Mask: UNetMobV2 v2**
376
+
377
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
378
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
379
+ |CloudMask_UNetMobV2_v2|UNetMobV2 v2|Cloud mask generated by [Aybar et al. 2024](https://www.sciencedirect.com/science/article/pii/S2352340924008163).|-|-|0|N/A|
380
+
381
+ - **Cloud Mask: Sensei v2**
382
 
383
+ |**Band**|**Name**|**Description**|**Center Wavelength** (nm)|**Bandwidth** (nm)|**Index**|**Scale Factor**|
384
+ | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
385
+ |CloudMask_Sensei_v2|Sensei v2|Cloud mask generated by [Alistair Francis 2024](https://ieeexplore.ieee.org/document/10505181).|-|-|0|N/A|