Agricultural Sandbox NL: A national-scale database of parcel-level, processed Sentinel-1 SAR data

Synthetic Aperture Radar (SAR) data handling, processing, and interpretation are barriers preventing a rapid uptake of SAR data by application specialists and non-expert domain users in the field of agricultural monitoring. To improve the accessibility of Sentinel-1 data, we have generated a reduced-volume, multi-year Sentinel-1 SAR database. It includes mean and standard deviation of VV, VH and VH/VV backscatter, pixel counts, geometry, crop type, local incidence angle and azimuth angle at parcel-level. The database uses around 3100 Sentinel-1 images (5 TB) to produce a 12 GB time series database for approximately 770,000 crop parcels over the Netherlands for a period of three years. The database can be queried by Sentinel-1 system parameters (e.g. relative orbit) or user application-specific parameters (e.g. crop type, spatial extent, time period) for parcel level assessment. The database can be used to accelerate the development of new tools, applications and methodologies for agricultural and water related applications, such as parcel-level crop bio-geophysical parameter estimation, inter-annual variability analysis, drought monitoring, grassland monitoring and agricultural management decision-support.

Lateral variations of electrical conductivity in the lower mantle constrained by Swarm and CryoSat-2 missions

The electrical conductivity is an important geophysical parameter connected to the thermal, chemical, and mineralogical state of the Earth’s mantle. In this paper, we apply the previously developed methodology of forward and inverse EM induction modeling to the latest version of satellite-derived spherical harmonic coefficients of external and internal magnetic field, and obtain the first 3-D mantle conductivity models with contributions from Swarm and CryoSat-2 satellite data. We recover degree 3 conductivity structures which partially overlap with the shape of the large low-shear velocity provinces in the lower mantle.

Lateral Variations of Electrical Conductivity in the Lower Mantle Constrained by Swarm and CryoSat-2 Missions

The electrical conductivity is an important geophysical parameter connected to the thermal, chemical, and mineralogical state of the Earth's mantle. In this paper we apply the previously developed methodology of forward and inverse EM induction modelling to the latest version of satellite-derived spherical harmonic coefficients of external and internal magnetic field, and obtain the first 3-D mantle conductivity models with contributions from Swarm and CryoSat-2 satellite data. We recover degree 3 conductivity structures which partially overlap with the shape of the large low-shear velocity provinces in the lower mantle.

Quantifying model structural uncertainty using airborne electromagnetic data

SUMMARY The ability to quantify structural uncertainty in geological models that incorporate geophysical data is affected by two primary sources of uncertainty: geophysical parameter uncertainty and uncertainty in the relationship between geophysical parameters and geological properties of interest. Here, we introduce an open-source, trans-dimensional Bayesian Markov chain Monte Carlo (McMC) algorithm GeoBIPy—Geophysical Bayesian Inference in Python—for robust uncertainty analysis of time-domain or frequency-domain airborne electromagnetic (AEM) data. The McMC algorithm provides a robust assessment of geophysical parameter uncertainty using a trans-dimensional approach that lets the AEM data inform the level of model complexity necessary by allowing the number of model layers itself to be an unknown parameter. Additional components of the Bayesian algorithm allow the user to solve for parameters such as data errors or corrections to the measured instrument height above ground. Probability distributions for a user-specified number of lithologic classes are developed through posterior clustering of McMC-derived resistivity models. Estimates of geological model structural uncertainty are thus obtained through the joint probability of geophysical parameter uncertainty and the uncertainty in the definition of each class. Examples of the implementation of this algorithm are presented for both time-domain and frequency-domain AEM data acquired in Nebraska, USA.

Analysis of the efficiency of models of transition zones to determine oil-saturation factors and position of contact of hydrocarbons with water

The article is devoted to the usage of models of transition zones in the interpretation of geological and geophysical information. These models are graphs of the dependences of oil-saturation factors of the collectors on their height above the level with zero capillary pressure, taking into account the geological and geophysical parameter. These models are not recommended for estimating oilsaturation factors of collectors in the transition zone. The height of occurrence of the collector above the level of zero capillary pressure can be estimated from model of the transition zone that take into account the values of the coefficients of residual water saturation factor of the collectors, but only when the model of the transition zone is confirmed by data capillarimetry studies on the core.

EFFECT OF GEOPHYSICAL PARAMETERS ON ATTENUATION OF CONTAMINANT IN FRESHWATER COASTAL AQUIFERS

<p>Freshwater coastal aquifers can be contaminated by influx of seawater. The study investigated the effect of geophysical parameter such as seepage velocity (<em>v</em>) determined empirically on the mass flux (<em>J</em>) of contaminant through the coastal aquifers. Porosities of the grains were determined and tagged samples A to E. <em>v</em> was obtained in the experimental setup. Results showed that hydraulic gradient ranged between 3.233 to 0.317 while the corresponding values of contaminant <em>J</em> ranged between 0.302 to 5.381 Kgm^-2s^-1 within 60 to 360 seconds. Therefore, the attenuation coefficients of <em>J</em> decreased with increased in flow rate of fluid through the samples.</p>

EFFECT OF GEOPHYSICAL PARAMETERS ON ATTENUATION OF CONTAMINANT IN FRESHWATER COASTAL AQUIFERS

Freshwater coastal aquifers can be contaminated by influx of seawater. The study investigated the effect of geophysical parameter such as seepage velocity (v) determined empirically on the mass flux (J) of contaminant through the coastal aquifers. Porosities of the grains were determined and tagged samples A to E. v was obtained in the experimental setup. Results showed that hydraulic gradient ranged between 3.233 to 0.317 while the corresponding values of contaminant J ranged between 0.302 to 5.381 Kgm-2s-1 within 60 to 360 seconds. Therefore, the attenuation coefficients of J decreased with increased in flow rate of fluid through the samples.

GEOPHYSICAL PARAMETER RETRIEVAL FOR MICROWAVE C BAND SYNTHETIC APERTURE RADAR (SAR) DATASET USING INTEGRAL EQUATION MODEL

<p><strong>Abstract.</strong> The microwave remote sensing is highly useful, as it provides synoptic observation of the Earth’s surface or planetary bodies, regardless of day or night and the atmospheric conditions, propagation through ionosphere with minimum loss. One of the best microwave technology for imaging system is the Synthetic Aperture Radar (SAR) remote sensing. The microwave SAR currently represents the best approach for obtaining spatially distributed geophysical parameter present on the Earth’s surface or planetary bodies. In the present work, geophysical parameters <i>viz.</i>, Soil Moisture, Surface Roughness, Dielectric Constant (&amp;epsilon;) and Backscattering Coefficients (&amp;sigma;⁰) will be retrieved. The modelling makes the process of estimating information beyond the real observation range for data interpretation. In the present paper most widely used modelling techniques for the microwave SAR dataset is an Integral Equation Model (IEM) which is implemented for above said geophysical parameters retrieval. The aim of the present work is to estimate accurate, reliable and skillful measurements of geophysical parameters from the microwave SAR dataset. In the present study microwave C band SAR dataset is used. The overall processing was done by using PolSARPro Ver. 5.0 software. In the present work, geophysical parameters are measured with the help IEM modelling, the statistical parameter and occurrence plane, estimated from the microwave SAR image, which was very helpful for retrieving geophysical parameters. From the overall paper work, it was concluded that the IEM modelling is a one of the realistic modelling methods for retrieving geophysical parameters for microwave C band SAR dataset.</p>