Vše

Co hledáte?

Vše
Projekty
Výsledky výzkumu
Subjekty

Rychlé hledání

  • Projekty podpořené TA ČR
  • Významné projekty
  • Projekty s nejvyšší státní podporou
  • Aktuálně běžící projekty

Chytré vyhledávání

  • Takto najdu konkrétní +slovo
  • Takto z výsledků -slovo zcela vynechám
  • “Takto můžu najít celou frázi”

Estimation of Soil Properties Based on Soil Colour Index

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F18%3A43913368" target="_blank" >RIV/62156489:43210/18:43913368 - isvavai.cz</a>

  • Výsledek na webu

    <a href="http://acs.agr.hr/acs/index.php/acs/article/view/1330" target="_blank" >http://acs.agr.hr/acs/index.php/acs/article/view/1330</a>

  • DOI - Digital Object Identifier

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Estimation of Soil Properties Based on Soil Colour Index

  • Popis výsledku v původním jazyce

    Knowledge on soil properties is an important aspect in the implementation of precision agriculture. For this study was used an image taken by Sentinel 2 depicting fields of one farm with 8,261 ha in the South Moravian region of the Czech Republic. For the determination of soil properties, soil samples were taken at a density of 1 sample per 3 hectares and analyzed by Mehlich III methodology. The content of available nutrients phosphorus, potassium, magnesium and calcium have been determined together with soil pH, soil texture and sand. The specified sampling revealed high variability for phosphorus, potassium and calcium. Lower variability has been observed with magnesium and pH. An identification of bare soil area without vegetation cover was tested by different threshold values of Normalized vegetation difference index (NDVI) (0.15 - 0.3). The correlations between the multispectral bands and the soil properties were weak. In the analysis of soil samples was detected positive correlation (r = 0.505) between soil texture and Colour Index (CI). In area was found a negative correlation between CI and Ca (r = -0.618), then between CI and pH (r = -0.504). Weak correlation were found between CI, phosphorus and magnesium. At the level of lower NDVI values (0.16 - 0.15) we found correlation between CI and the sand content. The observed level of correlation found in the data of remote sensing can predict some soil properties in fields that have not been subjected to soil sampling and facilitate learning about soil properties for decisions in precision agriculture.

  • Název v anglickém jazyce

    Estimation of Soil Properties Based on Soil Colour Index

  • Popis výsledku anglicky

    Knowledge on soil properties is an important aspect in the implementation of precision agriculture. For this study was used an image taken by Sentinel 2 depicting fields of one farm with 8,261 ha in the South Moravian region of the Czech Republic. For the determination of soil properties, soil samples were taken at a density of 1 sample per 3 hectares and analyzed by Mehlich III methodology. The content of available nutrients phosphorus, potassium, magnesium and calcium have been determined together with soil pH, soil texture and sand. The specified sampling revealed high variability for phosphorus, potassium and calcium. Lower variability has been observed with magnesium and pH. An identification of bare soil area without vegetation cover was tested by different threshold values of Normalized vegetation difference index (NDVI) (0.15 - 0.3). The correlations between the multispectral bands and the soil properties were weak. In the analysis of soil samples was detected positive correlation (r = 0.505) between soil texture and Colour Index (CI). In area was found a negative correlation between CI and Ca (r = -0.618), then between CI and pH (r = -0.504). Weak correlation were found between CI, phosphorus and magnesium. At the level of lower NDVI values (0.16 - 0.15) we found correlation between CI and the sand content. The observed level of correlation found in the data of remote sensing can predict some soil properties in fields that have not been subjected to soil sampling and facilitate learning about soil properties for decisions in precision agriculture.

Klasifikace

  • Druh

    J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS

  • CEP obor

  • OECD FORD obor

    40500 - Other agricultural sciences

Návaznosti výsledku

  • Projekt

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2018

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název periodika

    Agriculturae Conspectus Scientificus

  • ISSN

    1331-7768

  • e-ISSN

  • Svazek periodika

    83

  • Číslo periodika v rámci svazku

    1

  • Stát vydavatele periodika

    HR - Chorvatská republika

  • Počet stran výsledku

    6

  • Strana od-do

    71-76

  • Kód UT WoS článku

  • EID výsledku v databázi Scopus

    2-s2.0-85045210476