Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

Anton Vrieling (Corresponding Author), Andrew K. Skidmore, Tiejun Wang, Michele Meroni, Bruno J. Ens, Kees Oosterbeek, Brian O’Connor, Roshanak Darvishzadeh, Marco Heurich, Anita Shepherd, Marc Paganini

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)19-30
Number of pages12
JournalInternational journal of applied earth observation and geoinformation
Volume59
Early online date7 Mar 2017
DOIs
Publication statusPublished - 1 Jul 2017

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image resolution
Image resolution
phenology
Time series
Satellites
time series
Geothermal springs
Proba
Fusion reactions
Pixels
MODIS
Availability
Landsat
satellite data
Sensors
Composite materials
satellite sensor
vegetation
vegetation index
cloud cover

Keywords

  • Agriculture
  • Landscape variability
  • Multi-source imagery
  • Multi-temporal analysis
  • NDVI time series
  • Phenology
  • Saltmarsh
  • Spatial resolution

Cite this

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series. / Vrieling, Anton (Corresponding Author); Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O’Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc.

In: International journal of applied earth observation and geoinformation, Vol. 59, 01.07.2017, p. 19-30.

Research output: Contribution to journalArticle

Vrieling, A, Skidmore, AK, Wang, T, Meroni, M, Ens, BJ, Oosterbeek, K, O’Connor, B, Darvishzadeh, R, Heurich, M, Shepherd, A & Paganini, M 2017, 'Spatially detailed retrievals of spring phenology from single-season high-resolution image time series', International journal of applied earth observation and geoinformation, vol. 59, pp. 19-30. https://doi.org/10.1016/j.jag.2017.02.021
Vrieling, Anton ; Skidmore, Andrew K. ; Wang, Tiejun ; Meroni, Michele ; Ens, Bruno J. ; Oosterbeek, Kees ; O’Connor, Brian ; Darvishzadeh, Roshanak ; Heurich, Marco ; Shepherd, Anita ; Paganini, Marc. / Spatially detailed retrievals of spring phenology from single-season high-resolution image time series. In: International journal of applied earth observation and geoinformation. 2017 ; Vol. 59. pp. 19-30.
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abstract = "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.",
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AU - Ens, Bruno J.

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AU - O’Connor, Brian

AU - Darvishzadeh, Roshanak

AU - Heurich, Marco

AU - Shepherd, Anita

AU - Paganini, Marc

N1 - This work was financed through the European Space Agency’s Innovators-III project “Remote Sensing for Essential Biodiversity Variables”. We thank Willem Nieuwenhuis (University of Twente) for his assistance in atmospherically correcting the RapidEye imagery. We much appreciate the feedback of the anonymous reviewers on a previous version of this paper.

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N2 - 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.

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KW - Agriculture

KW - Landscape variability

KW - Multi-source imagery

KW - Multi-temporal analysis

KW - NDVI time series

KW - Phenology

KW - Saltmarsh

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JO - International journal of applied earth observation and geoinformation

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