High-resolution mapping of in-depth soil moisture content through a laboratory experiment coupling a spectroradiometer and two hyperspectral cameras

Abstract

A laboratory experiment is set up to study both surface and in-depth soil moisture content (SMC). For that purpose, an aquarium is filled successively with two soils, a clay loam and a sand. Reflectance spectra are acquired in the solar domain (400-2400 nm) on the soil surface using an ASD FieldSpec 3 HR spectroradiometer and in-depth through the aquarium glass wall using two hyperspectral cameras. Successive amounts of water ranging from low to heavy rainfall in a temperate region are uniformly poured into the aquarium. The MARMITforSMC method based on the MARMIT (MultilAyer Radiative Transfer Model for soIl reflecTance) model is applied to each reflectance spectrum to determine gravimetric SMC. In particular, vertical profiles of SMC are provided with unprecedented spatial accuracy (0.287 mm). The results are compared with volumetric SMC measured by two time-domain reflectometry (TDR) sensors. The in-depth SMC image produced on the sand shows lower values within the first 2cm (5%) than below (17%). In contrast, the SMC image produced on the clay loam shows evenly distributed values whatever the position in the aquarium, even 1h after moistening. The difference in grain size between the soils explains this result.

Estimating Regional Soil Moisture Distribution Based on NDVI and Land Surface Temperature Time Series Data in the Upstream of the Heihe River Watershed, Northwest China

“…Estimation of 0-100 cm soil moisture by the principle of maximum entropy achieved better results than those obtained by the exponential decaying function in the Southeastern USA, a subtropical humid area [29]. With the measurement of the spectral characteristics of soil profile, Balet et al [30] inferred soil moisture conditions based on the MARMIT (MultilAyer Radiative Transfer Model for soIl reflecTance) model. Over the past decades, MODIS LST and NDVI products have been widely used in agriculture, ecosystem and global change research [31,32].…”

Possibility of Zhuhai-1 Hyperspectral Imagery for Monitoring Salinized Soil Moisture Content Using Fractional Order Differentially Optimized Spectral Indices

“…Soil moisture is an important factor that affects plant growth and development, and it is also a key indicator for evaluating soil quality and judging farmland moisture [1]. However, soil moisture content (SMC) is also one of the most easily changed and contaminated indicators in various physical and chemical properties of soil, and thus it is urgent to explore an efficient and reliable large-area observation method [2]. Remote sensing technology has unique advantages in large-area observations.…”

Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

“…A number of approaches have been taken to model soil moisture content from spectral data, including the use of spectral indices [20][21][22] , band depth of water absorption features 20,23 , and simplified radiative transfer models, such as those based on a two-stream approximation for diffuse reflectance using the Kubelka-Monk model 24,25 . In this work, we employ a recently developed radiative transfer model that incorporates the possibility of a directional source and has produced promising results in a laboratory setting 26,27 . While we considered more than one of these alternative approaches that could in principle be applied to hyperspectral imagery, the primary models that address the problem at hand of modeling water in the sediment pore space were the two-stream approach based on Kubelka-Munk (K-M) theory 24 and the model which we analyze in depth in this work, the multilayer radiative transfer model of soil reflectance (MARMIT) 26,27 .…”

“…In this work, we employ a recently developed radiative transfer model that incorporates the possibility of a directional source and has produced promising results in a laboratory setting 26,27 . While we considered more than one of these alternative approaches that could in principle be applied to hyperspectral imagery, the primary models that address the problem at hand of modeling water in the sediment pore space were the two-stream approach based on Kubelka-Munk (K-M) theory 24 and the model which we analyze in depth in this work, the multilayer radiative transfer model of soil reflectance (MARMIT) 26,27 . Comparisons of these two approaches demonstrated that MARMIT obtained more robust results.…”

“…MARMIT 26,27 makes the simplifying assumption that the embedded SMC can be treated by means of a layer of equivalent water thickness, with an assumed efficiency parameter, which weights the fraction of wet surface area present in a given location. The model treats soil and water as separate layers and uses the familiar Fresnel formalism for reflection and transmission at the boundaries of both the soil layer and the equivalent water layer.…”