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전 세계 맹그로브 숲 분포, v1 (2000)
이 데이터베이스는 2000년의 Landsat 위성 데이터를 사용하여 준비되었습니다. USGS Earth Resources Observation and Science Center (EROS)에서 얻은 1,000개가 넘는 Landsat 장면을 하이브리드 지도 및 비지도 디지털 이미지 분류 기술을 사용하여 분류했습니다. 이 데이터베이스는 최초의 가장 … annual ciesin forest-biomass global landsat-derived mangrove -
JRC 연간 수질 분류 내역, v1.4
이 데이터 세트에는 1984년부터 2021년까지의 지상수의 위치 및 시간적 분포 지도와 이러한 수면의 범위 및 변화에 관한 통계가 포함되어 있습니다. 자세한 내용은 관련 저널 논문인 '전 세계의 표면수 및 그 변화에 관한 고해상도 매핑'을 참고하세요. 연간 지구물리학 google 기록 jrc landsat-derived -
MOD44B.061 Terra Vegetation Continuous Fields Yearly Global 250m
Terra MODIS Vegetation Continuous Fields (VCF) 제품은 전 세계 표면 식생 덮음 추정치를 하위 픽셀 수준으로 나타낸 것입니다. 지구의 육상 표면을 기본적인 식생 특성의 비율로 연속적으로 나타내도록 설계되었으며, 나무 덮음 비율, 숲 덮음 비율, 잔디 덮음 비율 등 세 가지 표면 피복 구성요소의 그라데이션을 제공합니다. 연간 지구물리학 전 세계 landuse-landcover modis nasa -
Open Buildings Temporal V1
Open Buildings 2.5D 시계열 데이터 세트는 2016~2023년의 연간 주기로 유효한1 공간 해상도 4m (래스터는 0.5m 해상도로 제공됨)에서 건물 존재, 비율적 건물 수, 건물 높이에 관한 데이터를 포함합니다. 이 지도의 데이터는 … africa annual asia built-up height open-buildings -
위성 삽입 V1
Google 위성 임베딩 데이터 세트는 학습된 지리적 임베딩의 글로벌 컬렉션으로, 분석에 바로 사용할 수 있습니다. 이 데이터 세트의 각 10미터 픽셀은 다양한 지구 관측으로 측정된 해당 픽셀 및 주변의 표면 상태의 시간적 궤적을 인코딩하는 64차원 표현 또는 '임베딩 벡터'입니다. 연간 전 세계 Google Landsat 파생 위성 이미지 Sentinel-1 파생 -
VIIRS 야간 일/야간 연간 밴드 합성물 V2.1
연간 전 세계 VIIRS 야간 조명 데이터 세트는 2013년부터 2021년까지의 월별 구름 없는 평균 방사광도 그리드에서 생성된 시계열입니다. 2022년 데이터는 NOAA/VIIRS/DNB/ANNUAL_V22 데이터 세트에서 확인할 수 있습니다. 초기 필터링 단계에서 햇빛, 달빛, 구름 낀 픽셀이 삭제되어 대략적인 합성물이 만들어졌습니다. annual dnb eog lights nighttime noaa -
VIIRS 야간 일/야간 연간 밴드 합성물 V2.2
연간 전 세계 VIIRS 야간 조명 데이터 세트는 2022년 월별 구름 없는 평균 방사광도 그리드에서 생성된 시계열입니다. 이전 연도의 데이터는 NOAA/VIIRS/DNB/ANNUAL_V21 데이터 세트에서 확인할 수 있습니다. 초기 필터링 단계에서 햇빛, 달빛, 구름 낀 픽셀이 삭제되어 … 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) |"]]