Isolating type-specific phenologies through spectral unmixing of satellite time series |
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| Authors: | Jyoteshwar R Nagol Joseph O Sexton Anupam Anand Ritvik Sahajpal Thomas C Edwards |
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| Institution: | 1. Global Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park, MD, USA;2. USGS Utah Cooperative Fish and Wildlife Research Unit, Department of Wildland Resources, College of Natural Resources, Utah State University, Logan, UT, USA |
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| Abstract: | Vegetation phenology is commonly studied using time series of multi-spectral vegetation indices derived from satellite imagery. Differences in reflectance among land-cover and/or plant functional types are obscured by sub-pixel mixing, and so phenological analyses have typically sought to maximize the compositional purity of input satellite data by increasing spatial resolution. We present an alternative method to mitigate this ‘mixed-pixel problem’ and extract the phenological behavior of individual land-cover types inferentially, by inverting the linear mixture model traditionally used for sub-pixel land-cover mapping. Parameterized using genetic algorithms, the method takes advantage of the discriminating capacity of calibrated surface reflectance measurements in red, near infrared, and short-wave infrared wavelengths, as well as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index. In simulation, the unmixing procedure reproduced the reflectances and phenological signals of grass, crop, and deciduous forests with high fidelity (RMSE?
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| Keywords: | Spectral unmixing land-surface phenology NDVI genetic algorithms |
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