Eine neuere Version dieses Datasets mit vier Klassen für 2017–2020 finden Sie unter JAXA/ALOS/PALSAR/YEARLY/FNF4.
Die globale Karte für Wald/Nicht-Wald (Forest/Non-Forest, FNF) wird erstellt, indem das SAR-Bild (Rückstreukoeffizient) im globalen 25‑m-PALSAR-2/PALSAR-SAR-Mosaik klassifiziert wird, sodass Pixel mit starker und schwacher Rückstreuung als „Wald“ bzw. „Nicht-Wald“ zugewiesen werden. Hier wird „Wald“ als natürlicher Wald mit einer Fläche von mehr als 0,5 ha und einer Waldbedeckung von über 10 % definiert. Diese Definition entspricht der Definition der Ernährungs- und Landwirtschaftsorganisation der Vereinten Nationen (FAO). Da die Radar-Rückstreuung des Waldes von der Region (Klimazone) abhängt, erfolgt die Klassifizierung von „Wald“ / „Nicht-Wald“ anhand eines regionsabhängigen Rückstreuungsschwellenwerts. Die Klassifizierungsgenauigkeit wird anhand von In-situ-Fotos und hochauflösenden optischen Satellitenbildern überprüft. Detaillierte Informationen finden Sie in der Beschreibung des Datasets des Anbieters.
Attention:
Die Backscatter-Werte können in Waldgebieten in hohen Breitengraden von Pfad zu Pfad erheblich variieren. Dies ist auf die Änderung der Rückstreuungsintensität zurückzuführen, die durch das Einfrieren von Bäumen im Winter verursacht wird.
Dies kann sich auf die Klassifizierung von Wald/Nicht-Wald auswirken.
Bänder
Pixelgröße 25 Meter
Bänder
Name
Min.
Max.
Pixelgröße
Beschreibung
fnf
1
3
Meter
Klassifizierung der Landbedeckung in Wald/Nicht-Wald
fnf Class Table
Wert
Farbe
Beschreibung
1
#006400
Wald
2
#feff99
Nicht Wald
3
#0000ff
Wasser
Nutzungsbedingungen
Nutzungsbedingungen
JAXA behält das Eigentum am Dataset und kann keine Garantie für Probleme übernehmen, die durch die Verwendung der Datasets verursacht werden oder möglicherweise verursacht werden.
Jeder, der Ergebnisse mit den Datasets veröffentlichen möchte, muss die Inhaberschaft der Daten in der Publikation deutlich angeben.
Zitate
Quellenangaben:
Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Shiraishi Tomohiro, Rajesh Thapa und Richard Lucas, „New Global Forest/Non-forest Maps from ALOS PALSAR Data (2007–2010)“, Remote Sensing of Environment, 155, S. 13–31, Dezember 2014. doi:10.1016/j.rse.2014.04.014.
Eine neuere Version dieses Datasets mit 4 Klassen für 2017–2020 finden Sie unter JAXA/ALOS/PALSAR/YEARLY/FNF4. Die globale Karte für Wald/Nichtwald (Forest/Non-Forest, FNF) wird erstellt, indem das SAR-Bild (Rückstreukoeffizient) im globalen 25‑m-PALSAR-2/PALSAR-SAR-Mosaik klassifiziert wird, sodass Pixel mit starker und schwacher Rückstreuung als „Wald“ bzw. …
[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)"]]
