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Global Mangrove Forests Distribution, v1 (2000)
Veritabanı, 2000 yılına ait Landsat uydu verileri kullanılarak hazırlanmıştır. USGS Earth Resources Observation and Science Center (EROS)'dan elde edilen 1.000'den fazla Landsat görüntüsü,karma gözetimli ve gözetimsiz dijital görüntü sınıflandırma teknikleri kullanılarak sınıflandırıldı. Bu veritabanı, ilk ve en … annual ciesin forest-biomass global landsat-derived mangrove -
JRC Yıllık Su Sınıflandırması Geçmişi, v1.4
Bu veri kümesi, 1984-2021 yılları arasındaki yüzey suyunun konumu ve zamansal dağılımının haritalarını içerir ve bu su yüzeylerinin kapsamı ve değişimi hakkında istatistikler sağlar. Daha fazla bilgi için ilgili dergi makalesine bakın: Global yüzey suyunun ve … annual geophysical google history jrc landsat-derived -
MOD44B.061 Terra Vegetation Continuous Fields Yearly Global 250m
Terra MODIS Bitki Örtüsü Sürekli Alanları (VCF) ürünü, dünya genelindeki yüzey bitki örtüsü tahminlerinin piksel altı düzeyde bir temsilidir. Dünya'nın karasal yüzeyini temel bitki örtüsü özelliklerinin oranı olarak sürekli olarak temsil etmek için tasarlanan bu katman, üç yüzey örtüsü bileşeninin gradasyonunu sağlar: ağaç örtüsü yüzdesi, … annual geophysical global landuse-landcover modis nasa -
Açık Binalar Zamansal V1
Open Buildings 2,5D Zamansal Veri Kümesi, 2016-2023 yılları arasında yıllık olarak 4 m etkili1 mekansal çözünürlükte (rasterler 0,5 m çözünürlükte sağlanır) bina varlığı, kesirli bina sayıları ve bina yükseklikleri hakkında veriler içerir. Bu görüntüler, … africa annual asia built-up height open-buildings -
Uydu Yerleştirme V1
Google Uydu Yerleşimi veri kümesi, öğrenilmiş coğrafi yerleşimlerin analize hazır küresel bir koleksiyonudur. Bu veri kümesindeki her 10 metrelik piksel, çeşitli yer gözlemleri tarafından ölçülen yüzey koşullarının, ilgili pikselde ve çevresindeki zamansal yörüngelerini kodlayan 64 boyutlu bir temsil veya "yerleştirme vektörü"dür. yıllık küresel google landsat'tan türetilmiş uydu görüntüsü sentinel1'den türetilmiş -
VIIRS Gece Gündüz/Gece Yıllık Bant Bileşimleri V2.1
Yıllık küresel VIIRS gece ışıkları veri kümesi, 2013-2021 yılları arasındaki aylık bulutsuz ortalama parlaklık ızgaralarından üretilen bir zaman serisi. 2022'ye ait veriler NOAA/VIIRS/DNB/ANNUAL_V22 veri kümesinde mevcuttur. İlk filtreleme adımında güneş ışığı alan, ay ışığı alan ve bulutlu pikseller kaldırıldı. Bu işlem, … annual dnb eog lights nighttime noaa -
VIIRS Gece Gündüz/Gece Yıllık Bant Bileşimleri V2.2
Yıllık küresel VIIRS gece ışıkları veri kümesi, 2022'ye ait aylık bulutsuz ortalama parlaklık ızgaralarından oluşturulan bir zaman serisi. Önceki yıllara ait veriler NOAA/VIIRS/DNB/ANNUAL_V21 veri kümesinde mevcuttur. İlk filtreleme adımında güneş ışığı alan, ay ışığı alan ve bulutlu pikseller kaldırıldı. Bu işlem, aşağıdakileri içeren kaba kompozisyonlar elde edilmesine yol açtı: annual 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) |"]]