Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data.

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12220%2F21%3A43902925" target="_blank" >RIV/60076658:12220/21:43902925 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00027049:_____/21:N0000047 RIV/00027049:_____/21:N0000048 RIV/00027006:_____/21:10174589

Výsledek na webu

<a href="https://www.mdpi.com/2072-4292/13/20/4127" target="_blank" >https://www.mdpi.com/2072-4292/13/20/4127</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/rs13204127" target="_blank" >10.3390/rs13204127</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data.

Popis výsledku v původním jazyce

Knowledge of the spatial variability of soil hydraulic properties is important for many reasons, e.g., for soil erosion protection, or the assessment of surface and subsurface runoff. Nowadays, precision agriculture is gaining importance for which knowledge of soil hydraulic properties is essential, especially when it comes to the optimization of nitrogen fertilization. The present work aimed to exploit the ability of vegetation cover to identify the spatial variability of soil hydraulic properties through the expression of water stress. The assessment of the spatial distribution of saturated soil hydraulic conductivity (Ks) and field water capacity (FWC) was based on a combination of ground-based measurements and thermal and hyperspectral airborne imaging data. The crop water stress index (CWSI) was used as an indicator of crop water stress to assess the hydraulic properties of the soil. Supplementary vegetation indices were used. The support vector regression (SVR) method was used to estimate soil hydraulic properties from aerial data. Data analysis showed that the approach estimated Ks with good results (R2 = 0.77) for stands with developed crop water stress. The regression coefficient values for estimation of FWC for topsoil (0–0.3 m) ranged from R2 = 0.38 to R2 = 0.99. The differences within the study sites of the FWC estimations were higher for the subsoil layer (0.3–0.6 m). R2 values ranged from 0.12 to 0.99. Several factors affect the quality of the soil hydraulic features estimation, such as crop water stress development, condition of the crops, period and time of imaging, etc. The above approach is useful for practical applications for its relative simplicity, especially in precision agriculture.

Název v anglickém jazyce

Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data.

Popis výsledku anglicky

Knowledge of the spatial variability of soil hydraulic properties is important for many reasons, e.g., for soil erosion protection, or the assessment of surface and subsurface runoff. Nowadays, precision agriculture is gaining importance for which knowledge of soil hydraulic properties is essential, especially when it comes to the optimization of nitrogen fertilization. The present work aimed to exploit the ability of vegetation cover to identify the spatial variability of soil hydraulic properties through the expression of water stress. The assessment of the spatial distribution of saturated soil hydraulic conductivity (Ks) and field water capacity (FWC) was based on a combination of ground-based measurements and thermal and hyperspectral airborne imaging data. The crop water stress index (CWSI) was used as an indicator of crop water stress to assess the hydraulic properties of the soil. Supplementary vegetation indices were used. The support vector regression (SVR) method was used to estimate soil hydraulic properties from aerial data. Data analysis showed that the approach estimated Ks with good results (R2 = 0.77) for stands with developed crop water stress. The regression coefficient values for estimation of FWC for topsoil (0–0.3 m) ranged from R2 = 0.38 to R2 = 0.99. The differences within the study sites of the FWC estimations were higher for the subsoil layer (0.3–0.6 m). R2 values ranged from 0.12 to 0.99. Several factors affect the quality of the soil hydraulic features estimation, such as crop water stress development, condition of the crops, period and time of imaging, etc. The above approach is useful for practical applications for its relative simplicity, especially in precision agriculture.

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/TH02030133" target="_blank" >TH02030133: Zemědělský systém hospodaření integrující efektivní využití živin plodinami a ochranu vod před plošnými zdroji znečištění</a><br>

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Remote Sensing

ISSN

2072-4292

e-ISSN

—

Svazek periodika

13

Číslo periodika v rámci svazku

4127

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

25

Strana od-do

20

Kód UT WoS článku

000714484900001

EID výsledku v databázi Scopus

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