scholarly journals Burgess, T.M. & Webster, R. 1980. Optimal interpolation and isarithmic mapping of soil properties. I. The semi-variogram and punctual kriging. Journal of Soil Science , 31, 315-331.

2019 ◽  
Vol 70 (1) ◽  
pp. 7-10 ◽  
Author(s):  
R. M. Lark ◽  
G. B. M. Heuvelink ◽  
T. F. A. Bishop
Keyword(s):  
Soil Properties ◽  
Soil Science ◽  
Optimal Interpolation ◽  
Punctual Kriging

Regional characterisation of soil properties by combining soil science and hyperspectral and thermal remote sensing: A technical overview of lab and field remote sensing methods

2021 ◽  
Author(s):  
Richard Mommertz ◽  
Lars Konen ◽  
Martin Schodlok
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Regional Scale ◽  
Arable Land ◽  
Soil Mapping ◽  
Soil Science ◽  
Near Surface ◽  
Soil Parameter ◽  
The Impact ◽  
Parameter Retrieval

<p>Soil is one of the world’s most important natural resources for human livelihood as it provides food and clean water. Therefore, its preservation is of huge importance. For this purpose, a proficient regional database on soil properties is needed. The project “ReCharBo” (Regional Characterisation of Soil Properties) has the objective to combine remote sensing, geophysical and pedological methods to determine soil characteristics on a regional scale. Its aim is to characterise soils non-invasive, time and cost efficient and with a minimal number of soil samples to calibrate the measurements. Konen et al. (2021) give detailed information on the research concept and first field results in a presentation in the session “SSS10.3 Digital Soil Mapping and Assessment”. Hyperspectral remote sensing is a powerful and well known technique to characterise near surface soil properties. Depending on the sensor technology and the data quality, a wide variety of soil properties can be derived with remotely sensed data (Chabrillat et al. 2019, Stenberg et al. 2010). The project aims to investigate the effects of up and downscaling, namely which detail of information is preserved on a regional scale and how a change in scales affects the analysis algorithms and the possibility to retrieve valid soil parameter information. Thus, e.g. laboratory and field spectroscopy are applied to gain information of samples and fieldspots, respectively. Various UAV-based sensors, e.g. thermal & hyperspectral sensors, are applied to study soil properties of arable land in different study areas at field scale. Finally, airborne (helicopter) hyperspectral data will cover the regional scale. Additionally forthcoming spaceborne hyperspectral satellite data (e.g. Prisma, EnMAP, Sentinel-CHIME) are a promising outlook to gain detailed regional soil information. In this context it will be discussed how the multisensor data acquisition is best managed to optimise soil parameter retrieval. Sensor specific properties regarding time and date of acquisition as well as weather/atmospheric conditions are outlined. The presentation addresses and discusses the impact of a multisensor and multiscale remote sensing data collection regarding the results on soil parameter retrieval.</p><p> </p><p>References</p><p>Chabrillat, S., Ben-Dor, E. Cierniewski, J., Gomez, C., Schmid, T. & van Wesemael, B. (2019): Imaging Spectroscopy for Soil Mapping and Monitoring. Surveys in Geophysics 40:361–399. https://doi.org/10.1007/s10712-019-09524-0</p><p>Stenberg, B., Viscarra Rossel, R. A., Mounem Mouazen, A. & Wetterlind, J. (2010): Visible and Near Infrared Spectroscopy in Soil Science. In: Donald L. Sparks (editor): Advances in Agronomy. Vol. 107. Academic Press:163-215. http://dx.doi.org/10.1016/S0065-2113(10)07005-7</p>

scholarly journals Diagnostic role of soil physical properties of forest biogeocoenoses of the Ukrainian steppe zone

2018 ◽  
Vol 29 (2) ◽  
Author(s):  
V. A. Gorban
Keyword(s):  
Physical Properties ◽  
Soil Properties ◽  
Granulometric Composition ◽  
Steppe Zone ◽  
Diagnostic Value ◽  
Soil Physical Properties ◽  
Soil Science ◽  
Pedotransfer Functions ◽  
Diagnostic Feature ◽  
Aggregate Composition

For the current stage of the development of soil science it is relevant to search for objectively existing interactions between the various soil properties. Solving this issue most appropriately should be based on the establishment of pedotransfer functions. Pedotransfer functions appeared at the time of the birth of quantitative soil science, when one of the properties of the soil tried to predict others when it became clear that everything in the soil is interrelated when it was established that there is a well-defined number of fundamental, basic properties of the soil, which is basically defines its other properties. Accordingly, the purpose of our work is to establish the diagnostic value of the individual soil physical properties of forest biogeocoenoses of the steppe by means of determining the existing interconnections between them and other properties and characteristics of these soils. The solution of this issue is one of the tasks of developing research on the soil physical properties of forest biogeocoenoses of the Ukrainian steppe zone. The diagnostic value of granulometric and structural-aggregate composition, density and permeability for determining the general state of soils due to the existence of certain interactions between the indicated parameters and other soil properties is considered. The granulometric composition is a fundamental soil characteristic that determines not only the physical state, but also all the main soil properties and regimes of forest biogeocoenoses of the Ukrainian steppe zone. The structural and aggregate composition is an important complex diagnostic feature of chernozem, which helps to reveal the peculiarities of their genesis under the influence of forest vegetation, in particular as a result of changes in the content and composition of organic matter, exchange cations, the influence of root vegetation systems, etc. The soil density, due to existing interactions with other soil properties, is an important diagnostic feature that reflects the features of their genesis and regimes, which determines the specificity of the ecological functions of the soils of forest biogeocoenoses of the Ukrainian steppe zone. Water permeability can be considered as a complex characteristic of soils, which to a certain extent reflects their granulometric composition, porosity, structural and aggregate composition, determines the features of the water-air regime. The differences of physical properties of zonal chernozems and chernozems, the genesis of which are connected with artificial and natural forest biogeocoenoses within the steppe zone of Ukraine, are analyzed. The relevance of the further search for relationships between physical indicators that are easily and promptly analyzed, and other soil properties for expanding diagnostic possibilities with respect to their genesis is pointed out.

scholarly journals Evaluating the potential of Genetic Programming as an exploratory data analysis in soil science

2018 ◽  
Author(s):  
Lorenzo Menichetti ◽  
Alberto Tonda
Keyword(s):  
Data Analysis ◽  
Soil Respiration ◽  
Genetic Programming ◽  
Soil Properties ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Symbolic Regression ◽  
Environmental Modeling ◽  
Soil Science ◽  
Pedotransfer Functions

Genetic Programming is a powerful optimization technique, able to deliver high-quality results in several real-world problems. One of its most successful applications is symbolic regression, where the objective is to find a suitable expression to model the underlying relationship between data points, with no aprioristic assumptions. In this paper, we propose the application of a Genetic Programming technique to a dataset on soil respiration and soil properties, in order to investigate possible influences of soil properties on soil respiration through symbolic regression. The best candidate models obtained by the technique are then studied to determine possible differences in the relationships related to environmental factors. Recurring patterns in the best solutions proposed by the search algorithm are identified, and the suitability of symbolic regression in soil science is evaluated and discussed. Genetic Programming proves to be an extremely promising data mining technique for soil scientists, as it is able to uncover relationships that could otherwise remain hidden, while remaining completely neutral and bias-free. We suggest its application for routine data analysis, as the technique presents particular interest for environmental modeling and development of pedotransfer functions.

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