Una versione più recente di questo set di dati con 4 classi per il periodo 2017-2020 è disponibile in
JAXA/ALOS/PALSAR/YEARLY/FNF4
La mappa globale foresta/non foresta (FNF) viene generata
classificando l'immagine SAR (coefficiente di retrodiffusione) nel
mosaico SAR PALSAR-2/PALSAR globale con risoluzione di 25 m in modo che i pixel di retrodiffusione forte e
bassa vengano assegnati rispettivamente come "foresta" e "non foresta". In questo caso, per "foresta" si intende la foresta naturale
con una superficie superiore a 0,5 ettari e una copertura forestale superiore al 10%. Questa
definizione è uguale a quella dell'Organizzazione delle Nazioni Unite per l'alimentazione e l'agricoltura
(FAO). Poiché il backscatter radar della foresta
dipende dalla regione (zona climatica), la classificazione di
foresta/non foresta viene eseguita utilizzando una soglia di backscatter
dipendente dalla regione. L'accuratezza della classificazione viene
controllata utilizzando foto in situ e immagini satellitari
ottiche ad alta risoluzione. Informazioni dettagliate sono disponibili nella
Descrizione del set di dati del fornitore.
Attenzione:
I valori di backscatter possono variare notevolmente da un percorso all'altro
nelle aree forestali ad alta latitudine. Ciò è dovuto alla variazione
dell'intensità di retrodiffusione causata dal congelamento degli alberi in inverno.
Tieni presente che ciò potrebbe influire sulla classificazione di
foreste/non foreste.
Bande
Dimensioni pixel 25 metri
Bande
Nome
Min
Max
Dimensioni dei pixel
Descrizione
fnf
1
3
metri
Classificazione della copertura del suolo forestale/non forestale
fnf Class Table
Valore
Colore
Descrizione
1
#006400
Foresta
2
#feff99
Non foresta
3
#0000ff
Acqua
Termini e condizioni d'uso
Termini e condizioni d'uso
JAXA mantiene la proprietà del set di dati e non può garantire
alcun problema causato o possibilmente causato dall'utilizzo dei set di dati.
Chiunque desideri pubblicare risultati utilizzando i set di dati deve
riconoscere chiaramente la proprietà dei dati nella pubblicazione.
Citazioni
Citazioni:
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, dicembre 2014.
doi:10.1016/j.rse.2014.04.014.
Una versione più recente di questo set di dati con 4 classi per il periodo 2017-2020 è disponibile in JAXA/ALOS/PALSAR/YEARLY/FNF4. La mappa globale foresta/non foresta (FNF) viene generata classificando l'immagine SAR (coefficiente di retrodiffusione) nel mosaico SAR PALSAR-2/PALSAR con risoluzione globale di 25 m in modo che i pixel con retrodiffusione forte e bassa vengano assegnati come "foresta" 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)"]]
