Estimation of soil moisture using a vegetation scattering model in wheat fields

Abstract

We develop a vegetation scattering model to eliminate the effect of vegetation and surface roughness on the radar signal. The canopy water content is an important variable associated with the scattering effect of vegetation, and it can be calculated using the leaf area index, which is retrieved from PROSAILH optical model based on Landsat-8 images. The scattering model introduced the direct scattering contribution of underlying ground into the water cloud model. The experimental correlation length was replaced by a fitting parameter from C-band RADSARSAT-2 radar data to calculate the scattering contribution of underlying ground. Results demonstrate that the vegetation scattering model has a good performance in soil moisture retrieval with R 2 of 0.805 and root-mean-square error of 0.039 m 3 • m −3. The applicability and capability of the scattering model will provide the operational potential of C-band radar data for soil moisture retrieval in an agricultural region. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Vegetation Effects on Soil Moisture Retrieval from Water Cloud Model Using PALSAR-2 for Oil Palm Trees

“…It was reported that HH polarization could provide a low RMSE value of 0.049 m 3 /m 3 [71] using remote sensing-based vegetation descriptors, in this case Normalized Difference Infrared Index (NDII). Similarly, when canopy water content based on LAI was applied as a vegetation descriptor, an RMSE of 0.039 was recorded [53]. Overall, when RMSE and MAE are carefully evaluated, the cross-polarized HV backscatter coefficient is revealed to be more vulnerable than the co-polarized backscatter HH in terms of polarization response in all Cases 1-5 observed.…”

“…The estimation of parameters C pp and D pp are solved using a linear model fitting, following which, the values of C pp and D pp are substituted into Equation (2), which allows for parameter A pp and B pp to be solved using the Nonlinear Least Squares Method (NLSM) [51][52][53][54]. It was noted that using Levenberg-Marquardt (LM) optimization in NLSM, an estimation of A pp and B pp can be made [55].…”

Sentinel-1 Backscatter Analysis and Radiative Transfer Modeling of Dense Winter Wheat Time Series

“…Lately, more and more studies using microwave time series data to estimate the soil moisture of agricultural areas-especially for the crop type winter wheat-have been conducted [19][20][21]. Often, only a single satellite orbit constellation and, therefore, data from one satellite with the same acquisition geometry are used [19,[22][23][24].…”

“…Lately, more and more studies using microwave time series data to estimate the soil moisture of agricultural areas-especially for the crop type winter wheat-have been conducted [19][20][21]. Often, only a single satellite orbit constellation and, therefore, data from one satellite with the same acquisition geometry are used [19,[22][23][24]. Occasionally, the time series used consists of data from the same satellite but related to different orbits and, thus, various azimuth or/and incidence angles [20,23,[25][26][27].…”

“…Summarizing the above studies, one established approach is to simulate radar backscatter or to estimate soil moisture of vegetated areas by using radar backscattering models based on the Radiative Transfer (RT) equation [29,30]. These model simulations of radar backscatter from agricultural fields are based on sensor and platform configurations (e.g., incidence angle, azimuth angle, frequency, and polarization), soil properties (e.g., soil moisture, texture, and surface roughness), and vegetation parameters (e.g., Leaf Area Index (LAI), Normalized Difference Vegetation Index (NDVI), Vegetation Water Content (VWC), and biomass) [19,29]. In recent decades, several complex models such as the Michigan Canopy Scattering Model (MIMICS) [31], the Tor Vergata model [32], a first-order radiative transfer model from Quast [33,34], and a Wheat Canopy Scattering Model (WCSM) [27] have been developed for modeling the electromagnetic scattering of different vegetation types by using the first or second order of the RT equation.…”