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Global Mangrove Forests Distribution, v1 (2000)
Die Datenbank wurde mit Landsat-Satellitendaten aus dem Jahr 2000 erstellt. Mehr als 1.000 Landsat-Szenen, die vom USGS Earth Resources Observation and Science Center (EROS) stammen, wurden mithilfe von hybriden überwachten und unüberwachten Techniken zur digitalen Bildklassifizierung klassifiziert. Diese Datenbank ist die erste und … jährlich ciesin Waldbiomasse global aus Landsat-Daten Mangroven -
JRC Yearly Water Classification History, v1.4
Dieser Datensatz enthält Karten der Lage und zeitlichen Verteilung von Oberflächenwasser von 1984 bis 2021 sowie Statistiken zur Ausdehnung und Veränderung dieser Wasserflächen. Weitere Informationen finden Sie im zugehörigen Zeitschriftenartikel: High-resolution mapping of global surface water and its … jährliche geophysikalische Google Verlaufsdaten JRC aus Landsat-Daten abgeleitete -
MOD44B.061 Terra Vegetation Continuous Fields Yearly Global 250m
Das Terra MODIS-Produkt „Vegetation Continuous Fields“ (VCF) ist eine Darstellung der geschätzten globalen Vegetationsbedeckung auf Subpixelebene. Diese Karte stellt die Landoberfläche der Erde als Anteil an den grundlegenden Vegetationsmerkmalen dar und bietet eine Abstufung von drei Komponenten der Bodenbedeckung: Prozentsatz der Baumbedeckung, Prozentsatz der … jährlich geophysikalische global Landnutzung und ‑bedeckung modis nasa -
Open Buildings Temporal V1
Der 2,5D-Zeitreihendatensatz von Open Buildings enthält Daten zur Gebäudepräsenz, zur Anzahl der Gebäudeanteile und zur Gebäudehöhe mit einer effektiven1 räumlichen Auflösung von 4 m (Raster werden mit einer Auflösung von 0,5 m bereitgestellt) in jährlicher Taktung von 2016 bis 2023. Sie werden aus Open-Source-Bildern mit niedriger Auflösung von … africa annual asia built-up height open-buildings -
Satelliten-Embedding V1
Der Google Satellite Embedding-Dataset ist eine globale, analysebereite Sammlung von gelernten raumbezogenen Einbettungen. Jedes 10-Meter-Pixel in diesem Datensatz ist eine 64-dimensionale Darstellung oder ein „Embedding-Vektor“, der die zeitlichen Pfade der Oberflächenbedingungen an und um dieses Pixel herum codiert, wie sie von verschiedenen Erdbeobachtungssatelliten gemessen wurden. jährlich global Google Landsat-abgeleitet Satellitenbilder Sentinel-1-abgeleitet -
VIIRS-Tages-/Nachtband-Jahreszusammensetzungen (Tag/Nacht) – Version 2.1
Der jährliche globale VIIRS-Datensatz zu nächtlichen Lichtern ist eine Zeitreihe, die aus monatlichen wolkenfreien durchschnittlichen Rastern der Leuchtkraft von 2013 bis 2021 erstellt wurde. Daten für 2022 sind im Datensatz „NOAA/VIIRS/DNB/ANNUAL_V22“ verfügbar. In einem ersten Filterschritt wurden belichtete, beleuchtete und bewölkte Pixel entfernt, was zu groben Kompositionen führte, die … jährlich dnb eog lights nighttime noaa -
VIIRS-Tages-/Nachtband-Jahreszusammensetzungen (Tag/Nacht) – Version 2.2
Der jährliche globale VIIRS-Datensatz zu nächtlichen Lichtern ist eine Zeitreihe, die aus monatlichen wolkenfreien durchschnittlichen Rastern der Leuchtkraft für 2022 erstellt wurde. Daten für frühere Jahre sind im Datensatz NOAA/VIIRS/DNB/ANNUAL_V21 verfügbar. In einem ersten Filterschritt wurden belichtete, beleuchtete und bewölkte Pixel entfernt, was zu groben Kompositen führte, die … jährlich dnb eog lights nighttime noaa
Datasets tagged annual in Earth Engine
[null,null,[],[[["\u003cp\u003eThe Open Buildings Temporal V1 dataset provides annual data (2016-2023) on building presence, counts, and heights across Africa and Asia.\u003c/p\u003e\n"],["\u003cp\u003eThe JRC Yearly Water Classification History, v1.4 dataset offers annual maps and statistics on global surface water distribution and change from 1984 to 2021.\u003c/p\u003e\n"],["\u003cp\u003eThe Global Mangrove Forests Distribution, v1 (2000) dataset presents a global mangrove forest distribution map derived from Landsat satellite data from the year 2000.\u003c/p\u003e\n"],["\u003cp\u003eThe MOD44B.006 Terra Vegetation Continuous Fields Yearly Global 250m dataset provides yearly global vegetation cover estimates, including tree cover percentages.\u003c/p\u003e\n"],["\u003cp\u003eThe VIIRS Nighttime Day/Night Annual Band Composites V2.1 and V2.2 datasets offer annual global nighttime lights data, with V2.1 spanning 2013 to 2021 and V2.2 covering 2022.\u003c/p\u003e\n"]]],["The datasets provide annual global information on various Earth features. The Open Buildings dataset offers building presence, counts, and heights from 2016-2023. JRC data maps surface water distribution and changes from 1984-2021. Another dataset, based on data from 2000, details mangrove forest distribution. MODIS data provides continuous vegetation cover estimates, including tree cover percentages. Lastly, VIIRS data sets map annual nighttime light composites from 2013-2022, based on cloud-free average radiance grids.\n"],null,["# Datasets tagged annual in Earth Engine\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### Global Mangrove Forests Distribution, v1 (2000)](/earth-engine/datasets/catalog/LANDSAT_MANGROVE_FORESTS) |\n | The database was prepared using Landsat satellite data from the year 2000. More than 1,000 Landsat scenes obtained from the USGS Earth Resources Observation and Science Center (EROS) were classified using hybrid supervised and unsupervised digital image classification techniques. This database is the first, most ... |\n | [annual](/earth-engine/datasets/tags/annual) [ciesin](/earth-engine/datasets/tags/ciesin) [forest-biomass](/earth-engine/datasets/tags/forest-biomass) [global](/earth-engine/datasets/tags/global) [landsat-derived](/earth-engine/datasets/tags/landsat-derived) [mangrove](/earth-engine/datasets/tags/mangrove) |\n\n-\n\n |--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### JRC Yearly Water Classification History, v1.4](/earth-engine/datasets/catalog/JRC_GSW1_4_YearlyHistory) |\n | This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its ... |\n | [annual](/earth-engine/datasets/tags/annual) [geophysical](/earth-engine/datasets/tags/geophysical) [google](/earth-engine/datasets/tags/google) [history](/earth-engine/datasets/tags/history) [jrc](/earth-engine/datasets/tags/jrc) [landsat-derived](/earth-engine/datasets/tags/landsat-derived) |\n\n-\n\n |------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### MOD44B.061 Terra Vegetation Continuous Fields Yearly Global 250m](/earth-engine/datasets/catalog/MODIS_061_MOD44B) |\n | The Terra MODIS Vegetation Continuous Fields (VCF) product is a sub-pixel-level representation of surface vegetation cover estimates globally. Designed to continuously represent Earth's terrestrial surface as a proportion of basic vegetation traits, it provides a gradation of three surface cover components: percent tree cover, percent ... |\n | [annual](/earth-engine/datasets/tags/annual) [geophysical](/earth-engine/datasets/tags/geophysical) [global](/earth-engine/datasets/tags/global) [landuse-landcover](/earth-engine/datasets/tags/landuse-landcover) [modis](/earth-engine/datasets/tags/modis) [nasa](/earth-engine/datasets/tags/nasa) |\n\n-\n\n |--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### Open Buildings Temporal V1](/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings-temporal_v1) |\n | The Open Buildings 2.5D Temporal Dataset contains data about building presence, fractional building counts, and building heights at an effective1 spatial resolution of 4m (rasters are provided at 0.5m resolution) at an annual cadence from 2016-2023. It is produced from open-source, low-resolution imagery from the ... |\n | [africa](/earth-engine/datasets/tags/africa) [annual](/earth-engine/datasets/tags/annual) [asia](/earth-engine/datasets/tags/asia) [built-up](/earth-engine/datasets/tags/built-up) [height](/earth-engine/datasets/tags/height) [open-buildings](/earth-engine/datasets/tags/open-buildings) |\n\n-\n\n |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### Satellite Embedding V1](/earth-engine/datasets/catalog/GOOGLE_SATELLITE_EMBEDDING_V1_ANNUAL) |\n | The Google Satellite Embedding dataset is a global, analysis-ready collection of learned geospatial embeddings. Each 10-meter pixel in this dataset is a 64-dimensional representation, or \"embedding vector,\" that encodes temporal trajectories of surface conditions at and around that pixel as measured by various Earth observation ... |\n | [annual](/earth-engine/datasets/tags/annual) [global](/earth-engine/datasets/tags/global) [google](/earth-engine/datasets/tags/google) [landsat-derived](/earth-engine/datasets/tags/landsat-derived) [satellite-imagery](/earth-engine/datasets/tags/satellite-imagery) [sentinel1-derived](/earth-engine/datasets/tags/sentinel1-derived) |\n\n-\n\n |------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### VIIRS Nighttime Day/Night Annual Band Composites V2.1](/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V21) |\n | Annual global VIIRS nighttime lights dataset is a time series produced from monthly cloud-free average radiance grids spanning 2013 to 2021. Data for 2022 are available in the NOAA/VIIRS/DNB/ANNUAL_V22 dataset. An initial filtering step removed sunlit, moonlit and cloudy pixels, leading to rough composites that ... |\n | [annual](/earth-engine/datasets/tags/annual) [dnb](/earth-engine/datasets/tags/dnb) [eog](/earth-engine/datasets/tags/eog) [lights](/earth-engine/datasets/tags/lights) [nighttime](/earth-engine/datasets/tags/nighttime) [noaa](/earth-engine/datasets/tags/noaa) |\n\n-\n\n |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### VIIRS Nighttime Day/Night Annual Band Composites V2.2](/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V22) |\n | Annual global VIIRS nighttime lights dataset is a time series produced from monthly cloud-free average radiance grids for 2022. Data for earlier years are available in the NOAA/VIIRS/DNB/ANNUAL_V21 dataset. An initial filtering step removed sunlit, moonlit and cloudy pixels, leading to rough composites that contains ... |\n | [annual](/earth-engine/datasets/tags/annual) [dnb](/earth-engine/datasets/tags/dnb) [eog](/earth-engine/datasets/tags/eog) [lights](/earth-engine/datasets/tags/lights) [nighttime](/earth-engine/datasets/tags/nighttime) [noaa](/earth-engine/datasets/tags/noaa) |"]]