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Summary of Automated Soil Sampling and Analysis Techniques Assignment Help

Write about automated soil sampling and analysis techniques from this two papers attached only Discuss about any of this topics if its available in this two papers attached: Soil sampling technique Soil compacation Soil moisture content Remote sensing techniques Soil ph -note if some topics not available in the two papers attached ignore the topic

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The paper investigates the soil sampling technique used in soil moisture content. The paper includes experimental data of microwave remote sensing for soil moisture content retrieval. Different satellite based sampling and analysis is observed and the results are described.

Soil moisture rectification using field network

The remote sensing analysis is exceptionally tactical for soil hydrology of the Earth's surface. Ground-based soil moisture sensing processes for invasive and noninvasive quality of soil are monitored by satellite based remote sensing. This analysis is highly impactful and used globally for validation. A review is provided by (Lindell and Long. 2016) of several noninvasive soil analysis and measurement techniques and processing networks. Several soil moisture analysis using satellite techniques are common in surface hydrology such as Carbon Ray neutron Probe (CRNP). The investigation includes different techniques used in monitoring the soil moisture content and the outcomes are compared. Launching of the first satellite moisture products with real time contrast was discovered with the invention of SftAP-Mission.

However, a usual automated ingestion of situ data comparing weekly with other situ resources is observed in SftAP. Pixel-scale watersheds and other bigger sparse networks are the common resources used to deliver a range of soil moisture content every week. These resources are well versed of the current soil moisture retention technology. Estimation of errors in each measurement are recorded for every week and later the data is compared weekly basis. For estimation of the interoperability and accuracy of different networks, various sensors are used includes in situ sensor testbed. CRNP based validations are used in recent times for satellite based soil moisture testing. Different networks COSftOS, TERENO and COSftOS-UK give solutions to footprint-scale data observed in comparison of typical scale-point observations. Observation of backscatter, intensity temperature and retention of soil moisture across different time scales is necessary (Laiolo et al., 2016).

Soil moisture retrieval using satellites

In addition to satellite- and ground-based measurements, experiments are done on different time scales on various land surface techniques by climatology and atmospheric forcing for estimation of soil moisture content. Alternative accessories like triple collocation process via various satellite products and the ratio output of noise have been utilized for validation and rectification of soil moisture. In highly heterogeneous landscape situations performance of current radiative transfer models are not that effective when tested for soil moisture retrieval of satellites SftOs and SftAP (Rüdiger et al., 2016). These results are dependable and vary with different climate conditions. The techniques involves identification of parameters i.e. roughness elevation of the surface, vegetation water control or VWC and soil moisture. Based on these parameters it can be stated that a uniform RTft come within reach for soil moisture retrieval can have drawbacks and improvement for accuracy exists.

Different outputs in soil moisture remote sensing

Satellites provides important information that are related to hydrological, meteorological, agricultural and use of land and changing of applications require presentation of small-scale land surfaces of spatial heterogeneity as hydrological procedures at different scales ranging from centimeters to kilometers. Remote scale sensing provide soil moisture dynamics in large scale, and for in situ observations it point outs the scales and the modeling scales which is from few hundred meters to kilometers that leads to disturbance in performance of land surface hydrologic model. In order to improve hydrologic and satellite based soil moisture applications should be optimized to appropriate level (Cosh, M et al., 2017).

In ecological processes root-zone soil moistures plays an important role at individual plant to system scales. Root-zone soil moisture content is characterized by texture of the soil, precipitation patterns, and water holding capacity of soil, types of land surface as it can affect infiltration and runoff, and land cover and vegetation that lead to deep percolation and evaporation from soil. The satellite footprint measures soil moisture and it may be coarse and errors are formed while measuring local scale of field, watershed and catchment that may fit into an inaccurate scale of hydrologic fluxes at regional level, they are important for water resource assessment, hydro climatic predictions and agriculture. Satellite soil moisture (SMAP and SMOS) products are utilized to develop more efficient scaling tools. Studies have investigated about scale dependence of dominant physical controls on soil moisture distribution that has been undertaken. With the help of wavelet analysis that has airborne remote sensing data, it can observe strength of physical controls on different types of soil moisture evolved in different geographies and hydro climates (Zhao and A. 2015).

Remote Sensing in Near-Real-Time for the products of Soil Moisture for Management and Operation

At near real time ASCAT data is been available over satellite application facilities from many years. In numerical prediction of weather, operational utilization has gone advanced. There are more examples of ASCAT applications that are improvement of rainfall, identification of flash flood areas, and prediction of floods, discharge estimates, and identification of vegetation in drought. The ESA in March 2016 released new SMOS Level 2 soil moisture product. For the improvement of numerical forecasting of weather, flood prediction and drought, dissemination of fast soil moisture product got more importance. Remotely sensed data gives more unprecedented advantages, there are some challenges in terms of time resolution, shallow penetration depth, coarse space, and mismatched hydrologic principles persist. To improve accuracy and reduce uncertainty of soil moisture products and their uses, data assimilation schemes have to be updated and up-downscaling functions. Development of adaptive scaling, modeling schemes and data assimilation can be used for many societal applications for many years (Piles et al., 2016).


There are many uncertainties, which is related to validation, retrieval, climate-specific bias persist, remote sensing of soil moisture however it has matured in past few years. There are various applications and among the ruling ones are remotely sensed soil moisture for crop growth models and conditions of soil hydrology and agricultural water management.

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