The Use of Satellite Information (MODIS/Aqua) for Phenological and Classification Analysis of Plant Communities

Yulia Ivanova,Oleg Yakubailik,Anton Kovalev,Vlad Soukhovolsky

doi:10.3390/f10070561

Abstract

Vegetation indices derived from remote sensing measurements are commonly used to describe and monitor vegetation. However, the same plant community can have a different NDVI (normalized difference vegetation index) depending on weather conditions, and this complicates classification of plant communities. The present study develops methods of classifying the types of plant communities based on long-term NDVI data (MODIS/Aqua). The number of variables is reduced by introducing two integrated parameters of the NDVI seasonal series, facilitating classification of the meadow, steppe, and forest plant communities in Siberia using linear discriminant analysis. The quality of classification conducted by using the markers characterizing NDVI dynamics during 2003–2017 varies between 94% (forest and steppe) and 68% (meadow and forest). In addition to determining phenological markers, canonical correlations have been calculated between the time series of the proposed markers and the time series of monthly average air temperatures. Based on this, each pixel with a definite plant composition can be characterized by only four values of canonical correlation coefficients over the entire period analyzed. By using canonical correlations between NDVI and weather parameters and employing linear discriminant analysis, one can obtain a highly accurate classification of the study plant communities.

Highlights

Plant phenology is determined by the dates of the seasonal biological events in the plant life cycle such as the emergence of leaves, the emergence of flowers, etc
For analysis of normalized difference vegetation index (NDVI) images of different plant communities, the values of the parameters were analyzed in the (NDVIFmax, dNDVIF/dn) plane
NDVI parameters, vary rather widely both in one season and between seasons, as weather factors considerably influence the current values obtained by remote sensing techniques

Summary

Introduction

Plant phenology is determined by the dates of the seasonal biological events in the plant life cycle such as the emergence of leaves, the emergence of flowers, etc. The occurrence of phenological events is influenced by plant interactions with the air, soil, and water flows, and, phenology is one of the most reliable indicators of plant seasonal dynamics. Phenology is a sensitive indicator of a changing climate and, on the other hand, phenology is related to the productivity and biophysical properties of the ecosystem [1,2,3,4]. Changes in phenology dynamics can correspond to the effects of both local and global climate change on plant ecology [5,6].

Objectives

Methods

Results

Discussion

Conclusion