Modeling the Radial Stem Growth of the Pine (Pinus sylvestris L.) Forests Using the Satellite-Derived NDVI and LST (MODIS/AQUA) Data

Yulia Ivanova,Vlad Soukhovolsky,Anton Kovalev

doi:10.3390/atmos12010012

Abstract

The paper considers a new approach to modeling the relationship between the increase in woody phytomass in the pine forest and satellite-derived Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) (MODIS/AQUA) data. The developed model combines the phenological and forest growth processes. For the analysis, NDVI and LST (MODIS) satellite data were used together with the measurements of tree-ring widths (TRW). NDVI data contain features of each growing season. The models include parameters of parabolic approximation of NDVI and LST time series transformed using principal component analysis. The study shows that the current rate of TRW is determined by the total values of principal components of the satellite indices over the season and the rate of tree increment in the preceding year.

Highlights

Research addressing the growth and changes in productivity of boreal forests is useful for understanding and predicting sustainability of these ecosystems affected by diverse environmental stresses associated with extreme weather events and climate change [1–7].Most studies dealing with this problem predict that, because of climate change, tree growth will be affected by more frequent and violent extreme events
One can construct linear regression models of relationTo construct the model of radial growth, we take into account the relationship of the ships between the first differences of radial stem growth and values of the principal current year growth, tree-ring widths (TRW)(t), to the growth of the previous year, TRW(t − 1), determined components of matrices A and B
The model proposed in this study relates the average value of TRW first differences (FD) for the tree stand to the current seasonal integrated remote sensing parameters Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST)

Summary

Introduction

Research addressing the growth and changes in productivity of boreal forests is useful for understanding and predicting sustainability of these ecosystems affected by diverse environmental stresses associated with extreme weather events and climate change [1–7]. Most studies dealing with this problem predict that, because of climate change, tree growth will be affected by more frequent and violent extreme events (ice storms, wetland formation, droughts, windblows, etc.). Tree growth processes and weather events can be understood using methods of dendrochronology, which studies time series of tree ring widths (TRW) over many years [9–12]. Data on long-term TRW variations are used to determine how much wood is formed in the tree stem, which can be directly associated with the biomass increase and carbon consumption [13–16]. Dendrochronology methods have been used to study interactions between species-specific growth and temperature and humidity variations at the local, regional, and continental scales [17–21]

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Discussion

Conclusion