Digital mapping of soil organic carbon using remote sensing data: A systematic review
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F23%3A97356" target="_blank" >RIV/60460709:41210/23:97356 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0341816223005003" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0341816223005003</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.catena.2023.107409" target="_blank" >10.1016/j.catena.2023.107409</a>
Alternative languages
Result language
angličtina
Original language name
Digital mapping of soil organic carbon using remote sensing data: A systematic review
Original language description
Soil organic carbon (SOC) has attracted a lot of attention in the soil science community. Freely available remote sensing data combined with advanced digital soil mapping (DSM) techniques has led to a better understanding and management of SOC. This paper has considered the published literature with a focus on digital mapping of SOC using remote sensing data within 2010 to 2023 intervals. The objective was to consider all the important aspects of SOC prediction and mapping, including different land-use types, DSM algorithms, environmental variables, and remote sensing data sources. According to this review conducted on the 217 papers, cropland was the most popular type of land use. Regarding the DSM algorithms, random forest (RF) appeared in the largest number of studies. The terrain and spectral variables derived from the digital elevation model (DEM) and remote sensing images, were the highest demanding among all those used as input predictors. In addition, satellite platforms provided the largest portion of the remote sensing data used for the calibration of DSM models. This review provides quantitative insight into recent trends of SOC digital mapping using remote sensing technology while suggesting some directions for future development of the topic.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
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
0341-8162
Volume of the periodical
232
Issue of the periodical within the volume
NOV 2023
Country of publishing house
DE - GERMANY
Number of pages
11
Pages from-to
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UT code for WoS article
001046820400001
EID of the result in the Scopus database
2-s2.0-85166027232