Usage of Airborne Hyperspectral Imaging Data for Identifying Spatial Variability of Soil Nitrogen Content

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73608843" target="_blank" >RIV/61989592:15310/21:73608843 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2220-9964/10/6/355/htm" target="_blank" >https://www.mdpi.com/2220-9964/10/6/355/htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/ijgi10060355" target="_blank" >10.3390/ijgi10060355</a>

Result language

angličtina

Original language name

Usage of Airborne Hyperspectral Imaging Data for Identifying Spatial Variability of Soil Nitrogen Content

Original language description

Soil is a significant natural resource composed of organic and inorganic material. Nitrogen, one of the essential elements, is traditionally measured using laboratory methods. The development of hyperspectral imaging enables the cost-effective acquisition of both spectral and spatial information for detecting physical, chemical, and biological attributes of the soil samples. The presented work evaluates the suitability of airborne hyperspectral imaging for determining soil nitrogen content and producing a soil nitrogen map on a pixel-wise basis. The measurement of spatial variability of the soil nitrogen content was taken at two fields located at Rudice, in northeast Brno, Czech Republic, using laboratory methods and a handheld spectrometer. The soil reflectance was also recorded using airborne-mounted imaging spectroscopy sensors. A partial least squares regression was used to develop a model for the calibration of the data collected with a portable spectrometer and to predict the total nitrogen in the soils based on hyperspectral images from airborne sensors. The determination factor for the PLSR model presented in this paper reached an R-2 of 0.44. The model&apos;s performance could be improved by using a handheld spectrometer with a wider spectral range, using the same acquisition period for field data collection and hyperspectral imaging, and enlarging the sample size.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10511 - Environmental sciences (social aspects to be 5.7)

Project

<a href="/en/project/TA04020888" target="_blank" >TA04020888: Contactless monitoring and spatio-temporally modelling variability of selected differing soil characteristics</a><br>

Continuities

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

Publication year

2021

Confidentiality

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

Name of the periodical

ISPRS International Journal of Geo-Information

ISSN

2220-9964

e-ISSN

—

Volume of the periodical

10

Issue of the periodical within the volume

6

Country of publishing house

CH - SWITZERLAND

Number of pages

18

Pages from-to

"355-1"-"355-18"

UT code for WoS article

000666566200001

EID of the result in the Scopus database

2-s2.0-85107603402