Soil Organic Carbon Mapping Using Multispectral Remote Sensing Data: Prediction Ability of Data with Different Spatial and Spectral Resolutions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F19%3A80155" target="_blank" >RIV/60460709:41210/19:80155 - isvavai.cz</a>
Alternative codes found
RIV/00027049:_____/19:N0000112
Result on the web
<a href="https://www.mdpi.com/2072-4292/11/24/2947/htm" target="_blank" >https://www.mdpi.com/2072-4292/11/24/2947/htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/rs11242947" target="_blank" >10.3390/rs11242947</a>
Alternative languages
Result language
angličtina
Original language name
Soil Organic Carbon Mapping Using Multispectral Remote Sensing Data: Prediction Ability of Data with Different Spatial and Spectral Resolutions
Original language description
The image spectral data, particularly hyperspectral data, has been proven as an efficient data source for mapping of the spatial variability of soil organic carbon (SOC). Multispectral satellite data are readily available and cost-effective sources of spectral data compared to costly and technically demanding processing of hyperspectral data. Moreover, their continuous acquisition allows to develop a composite from time-series, increasing the spatial coverage of SOC maps. In this study, an evaluation of the prediction ability of models assessing SOC using real multispectral remote sensing data from different platforms was performed. The study was conducted on a study plot (1,45 km2) in the Chernozem region of South Moravia (Czechia). The adopted methods included field sampling and predictive modeling using satellite multispectral Sentinel-2, Landsat-8, and PlanetScope data, and multispectral UAS Parrot Sequoia data. Furthermore, the performance of a soil reflectance composite image from Sentinel-2 da
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)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Remote Sensing
ISSN
2072-4292
e-ISSN
2072-4292
Volume of the periodical
11
Issue of the periodical within the volume
24
Country of publishing house
CH - SWITZERLAND
Number of pages
23
Pages from-to
1-23
UT code for WoS article
000507333400063
EID of the result in the Scopus database
2-s2.0-85077852092