On exploring bivariate and trivariate maps as visualization tools for spatial associations in digital soil mapping: A focus on soil properties

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F23%3A103312" target="_blank" >RIV/60460709:41210/23:103312 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/s11119-022-09955-7" target="_blank" >https://doi.org/10.1007/s11119-022-09955-7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11119-022-09955-7" target="_blank" >10.1007/s11119-022-09955-7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On exploring bivariate and trivariate maps as visualization tools for spatial associations in digital soil mapping: A focus on soil properties

Popis výsledku v původním jazyce

The benefits of digital soil maps cannot be overemphasised. For many years, researchers have mapped different soil classes, properties and processes while identifying the spatial associations between soil properties using side-by-side visualization maps. Although this is acceptable, it may be difficult to identify complex spatial associations between the mapped soil properties. For some, the task may be challenging owing to multiple times of side-by-side placing of the maps and the possible application of none user-friendly colour palettes and or schemes. Innovative tools are proposed for visualizing and identifying spatial associations between digital soil maps (raster layers) using bivariate and trivariate maps. These tools are applied in a case study to identify the spatial interactions between pH and selected macro-nutrients [nitrogen (N) and potassium (K)] of similar locality (Czech Republic), resolution and scale. This study further gives a brief overview of the applicability of bivariate and trivariate maps following the digital soil mapping process. Results show that bivariate and trivariate maps are effective for visualizing complex associations between pH and macro-nutrients. However, precautionary measures should be taken while applying bivariate and trivariate maps to ensure they are self-explanatory and that the legend colour schemes applied are user-friendly. Also, the variables mapped should be related. In this case, pH is a key soil quality indicator that affects macro-nutrient availability in soils.

Název v anglickém jazyce

On exploring bivariate and trivariate maps as visualization tools for spatial associations in digital soil mapping: A focus on soil properties

Popis výsledku anglicky

The benefits of digital soil maps cannot be overemphasised. For many years, researchers have mapped different soil classes, properties and processes while identifying the spatial associations between soil properties using side-by-side visualization maps. Although this is acceptable, it may be difficult to identify complex spatial associations between the mapped soil properties. For some, the task may be challenging owing to multiple times of side-by-side placing of the maps and the possible application of none user-friendly colour palettes and or schemes. Innovative tools are proposed for visualizing and identifying spatial associations between digital soil maps (raster layers) using bivariate and trivariate maps. These tools are applied in a case study to identify the spatial interactions between pH and selected macro-nutrients [nitrogen (N) and potassium (K)] of similar locality (Czech Republic), resolution and scale. This study further gives a brief overview of the applicability of bivariate and trivariate maps following the digital soil mapping process. Results show that bivariate and trivariate maps are effective for visualizing complex associations between pH and macro-nutrients. However, precautionary measures should be taken while applying bivariate and trivariate maps to ensure they are self-explanatory and that the legend colour schemes applied are user-friendly. Also, the variables mapped should be related. In this case, pH is a key soil quality indicator that affects macro-nutrient availability in soils.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40104 - Soil science

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Precision Agriculture

ISSN

1385-2256

e-ISSN

1573-1618

Svazek periodika

24

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

21

Strana od-do

511-532

Kód UT WoS článku

000847055900001

EID výsledku v databázi Scopus

2-s2.0-85137740229