气候变化领域集成服务门户(CCPortal): Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring

CCPortal

DOI	10.1016/j.rse.2020.112243
	Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring
	Finger D.J.I.; McPherson M.L.; Houskeeper H.F.; Kudela R.M.
发表日期	2021
ISSN	00344257
卷号	254
英文摘要	Extending from central California to Alaska, bull kelp (Nereocystis luetkeana) forms seasonal kelp forests that are iconic coastal ecosystems in much of the eastern Pacific. Historical and ongoing field surveys and aerial imagery are used to provide biological data on kelp canopy cover and health, but satellite remote sensing provides the opportunity to generate consistent, long-term datasets over a large spatial scale. Robust satellite-based timeseries measurements of giant kelp (Macrocystis pyrifera) are available for much of the California coastline (e.g., Santa Barbara to Santa Cruz), but there have been no equivalent publications for bull kelp. Recent loss of bull kelp in northern California emphasized the need for more expansive long-term monitoring of canopy trends. We tested various kelp classification approaches using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to Landsat imagery, which allowed sufficient temporal and spatial data collection during bull kelp's narrow seasonal maximum, and compare with the California Department of Fish and Wildlife (CDFW) aerial survey canopy area product. We addressed five main topics that have relevance to enabling Landsat in long-term monitoring of bull kelp canopy coverage in northern California: (1) the effect of MESMA configurations applied to Landsat imagery, including software dependencies and endmember configurations, (2) comparison of Landsat to traditional surveys, (3) differences across Landsat sensors, (4) tidal influence on canopy area, and (5) trends in the decadal timeseries. We found that there was no statistical difference (p = 0.53) between MESMA platforms (IDL-based and a Python-scripted method; RMSE 1.5 km2 or 17.6% when normalized by the range in CDFW), and that a 7-endmember MESMA model provided the lowest RMSE (1.4 km2 or 16.9%). Furthermore, while tidal phases can submerge or emerge kelp canopy and thus potentially affect kelp detection, we found a weak and statistically insignificant correlation between tides and performance of our remote estimate of kelp canopy area. Canopy estimations from Landsat-8 images yielded a higher NRMSE than Landsat-4 and -5 images, but the lack of matchup limits comparison. Imagery from early fall yielded the largest coverage estimates. Overall, our results show that Landsat enables broad remote measurement of bull kelp canopy coverage to supplement existing survey methods and increase continuity of timeseries for monitoring long-term trends. © 2020 The Authors
英文关键词	Bull kelp; Endmember; Image classification; Landsat; Marine heat wave; MESMA; Nereocystis; Northern California; Tide; Timeseries
语种	英语
scopus关键词	Aerial photography; Antennas; Ecosystems; Large dataset; Remote sensing; Surveys; Classification approach; Large spatial scale; Long term monitoring; Multiple endmember spectral mixture analysis; Satellite remote sensing; Software dependencies; Statistical differences; Temporal and spatial; Satellite imagery; aerial survey; coast; Landsat; long-term change; monitoring system; remote sensing; satellite imagery; software; spatial data; Alaska; Bolivia; California; Santa Barbara [California]; Santa Cruz [Bolivia]; United States; Macrocystis pyrifera; Nereocystis; Nereocystis luetkeana
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178994
作者单位	Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA 94720, United States; Ocean Sciences Department, University of California Santa Cruz, Santa Cruz, CA 95064, United States; Department of Geography, University of California Los Angeles, Los Angeles, CA 90095, United States
推荐引用方式 GB/T 7714	Finger D.J.I.,McPherson M.L.,Houskeeper H.F.,et al. Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring[J],2021,254.
APA	Finger D.J.I.,McPherson M.L.,Houskeeper H.F.,&Kudela R.M..(2021).Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring.Remote Sensing of Environment,254.
MLA	Finger D.J.I.,et al."Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring".Remote Sensing of Environment 254(2021).