Phenology-based method for monitoring woody and herbaceous vegetation in forests at a sub-pixel scale using NDVI time series
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Among satellite remote sensing tools, spectral vegetation indices are widely used for monitoring vegetation dynamics. However, satellite-derived vegetation indices are mostly used to interpret changes as greening or browning of the entire vegetation system without being able to distinguish between the woody and herbaceous contribution to those trends. To date, only few studies have used vegetation indices to detect vegetation components in woodland systems at a sub-pixel level. To distinguish between woody and herbaceous contributions, Roderick et al. (1999) used time series analysis on NDVI. They aimed to map woody and herbaceous cover across Australia by applying a moving average method to separate between the long inter-annual trend and the seasonal (intra-annual) components of the time series. They assumed that woody vegetation in Australia is mainly evergreen (i.e., woody plants that keep their leaves and stay green throughout the entire year) and herbaceous vegetation is ephemeral (i.e., above ground tissues that wither during the dry season). Then, they attributed the baseline of the trend to the woody vegetation and the seasonal signal to herbaceous vegetation in the understory. Lu et al. (2003) further refined their method by applying a Seasonal-Trend decomposition (STL) based on LOcally wEighted regreSsion Smooth (LOESS) adding a small seasonal component to the trend. By applying STL on 8-km NDVI time series derived from the Advanced Very High Resolution Radiometer (AVHRR), they produced ensemble-monthly averages of herbaceous vegetation cover for a 14-year period over Australia. Although promising, their proposed model is relatively complex and not suited for Mediterranean vegetation systems. In their model, the NDVI attributed to the woody vegetation increases simultaneously with that attributed to the herbaceous vegetation while actuality there is a delay of few months between the development of ephemeral (herbaceous) and evergreen (woody) foliage in Mediterranean systems. In this study (Helman et al. 2015) we present an efficient method to distinguish between NDVI from woody (i.e., evergreen) and herbaceous (i.e., ephemeral) vegetation in Mediterranean woodlands at a sub-pixel scale using phenology-based time series analysis. We first built 14-year MODIS NDVI time series at a temporal resolution of 16 days and spatial resolution of 250 m. Then, using the distinct phenology of the herbaceous and woody vegetation we decomposed NDVI time series into their woody (NDVIW) and herbaceous (NDVIH) signals. We compared our results with field data of overstory (i.e., woody) leaf area index and estimated woody and herbaceous vegetation covers in two Mediterranean woodland sites. Results were also compared to NDVIu retrieved from MODIS BRDF data (Yang et al., 2014) at those two sites. Finally, we demonstrated the potential applications of this method for forest management and pre/post-fire monitoring. The proposed decomposition method was used for pre and post fire monitoring purposes in the mixed oak-pine woodlands of Mt Carmel. |
Decomposition of NDVI time series derived from MODIS at 250m for the Yatir pine forest (left) and the oak-pine woodlands of Mt Carmel (right). (b and f) the NDVI attributed to the woody vegetation. (c and g) The seasonal NDVI attributed to herbaceous vegetation. (d and h) The inter-annual NDVI attributed to the herbaceous vegetation.
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