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Relation between vegetation productivity trends and the start of the growing season trends

Data Visualization Created 08 Oct 2019 Last modified 17 Oct 2019
2 min read

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Unit

The vegetation productivity index is a dimensionless measure. It is calculated as the integral value of the yearly vegetation index. Hence, digital values indicate the approximated productivity of the land surface vegetation. Start of Season trends are expressed in number of days / year. 

Methodology

The dataset addresses trends in land surface productivity versus trends in the start of the vegetation growing season. Land surface productivity was derived from remote sensing observed time series of vegetation indices between 2000-2016. The vegetation index used in the indicator is the Plant Phenology Index (PPI, Jin and Eklundh, 2014). PPI is based on the MODIS Nadir BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR. The product provides reflectance data for the MODIS “land” bands (1 - 7) adjusted using a bi-directional reflectance distribution function. This function models values as if they were collected from a nadir-view to remove so called cross-track illumination effects. The product is distributed with 500 m pixel size (MODIS Sinusoidal Grid) with 8-days compositing period. The start of the growing season date date is defined as the date when the PPI has increased to the 20% level of the average annual PPI amplitude. The average annual PPI amplitude is the difference between the average peak level and the average base level for each pixel.

Reference: Jin, H., Eklundh, L. (2014): A physically based vegetation index for improved monitoring of plant phenology, Remote Sensing, 152, 512 – 525. Inpout to the PPI index was from MODIS NDVI.
Jin, H.X., Jönsson, A.M., Bolmgren, K., Langvall, O., Eklundh, L., 2017. Disentangling remotely-sensed plant phenology and snow seasonality at northern Europe using MODIS and the plant phenology index. Remote Sens Environ 2017, 198, 203-212.

Data sources

Plant Phenology Index provided by Lund University

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