Relationship Between Soil Moisture Content and Soil Surface Reflectance

Abstract

Depending on the topography and soil characteristics of an area, soil moisture, an important factor in crop productivity, can be quite variable over the land surface. Thus, a method for determination of soil moisture without the necessity for exhaustive manual measurements would be beneficial for characterizing soil moisture within a given region or field. In this study, soil surface reflectance data in the visible and near−infrared regions were analyzed in conjunction with surface moisture data in a field environment to determine the nature of the relationship between the two, and to identify potential methods for estimation of soil moisture from remotely sensed data in these wavelengths. Results indicate that it is feasible to estimate surface (0 to 7.6 cm) soil moisture from visible and near−infrared reflectance, although estimating moisture regimes rather than precise water content is perhaps more likely. Furthermore, an exponential model was appropriate to describe soil moisture from spectral reflectance data. In particular, the visible region of the electromagnetic spectrum works well with such a model. A partial least squares analysis with improved R 2 values over the single−band models indicated that mulitspectral data may add more useful information about soil moisture as compared to single−band data. The results also suggested that the performance of reflectance models for moisture estimation is a function of soil types; the estimation results were better for the lighter of the two soils in this study.

Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology: A Review

“…The direct detection of soil salinity becomes applicable and much easier for bare soils and/or whenever salt-related symptoms (e.g., crusts) and scattered vegetation are visible on the surface; in these cases, information such as salt types and quantity as well as the crust thickness can be provided based on the soil surface spectral signatures [67,101]. Yet, the direct deduction of soil salinity in arid and semi-arid regions that are characterized by dense vegetation cover would be difficult, as the vegetation will cause spectral mixing [102,103].…”

Assessment of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery and Artificial Neural Networks

“…The possibility of estimating SSM (0-7.6 cm) from visible and near-infrared (NIR) reflectance data has also been demonstrated [11]. Optical and thermal remote-sensing techniques or passive and active microwave sensors offer large-scale monitoring of SSM [11][12][13].…”

“…The possibility of estimating SSM (0-7.6 cm) from visible and near-infrared (NIR) reflectance data has also been demonstrated [11]. Optical and thermal remote-sensing techniques or passive and active microwave sensors offer large-scale monitoring of SSM [11][12][13]. Some meteorological satellites, such as the Advanced Microwave Scanning Radiometer (AMSR-E), the European Remote Sensing (ERS) satellite scatterometer or the Meteorological Satellite (METEOSAT), offer the possibility of monitoring operational SSM [3].…”

“…However, one of the major drawbacks of the Ts-VI method is that, in order to have enough points in a remote-sensing image to use in the determination of the boundaries of extreme conditions, a sufficiently large number of pixels must be sampled. This limitation is a handicap when dealing with smaller scale imagery on the order of the size of a typical farm field [11].…”

Improvement of Soil Moisture Retrieval from Hyperspectral VNIR-SWIR Data Using Clay Content Information: From Laboratory to Field Experiments

“…Nevertheless, these data have two main limitations: their high sensitivity to surface roughness [27] for SAR (Synthetic Aperture Radar) sensor and their coarse spatial resolution. However, numerous spectroscopic studies have been conducted to characterize the SMC influence on the spectral reflectance mainly with laboratory and with few in-situ measurements [20,28,29]. Angström [30] demonstrated through laboratory measurements that soil moisture content had an impact on the behavior of soil spectral reflectances in the solar domain.…”