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DOI	10.1038/s41467-021-20994-y
	New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests
	Hashimoto H.; Wang W.; Dungan J.L.; Li S.; Michaelis A.R.; Takenaka H.; Higuchi A.; Myneni R.B.; Nemani R.R.
发表日期	2021
ISSN	2041-1723
卷号	12 期号:1
英文摘要	Assessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.
语种	英语
scopus关键词	cloud cover; evergreen forest; geostationary satellite; ground-based measurement; MODIS; NDVI; observational method; remote sensing; satellite data; satellite sensor; seasonal variation; seasonality; spatiotemporal analysis; Article; canopy; cloud; controlled study; evergreen; geology; nonhuman; rain forest; seasonal variation; Brazil; color; ecosystem monitoring; photosynthesis; physiology; plant leaf; procedures; satellite imagery; season; spatiotemporal analysis; Amazon River; Satellites; Brazil; Color; Ecological Parameter Monitoring; Photosynthesis; Plant Leaves; Rainforest; Satellite Imagery; Seasons; Spatio-Temporal Analysis
来源期刊	Nature Communications
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/251524
作者单位	Department of Applied Environmental Science, California State University – Monterey Bay, Seaside, CA, United States; NASA Ames Research Center, Moffett Field, CA, United States; Guizhou Provincial Key Laboratory of Geographic State Monitoring of Watershed, Guizhou Education University, Guiyang, China; Bay Area Environmental Research Institute, Moffett Field, CA, United States; JAXA Earth Observation Research Center, Tsukuba, Ibaraki, Japan; Center for Environmental Remote Sensing, Chiba University, Chiba-shi, Chiba, Japan; Earth & Environment Department, Boston University, Boston, MA, United States
推荐引用方式 GB/T 7714	Hashimoto H.,Wang W.,Dungan J.L.,et al. New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests[J],2021,12(1).
APA	Hashimoto H..,Wang W..,Dungan J.L..,Li S..,Michaelis A.R..,...&Nemani R.R..(2021).New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests.Nature Communications,12(1).
MLA	Hashimoto H.,et al."New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests".Nature Communications 12.1(2021).