Mapping Soil Properties with Fixed Rank Kriging of Proximally
Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter

J 2022

Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter

KARAPETSAS, Nikolaos, Thomas K. ALEXANDRIDIS, George BILAS, Muhammad Abdul MUNNAF, Angela P GUERRERO et. al.

Základní údaje

Originální název

Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter

Autoři

KARAPETSAS, Nikolaos, Thomas K. ALEXANDRIDIS (garant), George BILAS, Muhammad Abdul MUNNAF, Angela P GUERRERO, Maria CALERA, Anna OSANN, Anne GOBIN, Tomáš ŘEZNÍK (203 Česká republika, domácí), Dimitrios MOSHOU a Abdul Mounem MOUAZEN

Vydání

Remote Sensing, MDPI, 2022, 2072-4292

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10508 Physical geography

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 5.000

Kód RIV

RIV/00216224:14310/22:00126404

Organizační jednotka

Přírodovědecká fakulta

DOI

http://dx.doi.org/10.3390/rs14071639

UT WoS

000780735200001

Klíčová slova anglicky

geostatistical interpolation; VNIR spectrometer; NDVI; fAPAR; precision agriculture

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 10. 8. 2022 13:19, Mgr. Marie Šípková, DiS.

Anotace

V originále

Soil surveys with line-scanning platforms appear to have great advantages over the traditional methods used to collect soil information for the development of field-scale soil mapping and applications. These carry VNIR (visible and near infrared) spectrometers and have been used in recent years extensively for the assessment of soil fertility at the field scale, and the delineation of site-specific management zones (MZ). A challenging feature of VNIR applications in precision agriculture (PA) is the massiveness of the derived datasets that contain point predictions of soil properties, and the interpolation techniques involved in incorporating these data into site-specific management plans. In this study, fixed-rank kriging (FRK) geostatistical interpolation, which is a flexible, non-stationary spatial interpolation method especially suited to handling huge datasets, was applied to massive VNIR soil scanner data for the production of useful, smooth interpolated maps, appropriate for the delineation of site-specific MZ maps. Moreover, auxiliary Sentinel-2 data-based biophysical parameters NDVI (normalized difference vegetation index) and fAPAR (fraction of photosynthetically active radiation absorbed by the canopy) were included as covariates to improve the filtering performance of the interpolator and the ability to generate uniform patterns of spatial variation from which it is easier to receive a meaningful interpretation in PA applications. Results from the VNIR prediction dataset obtained from a pivot-irrigated field in Albacete, southeastern Spain, during 2019, have shown that FRK variants outperform ordinary kriging in terms of filtering capacity, by doubling the noise removal metrics while keeping the computation cost reasonably low. Such features, along with the capacity to handle a large volume of spatial information, nominate the method as ideal for PA applications with massive proximal and remote sensing datasets.

Návaznosti

818346, interní kód MU

Název: Si-EU-Soil (Akronym: SIEUSIOL)

Investor: Evropská unie, Si-EU-Soil, Food security, sustainable agriculture and forestry, marine and maritime and inland water research (Societal Challenges)

Citovat

KARAPETSAS, Nikolaos, Thomas K. ALEXANDRIDIS, George BILAS, Muhammad Abdul MUNNAF, Angela P GUERRERO, Maria CALERA, Anna OSANN, Anne GOBIN, Tomáš ŘEZNÍK, Dimitrios MOSHOU a Abdul Mounem MOUAZEN. Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter. Remote Sensing. MDPI, 2022, roč. 14, č. 7, s. 1-22. ISSN 2072-4292. Dostupné z: https://dx.doi.org/10.3390/rs14071639.

@article{2210919,
   author = {Karapetsas, Nikolaos and Alexandridis, Thomas K. and Bilas, George and Munnaf, Muhammad Abdul and Guerrero, Angela P and Calera, Maria and Osann, Anna and Gobin, Anne and Řezník, Tomáš and Moshou, Dimitrios and Mouazen, Abdul Mounem},
   article_number = {7},
   doi = {http://dx.doi.org/10.3390/rs14071639},
   keywords = {geostatistical interpolation; VNIR spectrometer; NDVI; fAPAR; precision agriculture},
   language = {eng},
   issn = {2072-4292},
   journal = {Remote Sensing},
   title = {Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter},
   url = {https://www.mdpi.com/2072-4292/14/7/1639},
   volume = {14},
   year = {2022}
}

TY  - JOUR
ID  - 2210919
AU  - Karapetsas, Nikolaos - Alexandridis, Thomas K. - Bilas, George - Munnaf, Muhammad Abdul - Guerrero, Angela P - Calera, Maria - Osann, Anna - Gobin, Anne - Řezník, Tomáš - Moshou, Dimitrios - Mouazen, Abdul Mounem
PY  - 2022
TI  - Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter
JF  - Remote Sensing
VL  - 14
IS  - 7
SP  - 1-22
EP  - 1-22
PB  - MDPI
SN  - 20724292
KW  - geostatistical interpolation
KW  - VNIR spectrometer
KW  - NDVI
KW  - fAPAR
KW  - precision agriculture
UR  - https://www.mdpi.com/2072-4292/14/7/1639
N2  - Soil surveys with line-scanning platforms appear to have great advantages over the traditional methods used to collect soil information for the development of field-scale soil mapping and applications. These carry VNIR (visible and near infrared) spectrometers and have been used in recent years extensively for the assessment of soil fertility at the field scale, and the delineation of site-specific management zones (MZ). A challenging feature of VNIR applications in precision agriculture (PA) is the massiveness of the derived datasets that contain point predictions of soil properties, and the interpolation techniques involved in incorporating these data into site-specific management plans. In this study, fixed-rank kriging (FRK) geostatistical interpolation, which is a flexible, non-stationary spatial interpolation method especially suited to handling huge datasets, was applied to massive VNIR soil scanner data for the production of useful, smooth interpolated maps, appropriate for the delineation of site-specific MZ maps. Moreover, auxiliary Sentinel-2 data-based biophysical parameters NDVI (normalized difference vegetation index) and fAPAR (fraction of photosynthetically active radiation absorbed by the canopy) were included as covariates to improve the filtering performance of the interpolator and the ability to generate uniform patterns of spatial variation from which it is easier to receive a meaningful interpretation in PA applications. Results from the VNIR prediction dataset obtained from a pivot-irrigated field in Albacete, southeastern Spain, during 2019, have shown that FRK variants outperform ordinary kriging in terms of filtering capacity, by doubling the noise removal metrics while keeping the computation cost reasonably low. Such features, along with the capacity to handle a large volume of spatial information, nominate the method as ideal for PA applications with massive proximal and remote sensing datasets.
ER  -

KARAPETSAS, Nikolaos, Thomas K. ALEXANDRIDIS, George BILAS, Muhammad Abdul MUNNAF, Angela P GUERRERO, Maria CALERA, Anna OSANN, Anne GOBIN, Tomáš ŘEZNÍK, Dimitrios MOSHOU a Abdul Mounem MOUAZEN. Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter. \textit{Remote Sensing}. MDPI, 2022, roč.~14, č.~7, s.~1-22. ISSN~2072-4292. Dostupné z: https://dx.doi.org/10.3390/rs14071639.

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