Uma versão mais recente desse conjunto de dados com quatro classes para 2017 a 2020 pode ser encontrada em
JAXA/ALOS/PALSAR/YEARLY/FNF4
O mapa global de floresta/não floresta (FNF) é gerado classificando a imagem SAR (coeficiente de retroespalhamento) no mosaico global de 25 m de resolução PALSAR-2/PALSAR SAR para que pixels de retroespalhamento forte e baixo sejam atribuídos como "floresta" e "não floresta", respectivamente. Aqui, "floresta" é definida como a floresta natural com área maior que 0,5 ha e cobertura florestal acima de 10%. Essa definição é a mesma da Organização das Nações Unidas para Alimentação e Agricultura (FAO). Como o radar de retroespalhamento da floresta depende da região (zona climática), a classificação de floresta/não floresta é feita usando um limite de retroespalhamento dependente da região. A acurácia da classificação é verificada usando fotos in situ e imagens de satélite ópticas de alta resolução. Informações detalhadas estão disponíveis na descrição do conjunto de dados do provedor.
Atenção:
Os valores de retroespalhamento podem variar significativamente de um caminho para outro em áreas florestais de alta latitude. Isso ocorre devido à mudança na intensidade de retroespalhamento causada pelo congelamento das árvores no inverno.
Isso pode afetar a classificação de floresta/não floresta.
Bandas
Tamanho do pixel 25 metros
Bandas
Nome
Mín.
Máx.
Tamanho do pixel
Descrição
fnf
1
3
metros
Classificação de cobertura de terra florestal/não florestal
Tabela de classes fnf
Valor
Cor
Descrição
1
#006400
Floresta
2
#feff99
Não floresta
3
#0000ff
Água
Termos de Uso
Termos de Uso
A JAXA mantém a propriedade do conjunto de dados e não garante nenhum problema causado ou possivelmente causado pelo uso dos conjuntos de dados.
Qualquer pessoa que queira publicar resultados usando os conjuntos de dados precisa reconhecer claramente a propriedade dos dados na publicação.
Citações
Citações:
Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Shiraishi Tomohiro, Rajesh Thapa e Richard Lucas, "New Global Forest/Non-forest Maps from ALOS PALSAR Data (2007-2010)", Remote Sensing of Environment, 155, pp. 13-31, dezembro de 2014. doi:10.1016/j.rse.2014.04.014.
Uma versão mais recente desse conjunto de dados com quatro classes para 2017 a 2020 pode ser encontrada em JAXA/ALOS/PALSAR/YEARLY/FNF4. O mapa global de floresta/não floresta (FNF) é gerado classificando a imagem SAR (coeficiente de retroespalhamento) no mosaico global de 25 m de resolução PALSAR-2/PALSAR SAR para que pixels de retroespalhamento forte e baixo sejam atribuídos como "floresta" e …
[null,null,[],[[["\u003cp\u003eThe JAXA/ALOS/PALSAR/YEARLY/FNF dataset provides a global forest/non-forest map at 25-meter resolution, classifying areas as forest, non-forest, or water based on SAR backscatter data.\u003c/p\u003e\n"],["\u003cp\u003eThis dataset covers the period from 2007 to 2018 and utilizes a region-dependent threshold for classification to account for variations in radar backscatter across different climate zones.\u003c/p\u003e\n"],["\u003cp\u003eUsers should be aware that backscatter values might differ significantly in high-latitude forest areas due to seasonal changes, potentially affecting the classification accuracy.\u003c/p\u003e\n"],["\u003cp\u003eA newer version of the dataset, JAXA/ALOS/PALSAR/YEARLY/FNF4, offers an updated classification with four classes for the years 2017-2020.\u003c/p\u003e\n"],["\u003cp\u003eJAXA retains ownership of the dataset, and users are required to acknowledge the data source when publishing any results derived from it.\u003c/p\u003e\n"]]],["The JAXA EORC provides a global forest/non-forest (FNF) map dataset from 2007 to 2018. This dataset uses 25m resolution PALSAR-2/PALSAR SAR mosaic images, classifying pixels based on backscatter strength into \"forest,\" \"non-forest,\" and \"water.\" Forest is defined as natural forest with an area over 0.5 ha and cover exceeding 10%. The dataset is accessible via Google Earth Engine using the provided snippet and is classified with an accuracy determined through in-situ and high-resolution optical images.\n"],null,["# Global 3-class PALSAR-2/PALSAR Forest/Non-Forest Map\n\nDataset Availability\n: 2007-01-01T00:00:00Z--2018-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [JAXA EORC](https://www.eorc.jaxa.jp/ALOS/en/dataset/fnf_e.htm)\n\nTags\n:\n[alos](/earth-engine/datasets/tags/alos) [alos2](/earth-engine/datasets/tags/alos2) [classification](/earth-engine/datasets/tags/classification) [eroc](/earth-engine/datasets/tags/eroc) [forest](/earth-engine/datasets/tags/forest) [forest-biomass](/earth-engine/datasets/tags/forest-biomass) [jaxa](/earth-engine/datasets/tags/jaxa) [landcover](/earth-engine/datasets/tags/landcover) [palsar](/earth-engine/datasets/tags/palsar) [palsar2](/earth-engine/datasets/tags/palsar2) [sar](/earth-engine/datasets/tags/sar) \n\n#### Description\n\nA newer version of this dataset with 4 classes for 2017-2020 can be found in\n[JAXA/ALOS/PALSAR/YEARLY/FNF4](/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF4)\n\nThe global forest/non-forest map (FNF) is generated by\nclassifying the SAR image (backscattering coefficient) in the\nglobal 25m resolution PALSAR-2/PALSAR SAR mosaic so that strong and\nlow backscatter pixels are assigned as \"forest\" and \"non-forest\",\nrespectively. Here, \"forest\" is defined as the natural forest\nwith the area larger than 0.5 ha and forest cover over 10%. This\ndefinition is the same as the Food and Agriculture Organization\n(FAO) definition. Since the radar backscatter from the forest\ndepends on the region (climate zone), the classification of\nForest/Non-Forest is conducted by using a region-dependent\nthreshold of backscatter. The classification accuracy is\nchecked by using in-situ photos and high-resolution optical\nsatellite images. Detailed information is available in the provider's\n[Dataset Description](https://www.eorc.jaxa.jp/ALOS/en/palsar_fnf/DatasetDescription_PALSAR2_Mosaic_FNF_revE.pdf).\n\nAttention:\n\n- Backscatter values may vary significantly from path to path over high latitude forest areas. This is due to the change of backscattering intensity caused by freezing trees in winter. Please note that this may affect the classification of forest/non-forest.\n\n### Bands\n\n\n**Pixel Size**\n\n25 meters\n\n**Bands**\n\n| Name | Min | Max | Pixel Size | Description |\n|-------|-----|-----|------------|--------------------------------------------|\n| `fnf` | 1 | 3 | meters | Forest/Non-Forest landcover classification |\n\n**fnf Class Table**\n\n| Value | Color | Description |\n|-------|---------|-------------|\n| 1 | #006400 | Forest |\n| 2 | #feff99 | Non-Forest |\n| 3 | #0000ff | Water |\n\n### Terms of Use\n\n**Terms of Use**\n\nJAXA retains ownership of the dataset and cannot guarantee\nany problem caused by or possibly caused by using the datasets.\nAnyone wishing to publish any results using the datasets should\nclearly acknowledge the ownership of the data in the publication.\n\n### Citations\n\nCitations:\n\n- Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe,\n Shiraishi Tomohiro, Rajesh Thapa, and Richard Lucas, \"New Global\n Forest/Non-forest Maps from ALOS PALSAR Data (2007-2010)\", Remote Sensing\n of Environment, 155, pp. 13-31, December 2014.\n [doi:10.1016/j.rse.2014.04.014.](https://doi.org/10.1016/j.rse.2014.04.014)\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 dataset = ee.ImageCollection('JAXA/ALOS/PALSAR/YEARLY/FNF')\n .filterDate('2017-01-01', '2017-12-31');\nvar forestNonForest = dataset.select('fnf');\nvar forestNonForestVis = {\n min: 1,\n max: 3,\n palette: ['006400', 'feff99', '0000ff'],\n};\nMap.setCenter(136.85, 37.37, 4);\nMap.addLayer(forestNonForest, forestNonForestVis, 'Forest/Non-Forest');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JAXA/JAXA_ALOS_PALSAR_YEARLY_FNF) \n[Global 3-class PALSAR-2/PALSAR Forest/Non-Forest Map](/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF) \nA newer version of this dataset with 4 classes for 2017-2020 can be found in JAXA/ALOS/PALSAR/YEARLY/FNF4 The global forest/non-forest map (FNF) is generated by classifying the SAR image (backscattering coefficient) in the global 25m resolution PALSAR-2/PALSAR SAR mosaic so that strong and low backscatter pixels are assigned as \"forest\" and ... \nJAXA/ALOS/PALSAR/YEARLY/FNF, alos,alos2,classification,eroc,forest,forest-biomass,jaxa,landcover,palsar,palsar2,sar \n2007-01-01T00:00:00Z/2018-01-01T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://www.eorc.jaxa.jp/ALOS/en/dataset/fnf_e.htm)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_FNF)"]]
