High-resolution agriculture soil property maps from digital soil mapping methods, Czech Republic
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027049%3A_____%2F22%3AN0000019" target="_blank" >RIV/00027049:_____/22:N0000019 - isvavai.cz</a>
Alternative codes found
RIV/60460709:41210/22:92273
Result on the web
<a href="https://www.sciencedirect.com/science/article/abs/pii/S0341816222000108" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S0341816222000108</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.catena.2022.106024" target="_blank" >10.1016/j.catena.2022.106024</a>
Alternative languages
Result language
angličtina
Original language name
High-resolution agriculture soil property maps from digital soil mapping methods, Czech Republic
Original language description
Detailed maps of soil properties are essential for soil protection planning and management; however, creating very high-resolution maps at the national level with sufficient accuracy is a challenging task and remains unavailable for most countries. For the Czech Republic, very high resolution (20 m⋅pixel???? 1) soil property maps (soil organic carbon—SOC, texture, pH, bulk density, soil depth) were created using digital soil mapping methods, combined with a wide database of soil legacy and current samples. The latest approaches were employed for predictive mapping: a quantile random forest model with the determination of prediction intervals, a mosaic of bare soils from Sentinel-2 satellite data, a Gaussian pyramid of terrain attributes, and a buffer distance map. These variables were found to be among the most important in the resulting models. The properties were mapped with an RMSE accuracy of 0.43% SOC, 5.56–11.14% for texture fractions, 0.70 pH, 0.13 g⋅cm???? 3 bulk density, and 20.03 cm for soil depth, thus providing detailed data on soil cover. Greater levels of inaccuracy were found in areas with extreme values, for which further investigation is necessary either through more detailed sampling based on active learning, or adapted methods for enhanced predictive ability.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
40104 - Soil science
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Catena
ISSN
0341-8162
e-ISSN
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Volume of the periodical
2022
Issue of the periodical within the volume
212
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
24
Pages from-to
106024
UT code for WoS article
000791995200001
EID of the result in the Scopus database
2-s2.0-85122989943