Naftaly Goldshleger

Spectral properties and hydraulic conductance of soil crusts formed by raindrop impact

In this study, a controlled spectral investigation of the properties of structural crust, using infiltration rate as an indicator, was carried out, on a grumusol (typic chromoxerets) soil. The scope of this paper is to investigate the spectral relationship between structural crust and the infiltration rate and some related properties of a grumusol soil. Structural crust is a thin compact layer generated on the soils surface after rainstorm events due to raindrop energy. The crust, which is a result of physical segregation and rearrangement of soil particles, affects some of the soils physical properties, such as infiltration, run-off and soil erosion. A set of soil samples was subjected in the laboratory to increased levels of cumulative energy from a simulated rainstorm, while measuring the infiltration rate. The result was a set of soil samples with increased levels of crusting and correspondingly reduced infiltration rates. After drying the soil samples, their spectral parameters across the SWIR region (1.2 w m-2.4 w m) were studied in the laboratory. Empirical relations were found between the infiltration rate and reflectance values (either in raw or in first derivative domains). A spectral ratio manipulation, using a fog type rain treatment (characterized as having no rain energy) as reference, confirmed that, within the spectrum, changes in both albedo and absorption enabled the crust to be detected using reflectance radiation. This is basically because fine (mostly clay) mineral enrichment processes occurred at the surface of the crusted soil. These minerals (montmorillonite, calcite) are spectrally active across the selected spectral region. Although further study is required to fully account for other soils, rainstorm energies and water qualities, this technique suggests great potential as a tool for rapid, non-destructive, in situ assessment of crusted soil properties.

SOIL REFLECTANCE AS A TOOL FOR ASSESSING PHYSICAL CRUST ARRANGEMENT OF FOUR TYPICAL SOILS IN ISRAEL

Investigation of soil structural crust reflectance across the NIR-SWIR spectral region was conducted to account for the possibility of remotely sensed soil crust-related properties such as water infiltration. The raindrop energy disintegrates the soil aggregates and rearranges soil particles within the structural crust of the upper soil layer. The generation of structural crust affects the physical properties of the soil and can be identified by significant color changes on the soil’s surface. Spectral differences observed on the crusted soil are caused by the rearrangement of texture and clay minerals during raindrop events. In this study, four soils were subjected to increasing levels of raindrop energy in a rain simulator device with their reflectances measured concurrently. Two wavelengths representing particle size arrangement and clay content at 1.7 μm and 2.2 μm, respectively, were used to generate a dynamic chart of the crust formation. Soil mineralogy was found to be a major factor in the crust formation. In the clayey soils, two identical stages were identified: decreased albedo at 1.7 μm and an increase in the 2.2 μm absorption features. By employing this technique, a washing out of clay from the crust zone over the high raindrop energy was observed. However, in sandy soil, the predominant quartz particles created a different pattern. Because the coarse quartz particles reflect more energy, reverse reciprocal relationships with clay enrichment were found. Based on the relationship between raindrop energy and water infiltration rate (IR), a spectral model for predicting the IR was constructed. Three spectral domains were examined: reflectance (R), the first derivative of the reflectance (R’), and the ratio between reflectance of a given treatment and the reflectance of the non-crusted fog treated soil (R/Rfog). A significant relationship was discovered between the IR and the reflectance properties (R’ and ratio), suggesting clay content as the significant indicator of crust status. The results of this study show that soil reflectance can shed light on the structural crusting process. It is further suggested that this methodology may be used as well at high signal to noise ratios, employing airborne and space-borne hyperspectral sensors.

Monitoring of agricultural soil degradation by remote-sensing methods: a review

Agricultural land degradation is a global problem that severely hampers the production of food needed to sustain the growing world population. Mapping of soil degradation by remote sensing is instrumental for understanding the spatial extent and rate of this problem. Methods aimed at detecting soil loss, soil drying, and soil-quality deterioration have been demonstrated in numerous studies utilizing passive and active remote sensors. This review presents a short description of each form of soil degradation, including data regarding known extents and rates, and then reviews the methods with respect to direct and indirect modelling approaches. Two types of obstacles to achieving wide regional detection of soil degradation are revealed. The first concerns the complex and non-unique relationships between remote-sensing indicators and different soil properties, such as roughness, soil moisture (SM), soil salinity, and organic matter content. The second concerns the difficulties involved in acquiring data on subsurface soil properties. In view of these difficulties, we recommend expanding the use of phenomenological models capable of estimating soil-degradation potential according to combinations of environmental conditions, thus enabling remote-sensing efforts to be focused on local areas where the environmental threat is highest. The second avenue for improving the contribution of remote sensing on a wide regional scale involves the application of integrative methods, such as those based on hyperspectral, multisensory, and multitemporal approaches, as well as those that incorporate environmental information (such as topography, soil types, and precipitation).

Generalising relationships between runoff–rainfall coefficients and impervious areas: an integration of data from case studies in Israel with data sets from Australia and the USA

This study explores the generalised relationships between the proportion of impervious areas and storm runoff coefficient (RR) that characterises the current global trends of expansion and densification of urban zones. For this purpose there is an integrated database representing about 800 urban storm events in diverse locations around the world: from Israel and from detailed rainfall–runoff measurements in Australia and USA. Special attention is given here to the experience gathered in two case studies in Israel with information of surface imperviousness derived from remote sensing data, including air photographs and satellite images. Despite differences in measurement systems and methodologies between sites, there was evidential support for a new generalised three-phase model where in up to 20% of impervious area there are no expected major runoff events, a major enhancement in runoff–rainfall response to impervious area increase between 20% and 40%, and 1:1 relationship between 40% and 100% impervious area. This model may be implemented on a wide regional scale, based on remote sensing derived impervious areas for mapping urban areas with high flooding risk. Urban planning may incorporate this model for determining expected storm runoff levels and incorporating this information to derive appropriate hydrological solutions.

Estimating Pasture Quality of Fresh Vegetation Based on Spectral Slope of Mixed Data of Dry and Fresh Vegetation—Method Development

The main objective of the present study was to apply a slope-based spectral method to both dry and fresh pasture vegetation. Differences in eight spectral ranges were identified across the near infrared-shortwave infrared (NIR-SWIR) that were indicative of changes in chemical properties. Slopes across these ranges were calculated and a partial least squares (PLS) analytical model was constructed for the slopes vs. crude protein (CP) and neutral detergent fiber (NDF) contents. Different datasets with different numbers of fresh/dry samples were constructed to predict CP and NDF contents. When using a mixed-sample dataset with dry-to-fresh ratios of 85%:15% and 75%:25%, the correlations of CP (R2 = 0.95, in both) and NDF (R2 = 0.84 and 0.82, respectively) were almost as high as when using only dry samples (0.97 and 0.85, respectively). Furthermore, satisfactory correlations were obtained with a dry-to-fresh ratio of 50%:50% for CP (R2 = 0.92). The results of our study are especially encouraging because CP and NDF contents could be predicted even though some of the selected spectral regions were directly affected by atmospheric water vapor or water in the plants.

Generalising urban runoff and street network density relationship: A hydrological and remote-sensing case study in Israel

This paper describes the relationship between urban road network density and urban runoff coefficient in the coastal plain of Israel. The study assessed 30 years of recorded changes in rainfall-runoff coefficient in an urban catchment in the coastal plain of Israel. Rain and runoff were measured and sampled at measurement stations. Insight into the factors affecting urban runoff was gained by applying GIS and remote-sensing analysis, including street network density assessment and urban impermeable area recognition. Street network density was found to be a reliable indicator for both urban impermeability (R2 = 0.83) and runoff (R2 = 0.92) change dynamics, showing a strong linear correlation. Thus the urban street drainage network can help explain the dynamics of change in urban runoff. To prevent urban flooding hazards, and to help conserve water resources, regional planners should take into consideration road network density in built-up areas.

Spectral Slope as an Indicator of Pasture Quality

In this study, we develop a spectral method for assessment of pasture quality based only on the spectral information obtained with a small number of wavelengths. First, differences in spectral behavior were identified across the near infrared–shortwave infrared spectral range that were indicative of changes in chemical properties. Then, slopes across different spectral ranges were calculated and correlated with the changes in crude protein (CP), neutral detergent fiber (NDF) and metabolic energy concentration (MEC). Finally, partial least squares (PLS) regression analysis was applied to identify the optimal spectral ranges for accurate assessment of CP, NDF and MEC. Six spectral domains and a set of slope criteria for real-time evaluation of pasture quality were suggested. The evaluation of three level categories (low, medium, high) for these three parameters showed a success rate of: 73%–96% for CP, 72%–87% for NDF and 60%–85% for MEC. Moreover, only one spectral range, 1748–1764 nm, was needed to provide a good estimation of CP, NDF and MEC. Importantly, five of the six selected spectral regions were not affected by water absorbance. With some modifications, this rationale can be applied to further analyses of pasture quality from airborne sensors.

First results from a millimetre-wave measurement of soil moisture content

The method presented in this letter enables, for the first time, quantitative assessment of soil moisture content in the upper part of the root zone using remote sensing. The data are obtained in a short time and at low cost. We present results of measurements following water application at various cumulative energies by Morins rainfall simulator. The method is based on the emerging technology of millimetre waves, providing improved resolution of the subsurface concurrent with surface mapping. Development and use of the tools described herein will make it easier to understand processes occurring at the soil–water interface, such as soil crusting, penetration, run-off and erosion. We emphasize the difference between the suggested technique based on microwave radiation at millimetre wavelengths with excellent resolution and microwave radiation with a wavelength of tens of centimetres and thus reduced resolution.

Studying Vegetation Salinity: From the Field View to a Satellite-Based Perspective

Salinization of irrigated lands in the semi-arid Jezreel Valley, Northern Israel results in soil-structure deterioration and crop damage. We formulated a generic rule for estimating salinity of different vegetation types by studying the relationship between Cl/Na and different spectral slopes in the visible–near infrared–shortwave infrared (VIS–NIR–SWIR) spectral range using both field measurements and satellite imagery (Sentinel-2). For the field study, the slope-based model was integrated with conventional partial least squares (PLS) analyses. Differences in 14 spectral ranges, indicating changes in salinity levels, were identified across the VIS–NIR–SWIR region (350–2500 nm). Next, two different models were run using PLS regression: (i) using spectral slope data across these ranges; and (ii) using preprocessed spectral reflectance. The best model for predicting Cl content was based on continuum removal reflectance (R2 = 0.84). Satisfactory correlations were obtained using the slope-based PLS model (R2 = 0.77 for Cl and R2 = 0.63 for Na). Thus, salinity contents in fresh plants could be estimated, despite masking of some spectral regions by water absorbance. Finally, we estimated the most sensitive spectral channels for monitoring vegetation salinity from a satellite perspective. We evaluated the recently available Sentinel-2 imagery’s ability to distinguish variability in vegetation salinity levels. The best estimate of a Sentinel-2-based vegetation salinity index was generated based on a ratio between calculated slopes: the 490–665 nm and 705–1610 nm. This index was denoted as the Sentinel-2-based vegetation salinity index (SVSI) (band 4 − band 2)/(band 5 + band 11).

Empirical Model for Backscattering at Millimeter-Wave Frequency by Bare Soil Subsurface With Varied Moisture Content

This letter presents results of the angular variation of millimeter-wave-radiation backscattering coefficient for various levels of soil moisture content. The research sets the basis for a method, which enables assessment of the soil-moisture content in the upper part of the shallow root zone. Further development of the method should provide a microprofile measurement of soil moisture up to the root zone depth. The method is based on the emerging technology of millimeter waves, providing improved spatial resolution of the subsurface concurrent with surface mapping. The development and the use of the method described herein will make it easier to analyze and understand processes governing the soil-water interface, such as soil crusting, infiltration, runoff, and soil erosion.