BigEarthNet ist ein neues, umfangreiches Sentinel-2-Benchmark-Archiv,das aus 590.326 Sentinel-2-Bildausschnitten besteht. Für BigEarthNet wurden zwischen Juni 2017 und Mai 2018 125 Sentinel-2-Kacheln über den 10 Ländern (Deutschland, Österreich, Belgien, Finnland, Irland, Kosovo, Litauen, Luxemburg, Portugal, Serbien, Schweiz) Europas erfasst. Alle Kacheln wurden mit dem Tool zur Erstellung und Formatierung von Sentinel-2-Produkten der Stufe 2A (sen2cor) atmosphärisch korrigiert. Anschließend wurden sie in 590.326 nicht überlappende Bildausschnitte unterteilt. Jeder Bildausschnitt wurde mit den verschiedenen Landbedeckungsklassen (d.h. mit mehreren Labels) versehen, die aus der CORINE Land Cover-Datenbank von 2018 (CLC 2018) stammen.
Bänder
Bänder
Name
Skalieren
Pixelgröße
Wellenlänge
Beschreibung
B1
0.0001
60 Meter
443,9 nm (S2A) / 442,3 nm (S2B)
Aerosole
B2
0.0001
10 Meter
496,6 nm (S2A) / 492,1 nm (S2B)
Blau
B3
0.0001
10 Meter
560 nm (S2A) / 559 nm (S2B)
Grün
B4
0.0001
10 Meter
664,5 nm (S2A) / 665 nm (S2B)
Rot
B5
0.0001
20 Meter
703,9 nm (S2A) / 703,8 nm (S2B)
Roter Rand 1
B6
0.0001
20 Meter
740,2 nm (S2A) / 739,1 nm (S2B)
Red Edge 2
B7
0.0001
20 Meter
782,5 nm (S2A) / 779,7 nm (S2B)
Red Edge 3
B8
0.0001
10 Meter
835,1 nm (S2A) / 833 nm (S2B)
NIR
B9
0.0001
60 Meter
945 nm (S2A) / 943,2 nm (S2B)
Wasserdampf
B10
0.0001
60 Meter
1373,5 nm (S2A) / 1376,9 nm (S2B)
Zirrus
B11
0.0001
20 Meter
1613,7 nm (S2A) / 1610,4 nm (S2B)
SWIR 1
B12
0.0001
20 Meter
2202,4 nm (S2A) / 2185,7 nm (S2B)
SWIR 2
B8A
0.0001
20 Meter
864,8 nm (S2A) / 864 nm (S2B)
Red Edge 4
Bildattribute
Bildattribute
Name
Typ
Beschreibung
Labels
STRING_LIST
Liste der in diesem Bild enthaltenen Landbedeckungstypen
source
STRING
Produkt-ID des entsprechenden Sentinel-2-Bilds vom Typ 1C
tile_x
DOUBLE
X-Koordinate der Kachel im Quellbild
tile_y
DOUBLE
Y-Koordinate der Kachel im Quellbild
Nutzungsbedingungen
Nutzungsbedingungen
Das BigEarthNet-Archiv ist unter der Community Data License Agreement – Permissive, Version 1.0 lizenziert. Weitere Informationen finden Sie unter https://cdla.dev/permissive-1-0.
Zitate
Quellenangaben:
G. Sumbul, M. Charfuelan, B. Demir, V. Markl, BigEarthNet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding, IEEE International Conference on Geoscience and Remote Sensing Symposium, S. 5901–5904, Yokohama, Japan, 2019.
BigEarthNet ist ein neues, umfangreiches Sentinel-2-Benchmark-Archiv mit 590.326 Sentinel-2-Bildausschnitten. Für BigEarthNet wurden zwischen Juni 2017 und Mai 2018 125 Sentinel-2-Kacheln über den 10 Ländern Europas (Österreich, Belgien, Finnland, Irland, Kosovo, Litauen, Luxemburg, Portugal, Serbien, Schweiz) erfasst. Alle Kacheln wurden atmosphärisch korrigiert …
[null,null,[],[[["\u003cp\u003eBigEarthNet is a large-scale Sentinel-2 benchmark archive containing 590,326 image patches acquired between June 2017 and May 2018.\u003c/p\u003e\n"],["\u003cp\u003eIt covers 10 European countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) and is based on 125 Sentinel-2 tiles.\u003c/p\u003e\n"],["\u003cp\u003eEach image patch is annotated with multiple land-cover classes from the CORINE Land Cover database of 2018 (CLC 2018).\u003c/p\u003e\n"],["\u003cp\u003eBigEarthNet provides Sentinel-2 Level 2A product image patches, atmospherically corrected by sen2cor.\u003c/p\u003e\n"],["\u003cp\u003eThe archive is licensed under the Community Data License Agreement - Permissive, Version 1.0.\u003c/p\u003e\n"]]],[],null,["# TUBerlin/BigEarthNet/v1\n\nDataset Availability\n: 2017-06-01T00:00:00Z--2018-05-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [BigEarthNet](http://bigearth.net/)\n\nTags\n:\n [copernicus](/earth-engine/datasets/tags/copernicus) [landuse-landcover](/earth-engine/datasets/tags/landuse-landcover) [sentinel](/earth-engine/datasets/tags/sentinel) \n chip \n corine-derived \n label \n ml \ntile \n\n#### Description\n\nBigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of\n590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2\ntiles were acquired between June 2017 and May 2018 over the 10 countries\n(Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg,\nPortugal, Serbia, Switzerland) of Europe. All the tiles were atmospherically\ncorrected by the Sentinel-2 Level 2A product generation and formatting tool\n(sen2cor). Then, they were divided into 590,326 non-overlapping image\npatches. Each image patch was annotated by the multiple land-cover classes\n(i.e., multi-labels) that were provided from the CORINE Land Cover database\nof the year 2018 (CLC 2018).\n\n### Bands\n\n**Bands**\n\n| Name | Scale | Pixel Size | Wavelength | Description |\n|-------|--------|------------|---------------------------------|-------------|\n| `B1` | 0.0001 | 60 meters | 443.9nm (S2A) / 442.3nm (S2B) | Aerosols |\n| `B2` | 0.0001 | 10 meters | 496.6nm (S2A) / 492.1nm (S2B) | Blue |\n| `B3` | 0.0001 | 10 meters | 560nm (S2A) / 559nm (S2B) | Green |\n| `B4` | 0.0001 | 10 meters | 664.5nm (S2A) / 665nm (S2B) | Red |\n| `B5` | 0.0001 | 20 meters | 703.9nm (S2A) / 703.8nm (S2B) | Red Edge 1 |\n| `B6` | 0.0001 | 20 meters | 740.2nm (S2A) / 739.1nm (S2B) | Red Edge 2 |\n| `B7` | 0.0001 | 20 meters | 782.5nm (S2A) / 779.7nm (S2B) | Red Edge 3 |\n| `B8` | 0.0001 | 10 meters | 835.1nm (S2A) / 833nm (S2B) | NIR |\n| `B9` | 0.0001 | 60 meters | 945nm (S2A) / 943.2nm (S2B) | Water vapor |\n| `B10` | 0.0001 | 60 meters | 1373.5nm (S2A) / 1376.9nm (S2B) | Cirrus |\n| `B11` | 0.0001 | 20 meters | 1613.7nm (S2A) / 1610.4nm (S2B) | SWIR 1 |\n| `B12` | 0.0001 | 20 meters | 2202.4nm (S2A) / 2185.7nm (S2B) | SWIR 2 |\n| `B8A` | 0.0001 | 20 meters | 864.8nm (S2A) / 864nm (S2B) | Red Edge 4 |\n\n### Image Properties\n\n**Image Properties**\n\n| Name | Type | Description |\n|--------|-------------|-----------------------------------------------------|\n| labels | STRING_LIST | List of landcover types found in this image |\n| source | STRING | Product ID of the corresponding Sentinel-2 1C image |\n| tile_x | DOUBLE | X coordinate of tile in source image |\n| tile_y | DOUBLE | Y coordinate of tile in source image |\n\n### Terms of Use\n\n**Terms of Use**\n\nThe BigEarthNet Archive is licensed under the Community Data License\nAgreement - Permissive, Version 1.0. For more information,\nplease refer to\n[https://cdla.dev/permissive-1-0](https://cdla.dev/permissive-1-0/).\n\n### Citations\n\nCitations:\n\n- G. Sumbul, M. Charfuelan, B. Demir, V. Markl, BigEarthNet: A Large-Scale\n Benchmark Archive for Remote Sensing Image Understanding, IEEE International\n Conference on Geoscience and Remote Sensing Symposium, pp. 5901-5904,\n Yokohama, Japan, 2019.\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar geometry = ee.Geometry.Polygon(\n [[\n [16.656886757418057, 48.27086673747943],\n [16.656886757418057, 48.21359065567954],\n [16.733276070162198, 48.21359065567954],\n [16.733276070162198, 48.27086673747943]]]);\n\nvar ic = ee.ImageCollection('TUBerlin/BigEarthNet/v1');\n\nvar filtered = ic.filterBounds(geometry);\n\nvar tiles = filtered.map(function(image) {\n var labels = ee.List(image.get('labels'));\n\n var urban = labels.indexOf('Discontinuous urban fabric').gte(0);\n var highlight_urban = ee.Image(urban).toInt().multiply(1000);\n\n return image.addBands(\n {srcImg: image.select(['B4']).add(highlight_urban), overwrite: true});\n});\n\nvar image = tiles.mosaic().clip(geometry);\n\nvar visParams = {bands: ['B4', 'B3', 'B2'], min: 0, max: 3000};\n\nMap.addLayer(image, visParams);\nMap.centerObject(image, 13);\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/TUBerlin/TUBerlin_BigEarthNet_v1) \n[TUBerlin/BigEarthNet/v1](/earth-engine/datasets/catalog/TUBerlin_BigEarthNet_v1) \nBigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of 590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2 tiles were acquired between June 2017 and May 2018 over the 10 countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) of Europe. All the tiles were atmospherically corrected ... \nTUBerlin/BigEarthNet/v1, copernicus,landuse-landcover,sentinel \n2017-06-01T00:00:00Z/2018-05-31T00:00:00Z \n36.9 -9 68.1 31.6 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/http://bigearth.net/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/TUBerlin_BigEarthNet_v1)"]]
