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Global Mangrove Forests Distribution, v1 (2000)
Baza danych została przygotowana na podstawie danych satelitarnych Landsat z roku 2000. Ponad 1000 scen Landsat uzyskanych z USGS Earth Resources Observation and Science Center (EROS) zostało sklasyfikowanych za pomocą hybrydowych technik klasyfikacji obrazów cyfrowych z nadzorem i bez nadzoru. Ta baza danych jest pierwszą, najbardziej … annual ciesin forest-biomass global landsat-derived mangrove -
JRC Yearly Water Classification History, v1.4
Ten zbiór danych zawiera mapy lokalizacji i rozkładu czasowego powierzchni wody w latach 1984–2021 oraz statystyki dotyczące rozległości i zmian tych powierzchni. Więcej informacji znajdziesz w powiązanym artykule w czasopiśmie: High-resolution mapping of global surface water and its … annual geophysical google history jrc landsat-derived -
MOD44B.061 Terra Vegetation Continuous Fields Yearly Global 250m
Produkt Terra MODIS Vegetation Continuous Fields (VCF) to reprezentacja na poziomie poniżej piksela szacunków pokrycia powierzchni roślinnością na całym świecie. Ta mapa została zaprojektowana tak, aby ciągle przedstawiać powierzchnię lądową Ziemi jako proporcję podstawowych cech roślinności. Zawiera ona 3 elementy pokrycia powierzchni: odsetek pokrycia przez drzewa, odsetek … annual geophysical global landuse-landcover modis nasa -
Open Buildings Temporal V1
Czasowy zbiór danych Open Buildings 2.5D zawiera dane o obecności budynków, ich liczbie i wysokości w ramach efektywnej1 rozdzielczości przestrzennej 4 m (rastery są dostarczane z rozdzielczości 0, 5 m) w cyklu rocznym w latach 2016–2023. Jest ona tworzona na podstawie obrazów o niskiej rozdzielczości i dostępnych na licencji open source z … africa annual asia built-up height open-buildings -
Wstawianie satelity V1
Zbiór danych Google Satellite Embedding to globalna kolekcja gotowych do analizy zaimplementowanych w sieci neuronowej uogólnionych wektorów przedstawiających dane geoprzestrzenne. Każdy 10-metrowy piksel w tym zbiorze danych to 64-wymiarowa reprezentacja, czyli „wektor wbudowany”, który koduje czasowe trajektorie warunków na powierzchni w danym pikselu i wokół niego, zmierzone przez różne systemy obserwacji Ziemi … roczne globalne google na podstawie danych z Landsat obrazy satelitarne na podstawie danych z Sentinel-1 -
VIIRS Annual Day/Night Composites V2.1
Roczny globalny zbiór danych VIIRS o światłach nocnych to seria czasowa utworzona na podstawie miesięcznych siatek średniej jasności bez chmur z lat 2013–2021. Dane za 2022 r. są dostępne w zbiorze danych NOAA/VIIRS/DNB/ANNUAL_V22. W pierwszym kroku filtrowania usunięto piksele z oświetleniem słonecznym, księżycowym i chmurnym, co doprowadziło do powstania przybliżonych kompozycji, które … roczne dnb eog lights noc noaa -
VIIRS Annual Band Composites V2.2 Day/Night
Roczny globalny zbiór danych o nocnych światłach z VIIRS to seria czasowa utworzona na podstawie miesięcznych siatek średniego natężenia promieniowania bez chmur w 2022 roku. Dane z wcześniejszych lat są dostępne w zbiorze danych NOAA/VIIRS/DNB/ANNUAL_V21. W pierwszym kroku filtrowania usunięto piksele oświetlone przez słońce, księżyc i chmury, co doprowadziło do powstania przybliżonych kompozycji zawierających … roczne dnb eog lights noc 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) |"]]