Evaluation of NDVI Estimation Considering Atmospheric and BRDF Correction through Himawari-8/AHI

Noh-Hun Seong,Kyung-Soo Han,Jinsoo Kim,Daeseong Jung

doi:10.1007/s13143-019-00167-0

Abstract

Satellite-based vegetation indices are an essential element in understanding the Earth’s surface. In this study, we estimated the normalized difference vegetation index (NDVI) using Himawari-8/Advanced Himawari Imager (AHI) data and analyzed the sensitivity of products to atmospheric and surface correction. We used the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer model for atmospheric correction, and kernel-based semi-empirical bidirectional reflectance distribution function (BRDF) model to remove surface anisotropic effects. From this, top-of-atmosphere, top-of-canopy, and normalized NDVIs were produced. A sensitivity analysis showed that the normalized NDVI had the lowest number of missing values compared with the others and almost no low peaks during the study period. These results were validated by Terra and Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) and Project for On-Board Autonomy/Vegetation (PROBA) NDVI product, showing the root mean square error (RMSE) and bias of 0.09 and + 0.04 (MODIS) and 0.09 and − 0.04 (PROBA), respectively. These results also satisfied the FP7 Geoland2/BioPar project-defined user requirements (threshold: 0.15; target: 0.10).

Highlights

Vegetation index-based remote sensing is a standard tool of Earth system science and continues to play a central role in global change, carbon cycle, land coverage/use, and terrestrial ecology research
We examined three normalized difference vegetation index (NDVI) types (TOA NDVI, TOC NDVI, and normalized NDVI) for the Himawari-8/Advanced Himawari Imager (AHI) over a 1-year period from January to December 2017
The maximum value composite (MVC) values for the TOA and TOC NDVIs were synthesized over a 1-day period to equalize the temporal resolution of the three NDVIs

Summary

Introduction

Vegetation index-based remote sensing is a standard tool of Earth system science and continues to play a central role in global change, carbon cycle, land coverage/use, and terrestrial ecology research. Many studies use three types of reflectance to calculate NDVI: top-of-atmosphere (TOA), top-of-canopy (TOC), and normalized reflectance with bidirectional reflectance distribution function (BRDF) modeling. TOA reflectance does not include atmospheric correction In this case, atmospheric effects are removed during NDVI calculations (Holben 1986). Atmospheric elements such as water vapor, total ozone column, and aerosol optical depth (AOD) affect the accuracy of satellite-based land surface products (Nagol et al 2009). Normalized reflectance with BRDF modeling incurs changes in the NDVI value with changes in the satellite angle and solar angle (Fensholt et al 2006a). The resulting NDVI products must account for the BRDF effect (Vermote et al 2008); the BRDF must be modeled according to the satellite’s characteristics (Yeom and Kim 2013)

Methods

Results

Conclusion