Vegetation Structure Index (VSI): Retrieving Vegetation Structural Information from Multi-Angular Satellite Remote Sensing

Abstract

Utilization of the Bidirectional Reflectance Distribution Function (BRDF) model parameters obtained from the multi-angular remote sensing is one of the approaches for the retrieval of vegetation structural information. In this research, the potential of multi-angular vegetation indices, formulated by the combination of multi-spectral reflectance from different view angles, for the retrieval of forest above-ground biomass was assessed in the New England region. The multi-angular vegetation indices were generated by the simulation of the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Model Parameters Product (MCD43A1 Version 6)-based BRDF parameters. The effects of the seasonal (spring, summer, autumn, and winter) composites of the multi-angular vegetation indices on the above-ground biomass, the angular relationship of the spectral reflectance with above-ground biomass, and the interrelationships between the multi-angular vegetation indices were analyzed. Among the existing multi-angular vegetation indices, only the Nadir BRDF-adjusted NDVI and Hot-spot incorporated NDVI showed significant relationship (more than 50%) with the above-ground biomass. The Vegetation Structure Index (VSI), newly proposed in the research, performed in the most efficient way and explained 64% variation of the above-ground biomass, suggesting that the right choice of the spectral channel and observation geometry should be considered for improving the estimates of the above-ground biomass. In addition, the right choice of seasonal data (summer) was found to be important for estimating the forest biomass, while other seasonal data were either insensitive or pointless. The promising results shown by the VSI suggest that it could be an appropriate candidate for monitoring vegetation structure from the multi-angular satellite remote sensing.

Remote sensing of phenology: Towards the comprehensive indicators of plant community dynamics from species to regional scales

“…A different spectral index in the latter study showed sensitivity to young leaf flushing as another important structural change (de Moura et al, 2017). Future advances in multi‐angular reflectance products and correction algorithms thus could fill important gaps on the links between phenology and plant community diversity, ecological functioning, and responses to stressors (Hilker et al, 2009; Pacheco‐Labrador et al, 2016; Sharma, 2021). These opportunities have already started to emerge in UAV applications using structure from motion to infer 3‐D structure of landscapes from overlapping images (Dandois & Ellis, 2013); however, phenological analyses using this technique over full‐season time frames are still few (Park et al, 2019).…”

“…et al, 2017). Future advances in multiangular reflectance products and correction algorithms thus could fill important gaps on the links between phenology and plant community diversity, ecological functioning, and responses to stressors (Hilker et al, 2009;Pacheco-Labrador et al, 2016;Sharma, 2021).…”

Forest Structure Mapping of Boreal Coniferous Forests Using Multi-Source Remote Sensing Data

“…The analysis of forest structure changes based on radar or optical data are typically built indices to capture the complexity of the forest structure in terms of both horizontal and vertical structure. For instance, multi-angle remote sensing was used to obtain bidirectional reflectance distribution function (BRDF) model parameters to analyze vegetation structure information [7]. The optical vegetation index has been used as a horizontal structure to examine changes in canopy cover [8,9].…”