DOI: 10.1016/j.jag.2017.02.021
Scopus记录号: 2-s2.0-85026743481
论文题名: Spatially detailed retrievals of spring phenology from single-season high-resolution image time series
作者: Vrieling A ; , Skidmore A ; K ; , Wang T ; , Meroni M ; , Ens B ; J ; , Oosterbeek K ; , O’Connor B ; , Darvishzadeh R ; , Heurich M ; , Shepherd A ; , Paganini M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2017
卷: 59 起始页码: 19
结束页码: 30
语种: 英语
英文关键词: Agriculture
; Landscape variability
; Multi-source imagery
; Multi-temporal analysis
; NDVI time series
; Phenology
; Saltmarsh
; Spatial resolution
Scopus关键词: image resolution
; NDVI
; phenology
; pixel
; satellite imagery
; season
; spatial resolution
; spring (hydrology)
; temporal analysis
; time series analysis
; Friesland
; Frisian Islands
; Netherlands
; Schiermonnikoog
; West Frisian Islands
; Proba
英文摘要: Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability. © 2017 Elsevier B.V. All rights reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79923
Appears in Collections: 气候变化事实与影响
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作者单位: University of Twente, Faculty of Geo-Information Science and Earth Observation, P.O. Box 217, Enschede, Netherlands; European Commission, Joint Research Centre, Directorate D – Sustainable Resources, Via E. Fermi 2749, Ispra, VA, Italy; Sovon Dutch Centre for Field Ornithology, Sovon-Texel, P.O. Box 59, Den Burg, Netherlands; United Nations Environment Programme – World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge, United Kingdom; Bavarian Forest National Park, Freyunger Straße 2, Grafenau, Germany; Sustainable Soil & Grassland Systems, Rothamsted Research, North Wyke, Devon, United Kingdom; European Space Agency – ESRIN, Via Galileo Galilei, Casella Postale 64, Frascati, RM, Italy
Recommended Citation:
Vrieling A,, Skidmore A,K,et al. Spatially detailed retrievals of spring phenology from single-season high-resolution image time series[J]. International Journal of Applied Earth Observation and Geoinformation,2017-01-01,59