Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI

@article{citeulike:484852, abstract = {Current models of vegetation dynamics using the normalized vegetation index (NDVI) time series perform poorly for high-latitude environments. This is due partly to specific attributes of these environments, such as short growing season, long periods of darkness in winter, persistence of snow cover, and dominance of evergreen species, but also to the design of the models. We present a new method for monitoring vegetation activity at high latitudes, using Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI. It estimates the NDVI of the vegetation during winter and applies a double logistic function, which is uniquely defined by six parameters that describe the yearly NDVI time series. Using NDVI data from 2000 to 2004, we illustrate the performance of this method for an area in northern Scandinavia (35 x 162 km2, 68[deg] N 23[deg] E) and compare it to existing methods based on Fourier series and asymmetric Gaussian functions. The double logistic functions describe the NDVI data better than both the Fourier series and the asymmetric Gaussian functions, as quantified by the root mean square errors. Compared with the method based on Fourier series, the new method does not overestimate the duration of the growing season. In addition, it handles outliers effectively and estimates parameters that are related to phenological events, such as the timing of spring and autumn. This makes the method most suitable for both estimating biophysical parameters and monitoring vegetation phenology.}, author = {Beck, Pieter S. and Atzberger, Clement and Hogda, Kjell A. and Johansen, Bernt and Skidmore, Andrew K. }, citeulike-article-id = {484852}, doi = {http://dx.doi.org/10.1016/j.rse.2005.10.021}, journal = {Remote Sensing of Environment}, keywords = {dynamics, high\_latitude, modis, monitoring, ndvi, time-series, vegetation}, month = {February}, number = {3}, pages = {321--334}, posted-at = {2008-07-03 08:56:55}, priority = {2}, title = {Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI}, url = {http://dx.doi.org/10.1016/j.rse.2005.10.021}, volume = {100}, year = {2006} }

TY - JOUR ID - citeulike:484852 L3 - citeulike-article-id:484852 TI - Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI JF - Remote Sensing of Environment VL - 100 IS - 3 SP - 321 EP - 334 N2 - Current models of vegetation dynamics using the normalized vegetation index (NDVI) time series perform poorly for high-latitude environments. This is due partly to specific attributes of these environments, such as short growing season, long periods of darkness in winter, persistence of snow cover, and dominance of evergreen species, but also to the design of the models. We present a new method for monitoring vegetation activity at high latitudes, using Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI. It estimates the NDVI of the vegetation during winter and applies a double logistic function, which is uniquely defined by six parameters that describe the yearly NDVI time series. Using NDVI data from 2000 to 2004, we illustrate the performance of this method for an area in northern Scandinavia (35 x 162 km2, 68[deg] N 23[deg] E) and compare it to existing methods based on Fourier series and asymmetric Gaussian functions. The double logistic functions describe the NDVI data better than both the Fourier series and the asymmetric Gaussian functions, as quantified by the root mean square errors. Compared with the method based on Fourier series, the new method does not overestimate the duration of the growing season. In addition, it handles outliers effectively and estimates parameters that are related to phenological events, such as the timing of spring and autumn. This makes the method most suitable for both estimating biophysical parameters and monitoring vegetation phenology. KW - dynamics KW - high_latitude KW - modis KW - monitoring KW - ndvi KW - time-series KW - vegetation AU - Beck, Pieter AU - Atzberger, Clement AU - Hogda, Kjell AU - Johansen, Bernt AU - Skidmore, Andrew PY - 2006/02/15/ UR - http://dx.doi.org/10.1016/j.rse.2005.10.021 ER -