Comparison of Field and SAR-Derived Descriptors in the Retrieval of Soil Moisture from Oil Palm Crops Using PALSAR-2

Aimrun Wayayok,Veena Shashikant,Wataru Takeuchi,Md Rowshon Kamal,Yang Ping Lee,Abdul Rashid Mohamed Shariff

doi:10.3390/rs13234729

Aimrun Wayayok, Veena Shashikant + Show 4 more

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https://doi.org/10.3390/rs13234729

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Abstract

Synthetic-aperture radar’s (SAR’s) capacity to resolve the cloud cover concerns encountered while gathering optical data has tremendous potential for soil moisture data retrieval using SAR data. It is possible to use SAR data to recover soil moisture because the backscatter coefficient is sensitive to both soil and vegetation by penetrating through the vegetation layer. This study investigated the feasibility of employing a SAR-derived radar vegetation index (RVI), the ratios of the backscatter coefficients using polarizations of HH/HV (RHH/HV) and HV/HH (RHH/HV) to an oil palm crops as vegetation indicators in the water cloud model (WCM) using phased-array L-band SAR-2 (PALSAR-2). These data were compared to the manual leaf area index (LAI) and a physical soil sampling method for computing soil moisture. The field data included the LAI input parameters and, more importantly, physical soil samples from which to calculate the soil moisture. The fieldwork was carried out in Chuping District, Perlis State, Malaysia. Corresponding PALSAR-2 data were collected on three observation dates in 2019: 17 January, 16 April, and 9 July. The results showed that the WCM modeled using the LAI under HV polarization demonstrated promising accuracy, with the root mean square error recorded as 0.033 m3/m3. This was comparable to the RVI and RHH/HV under HV polarization, which had accuracies of 0.031 and 0.049 m3/m3, respectively. The findings of this study suggest that SAR-based indicators, RHH/HV and RVI using PALSAR-2, can be used to reduce field-related input in the retrieval of soil moisture data using the WCM for oil palm crop.

Highlights

IntroductionOil palm has long been recognized as a vital crop in tropical agricultural regions with a consistently increasing output rate, especially in Indonesia and Malaysia, which export significant amounts of crude palm oil to other countries [1]
For the SAR-based vegetation descriptors, the radar vegetation index (RVI) was derived from the PALSAR-2 images, where it has been shown to describe the structural vegetation characteristics, and the RVI correlates with the vegetation water content and leaf area index (LAI) indicators [84]
The ratio of the backscatter coefficients HH/HV (R HH/HV) and R HV/HH were employed to evaluate the potential use of these simple ratios as vegetation descriptors because the latter has been reported as being able to distinguish fluctuations in soil moisture using SAR data, and to identify areas where the influence of soil surface roughness can be mitigated [58]

Summary

Introduction

Oil palm has long been recognized as a vital crop in tropical agricultural regions with a consistently increasing output rate, especially in Indonesia and Malaysia, which export significant amounts of crude palm oil to other countries [1]. In Malaysia, oil palm crop production occupies 71% of the agricultural land [2]. Oil palm crop is the second most important source of edible oil, behind soybean, in terms of production [3]. Beyond its core role as an edible oil, palm oil has spawned other palm-based sectors, such as specialized fats, cocoa-butter alternatives, oleochemicals, soaps, domestic detergents, nutritional

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