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|Title:||Spatially detailed retrievals of spring phenology from single-season high-resolution image time series|
|Authors:||Vrieling A.; SKIDMORE Andrew; WANG Tiejun; MERONI MICHELE; ENS Bruno; OOSTERBEEK Kees; O’CONNOR Brian; DARVISHZADEH Roshanak; HEURICH Marco; SHEPHERD Anita; PAGANINI Marc|
|Citation:||INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION vol. 59 p. 19-30|
|Publisher:||ELSEVIER SCIENCE BV|
|Type:||Articles in periodicals and books|
|Abstract:||tVegetation indices derived from satellite image time series have been extensively used to estimate thetiming of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensorswith daily revisit capability are typically employed for this purpose. In recent years, phenology is beingretrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellitedata. To overcome the reduced acquisition frequency of such data, previous attempts involved fusionbetween high- and medium-resolution data, or combinations of multi-year acquisitions in a single phe-nological reconstruction. The objectives of this study are to demonstrate that phenological parameters cannow be retrieved from single-season high-resolution time series, and to compare these retrievals againstthose derived from multi-year high-resolution and single-season medium-resolution satellite data. Thestudy focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamicsaltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution)acquired between March and August 2015, phenological parameters were estimated using a function fit-ting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLIdata, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrievedphenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and alarge 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 bythe inclusion of years with warmer spring temperatures, whereas adjustment of the average phenologyto 2015 observations was only feasible for a few pixels due to cloud cover around phenological transi-tion dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolutionequivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care,particularly in landscapes with fine-scale land cover variability.|
|JRC Directorate:||Sustainable Resources|
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