Analysis of spatiotemporal variability of C-factor derived from remote sensing data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F18%3A00488990" target="_blank" >RIV/86652079:_____/18:00488990 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989592:15310/18:73587793

Výsledek na webu

<a href="http://dx.doi.org/10.1117/1.JRS.12.016022" target="_blank" >http://dx.doi.org/10.1117/1.JRS.12.016022</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/1.JRS.12.016022" target="_blank" >10.1117/1.JRS.12.016022</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of spatiotemporal variability of C-factor derived from remote sensing data

Popis výsledku v původním jazyce

Soil erosion is an important phenomenon that contributes to the degradation of agricultural land. Even though it is a natural process, human activities can significantly increase its impact on land degradation and present serious limitation on sustainable agricultural land use. Nowadays, the risk of soil erosion is assessed either qualitatively by expert assessment or quantitatively using model-based approach. One of the primary factors affecting the soil erosion assessment is a cover-management factor, C-factor. In the Czech Republic, several models are used to assess the C-factor on a long-term basis based on data collected using traditional tabular methods. This paper presents work to investigate the estimation of both long-term and short-term cover-management factors using remote sensing data. The results demonstrate a successful development of C-factor maps for each month of 2014, growing season average, and annual average for the Czech Republic. C-factor values calculated from remote sensing data confirmed expected trend in their temporal variability for selected crops. The results presented in this paper can be used for enhancing existing methods for estimating C-factor, planning future agricultural activities, and designing technical remediations and improvement activities of land use in the Czech Republic, which are also financially supported by the European Union funds. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

Název v anglickém jazyce

Analysis of spatiotemporal variability of C-factor derived from remote sensing data

Popis výsledku anglicky

Soil erosion is an important phenomenon that contributes to the degradation of agricultural land. Even though it is a natural process, human activities can significantly increase its impact on land degradation and present serious limitation on sustainable agricultural land use. Nowadays, the risk of soil erosion is assessed either qualitatively by expert assessment or quantitatively using model-based approach. One of the primary factors affecting the soil erosion assessment is a cover-management factor, C-factor. In the Czech Republic, several models are used to assess the C-factor on a long-term basis based on data collected using traditional tabular methods. This paper presents work to investigate the estimation of both long-term and short-term cover-management factors using remote sensing data. The results demonstrate a successful development of C-factor maps for each month of 2014, growing season average, and annual average for the Czech Republic. C-factor values calculated from remote sensing data confirmed expected trend in their temporal variability for selected crops. The results presented in this paper can be used for enhancing existing methods for estimating C-factor, planning future agricultural activities, and designing technical remediations and improvement activities of land use in the Czech Republic, which are also financially supported by the European Union funds. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

<a href="/cs/project/LO1415" target="_blank" >LO1415: CzechGlobe 2020 - Rozvoj Centra pro studium dopadů globální změny klimatu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Journal of Applied Remote Sensing

ISSN

1931-3195

e-ISSN

—

Svazek periodika

12

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

000425805600002

EID výsledku v databázi Scopus

2-s2.0-85042448567