Naslov
Use of VNIR spectroscopy for assessment of Stagnosols properties based on linear and non- linear calibration methods

Autori
Šestak, Ivana ; Mesić, Milan ; Zgorelec, Željka ; Perčin Aleksandra

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Book of Abstracts: "Utilizing potential of soil and land resources: Key roles of science and effective policy" / Romić, Marija ; Rastija, Domagoj ; Popović, Brigita - Zagreb : Hrvatsko tloznanstveno društvo, 2018, 56-56

ISBN
978-953-7878-85-6

Skup
13. kongres Hrvatskog tloznanstvenog društva

Mjesto i datum
Vukovar, Hrvatska, 10.09.2018. - 14.09.2018

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
soil reflectance ; principal component analysis ; linear modeling ; neural networks ; soil quality

Sažetak
Soil organic and mineral compounds can be estimated non-destructively by visible and near infrared (VNIR) diffuse reflectance spectroscopy. However, results of calibration models differ in dependence of measurement precision, spectral range, variability of soil properties and calibration methods used for prediction. The objective of research was to estimate the ability of hyperspectral VNIR spectroscopy for field-scale prediction of soil total carbon (TC %) and total nitrogen (TN %) content, soil pH, plant-available potassium (K) and phosphorus (P), in arable Stagnosols. Total of 200 soil samples taken from field experiment (soil depth: 30 cm ; sampling grid: 15x15 m ; 2016) were scanned in laboratory using portable spectroradiometer (FieldSpec®3, 350-1050 nm). Partial least squares regression (PLSR) with full cross-validation and artificial neural networks (ANN) were used to build prediction models of selected soil properties based on VNIR spectra. Strong to full correlation and low root mean squared error were obtained between predicted and measured values for the calibration and validation dataset, and both calibration methods. ANN models were more efficient in capturing the complex link between selected soil properties and soil reflectance spectra. Key spectral features and algorithms defined in this study should help to support site-specific and real-time soil survey using hyperspectral remote sensing.

Izvorni jezik
Engleski

Znanstvena područja
Poljoprivreda (agronomija)

POVEZANOST RADA