Assessment of soil variability of South moravian region based on the satellite imagery

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F18%3A43913369" target="_blank" >RIV/62156489:43210/18:43913369 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/86652079:_____/18:00489762

Výsledek na webu

<a href="https://doi.org/10.11118/actaun201866010119" target="_blank" >https://doi.org/10.11118/actaun201866010119</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.11118/actaun201866010119" target="_blank" >10.11118/actaun201866010119</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Assessment of soil variability of South moravian region based on the satellite imagery

Popis výsledku v původním jazyce

The aim of this study was to analyse the sets of atmospherically corrected Remote Sensing (RS) data in order to assess the variability of bare arable land between different soil blocks in the selected area and evaluate the suitability of this approach for locally targeted management. The study was carried out on the territory of parts of South Moravian, Vysocina and Zlín regions. The RS data was analyzed by two models developed in the Arc GIS 10.22 environment using the Normalized Differential Vegetation Index (NDVI) and the Principal component analysis (PCA) analyzing bare soil (BS) with more than 50 % and more than 95 % of the block representation. A layer of agricultural land from the LPIS system was used to delimit arable land areas. For correct determinig of BS value for NDVI were carried out the terrestrial measurements in the monitored area by using the GreenSeeker handheld crop sensor and The FieldSpec(R) HandHeld 2 spectrometer. Based on these measurements and image dates, 0.2 NDVI was selected as the limit value. As a more suitable source for identifying BS, RapidEye appears to be able to identify an average of 26 % of the observed area as bare ground compared to Sentinel 2 data (22.5 % of the observed area) in models with more than 50 % By representing the BS in a block (NDVI 50, PCA 50). In these versions of the model was more variable soil (VS) indicated by RapidEye. With more than 95 % of the BS in the block (NDVI 95, PCA 95) was found more variable soils by Sentinel 2. This method of indirectly identifying soil variability can assist in the application of fertilizer or soil treatment in the area of site-specific management.

Název v anglickém jazyce

Assessment of soil variability of South moravian region based on the satellite imagery

Popis výsledku anglicky

The aim of this study was to analyse the sets of atmospherically corrected Remote Sensing (RS) data in order to assess the variability of bare arable land between different soil blocks in the selected area and evaluate the suitability of this approach for locally targeted management. The study was carried out on the territory of parts of South Moravian, Vysocina and Zlín regions. The RS data was analyzed by two models developed in the Arc GIS 10.22 environment using the Normalized Differential Vegetation Index (NDVI) and the Principal component analysis (PCA) analyzing bare soil (BS) with more than 50 % and more than 95 % of the block representation. A layer of agricultural land from the LPIS system was used to delimit arable land areas. For correct determinig of BS value for NDVI were carried out the terrestrial measurements in the monitored area by using the GreenSeeker handheld crop sensor and The FieldSpec(R) HandHeld 2 spectrometer. Based on these measurements and image dates, 0.2 NDVI was selected as the limit value. As a more suitable source for identifying BS, RapidEye appears to be able to identify an average of 26 % of the observed area as bare ground compared to Sentinel 2 data (22.5 % of the observed area) in models with more than 50 % By representing the BS in a block (NDVI 50, PCA 50). In these versions of the model was more variable soil (VS) indicated by RapidEye. With more than 95 % of the BS in the block (NDVI 95, PCA 95) was found more variable soils by Sentinel 2. This method of indirectly identifying soil variability can assist in the application of fertilizer or soil treatment in the area of site-specific management.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

40500 - Other agricultural sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis

ISSN

1211-8516

e-ISSN

—

Svazek periodika

66

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

11

Strana od-do

119-129

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85103505692