Viewing Geometry Sensitivity of Commonly Used Vegetation Indices towards the Estimation of Biophysical Variables in Orchards

Jonathan Van Beek,Pol Coppin,Laurent Tits,Pieter Janssens,Ben Somers,Tom Deckers

doi:10.3390/jimaging2020015

Jonathan Van Beek, Pol Coppin + Show 4 more

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https://doi.org/10.3390/jimaging2020015

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Abstract

Stress-related biophysical variables of capital intensive orchard crops can be estimated with proxies via spectral vegetation indices from off-nadir viewing satellite imagery. However, variable viewing compositions affect the relationship between spectral vegetation indices and stress-related variables (i.e., chlorophyll content, water content and Leaf Area Index (LAI)) and could obstruct change detection. A sensitivity analysis was performed on the estimation of biophysical variables via vegetation indices for a wide range of viewing geometries. Subsequently, off-nadir viewing satellite imagery of an experimental orchard was analyzed, while all influences of background admixture were minimized through vegetation index normalization. Results indicated significant differences between nadir and off-nadir viewing scenes (∆R2 > 0.4). The Photochemical Reflectance Index (PRI), Normalized Difference Infrared Index (NDII) and Simple Ratio Pigment Index (SRPI) showed increased R2 values for off-nadir scenes taken perpendicular compared to parallel to row orientation. Other indices, such as Normalized Difference Vegetation Index (NDVI), Gitelson and Merzlyak (GM) and Structure Insensitive Pigment Index (SIPI), showed a significant decrease in R2 values from nadir to off-nadir viewing scenes. These results show the necessity of vegetation index selection for variable viewing applications to obtain an optimal derivation of biophysical variables in all circumstances.

Highlights

Monitoring and managing of capital intensive orchard crops through precision agriculture is centered around the estimation of stress-related biophysical variables such as chlorophyll content [1,2], water content [2,3,4] and Leaf Area Index (LAI) [5]
The simulations were used to investigate the overall effect of viewing geometry on the estimation of biophysical variables through vegetation indices without the influence of sensor/target anomalies
Practical use in hedgerow orchards under temperate climate conditions requires the use of high spatial resolution satellite sensors with off-nadir viewing capabilities [10,11]

Summary

Introduction

Monitoring and managing of capital intensive orchard crops through precision agriculture is centered around the estimation of stress-related biophysical variables such as chlorophyll content [1,2], water content [2,3,4] and Leaf Area Index (LAI) [5]. Labor intensive and destructive in situ measurements of biophysical variables could be circumvented through remotely sensed imagery and spectral vegetation indices [6,7]. Practical use of remotely sensed spectral imagery in temperate climates requires near-to-daily revisit times because of the high cloud cover [10]. Heterogeneous orchards require high spatial resolution imagery.

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