BigEarthNet to nowe, duże archiwum referencyjne Sentinel-2,które zawiera 590 326 fragmentów obrazów Sentinel-2. Do utworzenia zbioru BigEarthNet wykorzystano 125 obrazów Sentinel-2 pozyskanych w okresie od czerwca 2017 r. do maja 2018 r. nad 10 krajami Europy (Austrią, Belgią, Finlandią, Irlandią, Kosowem, Litwą, Luksemburgiem, Portugalią, Serbią i Szwajcarią). Wszystkie kafelki zostały skorygowane atmosferycznie za pomocą narzędzia do generowania i formatowania produktów Sentinel-2 Level 2A (sen2cor). Następnie podzielono je na 590 326 niepokrywających się fragmentów obrazu. Każdy fragment obrazu został oznaczony wieloma klasami pokrycia terenu (czyli wieloma etykietami) pochodzącymi z bazy danych CORINE Land Cover z 2018 roku (CLC 2018).
Pasma
Pasma
Nazwa
Skaluj
Rozmiar piksela
Długość fali
Opis
B1
0,0001
60 metrów
443,9 nm (S2A) / 442,3 nm (S2B)
Aerozole
B2
0,0001
10 metrów
496,6 nm (S2A) / 492,1 nm (S2B)
Niebieski
B3
0,0001
10 metrów
560 nm (S2A) / 559 nm (S2B)
Zielony
B4
0,0001
10 metrów
664,5 nm (S2A) / 665 nm (S2B)
Czerwony
B5
0,0001
20 metrów
703,9 nm (S2A) / 703,8 nm (S2B)
Red Edge 1
B6
0,0001
20 metrów
740,2 nm (S2A) / 739,1 nm (S2B)
Red Edge 2
B7
0,0001
20 metrów
782,5 nm (S2A) / 779,7 nm (S2B)
Red Edge 3
B8
0,0001
10 metrów
835,1 nm (S2A) / 833 nm (S2B)
NIR
B9
0,0001
60 metrów
945 nm (S2A) / 943,2 nm (S2B)
para wodna,
B10
0,0001
60 metrów
1373,5 nm (S2A) / 1376,9 nm (S2B)
Cirrus
B11
0,0001
20 metrów
1613,7 nm (S2A) / 1610,4 nm (S2B)
SWIR 1
B12
0,0001
20 metrów
2202,4 nm (S2A) / 2185,7 nm (S2B)
SWIR 2
B8A
0,0001
20 metrów
864,8 nm (S2A) / 864 nm (S2B)
Red Edge 4
Właściwości obrazu
Właściwości obrazu
Nazwa
Typ
Opis
etykiety
STRING_LIST
Lista typów pokrycia terenu znalezionych na tym obrazie
źródło
CIĄG ZNAKÓW
Identyfikator produktu odpowiadający obrazowi Sentinel-2 1C
tile_x
LICZBA ZMIENNOPRZECINKOWA O PODWÓJNEJ PRECYZJI
Współrzędna X kafelka w obrazie źródłowym
tile_y
LICZBA ZMIENNOPRZECINKOWA O PODWÓJNEJ PRECYZJI
Współrzędna Y kafelka w obrazie źródłowym
Warunki korzystania z usługi
Warunki korzystania z usługi
Archiwum BigEarthNet jest licencjonowane na podstawie umowy Community Data License Agreement – Permissive, wersja 1.0. Więcej informacji znajdziesz na stronie https://cdla.dev/permissive-1-0.
Cytaty
Cytowania:
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, pp. 5901-5904,
Yokohama, Japan, 2019.
BigEarthNet to nowe, duże archiwum referencyjne Sentinel-2,które zawiera 590 326 fragmentów obrazów Sentinel-2. Do utworzenia zbioru BigEarthNet wykorzystano 125 obrazów z satelity Sentinel-2, które zostały pozyskane w okresie od czerwca 2017 r. do maja 2018 r. w 10 krajach Europy (Austrii, Belgii, Finlandii, Irlandii, Kosowie, Litwie, Luksemburgu, Portugalii, Serbii i Szwajcarii). Wszystkie kafelki zostały skorygowane pod kątem warunków atmosferycznych…
[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)"]]
