Multi-decadal satellite monitoring of soil carbon and its role in farm carbonfootprint: a case study for the Czech Republic

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F25%3A00639646" target="_blank" >RIV/86652079:_____/25:00639646 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11310/25:10515669

Result on the web

<a href="https://www.tandfonline.com/doi/full/10.1080/22797254.2025.2562069" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/22797254.2025.2562069</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/22797254.2025.2562069" target="_blank" >10.1080/22797254.2025.2562069</a>

Result language

angličtina

Original language name

Multi-decadal satellite monitoring of soil carbon and its role in farm carbonfootprint: a case study for the Czech Republic

Original language description

This paper presents a study on the retrieval of long-term trends in soil organic carbon (SOC) using advanced time-series analysis applied to multi-temporal Landsat and Sentinel-2 satellite data processed in the form of 5-year bare soil composites. The research is focused on the Czech Republic, a region that is characterized by a diverse range of soil types and a variety of agricultural practices. The study integrates a support vector regression algorithm with soil type mapping to construct a model of soil organic carbon (SOC) and their long-term trends at different spatial scales, including laboratory and field spectroscopy and Earth observation (EO) scales. The highest accuracy of SOC retrieval was obtained for soil optical properties measured using a field spectroradiometer (LAB2LAB case) for a scenario involving wet soil (r(2) = 0.73), followed by satellite retrievals (EO2EO scenario) with r(2) = 0.63. When applied retrospectively to Landsat satellite observations, long-term SOC trends from Landsat observations between 1985 and 2023 were retrieved across different soil types, thereby highlighting the influence of soil characteristics on these trends. Furthermore, the methodology proposed offers a novel approach to evaluating the carbon footprint at the farm level, integrating soil organic carbon dynamics into carbon accounting systems.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20705 - Remote sensing

Project

<a href="/en/project/EH22_008%2F0004635" target="_blank" >EH22_008/0004635: AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

European Journal of Remote Sensing

ISSN

2279-7254

e-ISSN

2279-7254

Volume of the periodical

58

Issue of the periodical within the volume

1

Country of publishing house

IT - ITALY

Number of pages

23

Pages from-to

2562069

UT code for WoS article

001574733700001

EID of the result in the Scopus database

2-s2.0-105016649837