气候变化领域集成服务门户(CCPortal): Scale-dependency of Arctic ecosystem properties revealed by UAV

CCPortal

DOI	10.1088/1748-9326/aba20b
	Scale-dependency of Arctic ecosystem properties revealed by UAV
	Siewert M.B.; Olofsson J.
发表日期	2020
ISSN	17489318
卷号	15 期号:9
英文摘要	In the face of climate change, it is important to estimate changes in key ecosystem properties such as plant biomass and gross primary productivity (GPP). Ground truth estimates and especially experiments are performed at small spatial scales (0.01-1 m2) and scaled up using coarse scale satellite remote sensing products. This will lead to a scaling bias for non-linearly related properties in heterogeneous environments when the relationships are not developed at the same spatial scale as the remote sensing products. We show that unmanned aerial vehicles (UAVs) can reliably measure normalized difference vegetation index (NDVI) at centimeter resolution even in highly heterogeneous Arctic tundra terrain. This reveals that this scaling bias increases most at very fine resolution, but UAVs can overcome this by generating remote sensing products at the same scales as ecological changes occur. Using ground truth data generated at 0.0625 m2 and 1 m2 with Landsat 30 m scale satellite imagery the resulting underestimation is large (8.9%-17.0% for biomass and 5.0%-9.7% for GPP600) and of a magnitude comparable to the expected effects of decades of climate change. Methods to correct this upscaling bias exist but rely on sub-pixel information. Our data shows that this scale-dependency will vary strongly between areas and across seasons, making it hard to derive generalized functions compensating for it. This is particularly relevant to Arctic greening with a predominantly heterogeneous land cover, strong seasonality and much experimental research at sub-meter scale, but also applies to other heterogeneous landscapes. These results demonstrate the value of UAVs for satellite validation. UAVs can bridge between plot scale used in ecological field investigations and coarse scale in satellite monitoring relevant for Earth System Models. Since future climate changes are expected to alter landscape heterogeneity, seasonally updated UAV imagery will be an essential tool to correctly predict landscape-scale changes in ecosystem properties. © 2020 The Author(s). Published by IOP Publishing Ltd.
英文关键词	Arctic greening; Climate change; GPP; NDVI; Scale-dependency; UAV
语种	英语
scopus关键词	Antennas; Arctic vehicles; Ecosystems; Plants (botany); Remote sensing; Satellite imagery; Small satellites; Unmanned aerial vehicles (UAV); Experimental research; Gross primary productivity; Heterogeneous environments; Heterogeneous landscapes; Landscape heterogeneities; Normalized difference vegetation index; Satellite remote sensing; Sub-pixel information; Climate change; aerial survey; ecosystem dynamics; scale effect; unmanned vehicle; Arctic
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/153800
作者单位	Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden
推荐引用方式 GB/T 7714	Siewert M.B.,Olofsson J.. Scale-dependency of Arctic ecosystem properties revealed by UAV[J],2020,15(9).
APA	Siewert M.B.,&Olofsson J..(2020).Scale-dependency of Arctic ecosystem properties revealed by UAV.Environmental Research Letters,15(9).
MLA	Siewert M.B.,et al."Scale-dependency of Arctic ecosystem properties revealed by UAV".Environmental Research Letters 15.9(2020).