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Remote Sensing Phenology

Status and the Way Forward

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Phenology of Ecosystem Processes

Abstract

A number of approaches using a variety of satellite remote sensing products have been used to derive metrics related to the timing of biological events (or land surface phenology, LSP). The advantages of utilizing remote sensing for phenology applications are the ability to capture the continuous expression of phenology patterns across the landscape and the ability to retrospectively observe phenology from archived satellite data sets (e.g. Landsat and Advanced Very High Resolution Radiometer). However, LSP databases have not yet been satisfactorily validated due to the difficulty in obtaining sufficiently extensive ground observations throughout the growing season. A multi-level validation approach that uses ground observations, dedicated web cameras, and high, medium, and coarse spatial resolution satellite data is needed to give scientists an improved level of confidence in utilizing the data. Many of these shortcomings are being addressed by phenology networks across the globe such as the U.S. National Phenology Network. Even without extensive validation, a number of applications areas have employed LSP data successfully, including studies on ecosystems analysis, disasters, land use, and climate change. Land surface phenology promises to continue contributing to these types of applications, and will also likely serve as an important early indicator of environmental effects of climate change

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Authors and Affiliations

  1. U.S. Geological Survey, Geographic Analysis and Monitoring, Reston, VA, USA

    Bradley C. Reed

  2. Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, WI, USA

    Mark D. Schwartz

  3. Center for Spatial Analysis, University of Oklahoma, Norman, OK, USA

    Xiangming Xiao

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  1. Bradley C. Reed
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Correspondence to Bradley C. Reed .

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Editors and Affiliations

  1. Dept. Forestry &, North Carolina State University, Main Campus Drive 920, Raleigh, 27695, U.S.A.

    Asko Noormets

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Reed, B.C., Schwartz, M.D., Xiao, X. (2009). Remote Sensing Phenology. In: Noormets, A. (eds) Phenology of Ecosystem Processes. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0026-5_10

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