Evaluation and Normalization of Topographic Effects on Vegetation Indices

Rui Chen,Jing Li,Aleixandre Verger,Guoxiang Liu,Gaofei Yin

doi:10.3390/rs12142290

Abstract

The normalization of topographic effects on vegetation indices (VIs) is a prerequisite for their proper use in mountainous areas. We assessed the topographic effects on the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the soil adjusted vegetation index (SAVI), and the near-infrared reflectance of terrestrial vegetation (NIRv) calculated from Sentinel-2. The evaluation was based on two criteria: the correlation with local illumination condition and the dependence on aspect. Results show that topographic effects can be neglected for the NDVI, while they heavily influence the SAVI, EVI, and NIRv: the local illumination condition explains 19.85%, 25.37%, and 26.69% of the variation of the SAVI, EVI, and NIRv, respectively, and the coefficients of variation across different aspects are, respectively, 8.13%, 10.46%, and 14.07%. We demonstrated the applicability of existing correction methods, including statistical-empirical (SE), sun-canopy-sensor with C-correction (SCS + C), and path length correction (PLC), dedicatedly designed for reflectance, to normalize topographic effects on VIs. Our study will benefit vegetation monitoring with VIs over mountainous areas.

Highlights

The vegetation indices (VIs) are widely used in vegetation monitoring and biophysical parameters retrieval because of their simplicity and robustness [1]
The enhanced vegetation index (EVI) has the highest slope (0.302) and the near-infrared reflectance of terrestrial vegetation (NIRv) has the highest correlation with illumination conditions (R2 = 0.267)
We assessed the topographic effects on four VIs: normalized difference vegetation index (NDVI), EVI, soil adjusted vegetation index (SAVI), and NIRv, calculated from

Summary

Introduction

The vegetation indices (VIs) are widely used in vegetation monitoring and biophysical parameters retrieval because of their simplicity and robustness [1]. Among existing VIs, the normalized difference vegetation index (NDVI) is the most widely used, partly due to its normalized ratio form, which minimizes the influence of several confounding factors [2]. Many studies revealed that NDVI still suffers from many confounding factors, e.g., atmosphere and soil, and is prone to saturate for dense vegetation [3]. Many alternative soil-adjusted and atmospherically resistant VIs based on normalized expressions with ratios of reflectance terms that can contain additional corrective factors for confounding factors have been developed, including the enhanced vegetation index (EVI) [3], the soil adjusted vegetation index (SAVI) [4], and the near-infrared reflectance of terrestrial vegetation (NIRv) [5].

Methods

Results

Discussion

Conclusion