We are pleased to share that the AUC Geographica was awarded an Impact Factor of 0.6 in the 2022 Journal Citation Reports™ released by Clarivate in June 2023. AUC Geographica ranks (JCI) in Q3 in Geography.
AUC Geographica (Acta Universitatis Carolinae Geographica) is a scholarly academic journal continuously published since 1966 that publishes research in the broadly defined field of geography: physical geography, geo-ecology, regional, social, political and economic geography, regional development, cartography, geoinformatics, demography and geo-demography.
AUC Geographica also publishes articles that contribute to advances in geographic theory and methodology and address the questions of regional, socio-economic and population policy-making in Czechia.
Periodical twice yearly.
Release dates: June 30, December 31
All articles are licenced under Creative Commons Attribution 4.0 International licence (CC BY 4.0), have DOI and are indexed in CrossRef database.
AUC Geographica is covered by the following services: WOS, EBSCO, GeoBibline, SCOPUS, Ulrichsweb and Directory of Open Access Journals (DOAJ).
The journal has been covered in the SCOPUS database since 1975 – today
https://www.scopus.com/source/sourceInfo.uri?sourceId=27100&origin=recordpage
The journal has been selected for coverage in Clarivate Analytics products and services. Beginning with V. 52 (1) 2017, this publication will be indexed and abstracted in Emerging Sources Citation Index.
The journal has been indexed by the Polish Ministry of Science and Higher Education (MSHE) on the list of scientific journals recommended for authors to publish their articles. ICI World of Journals; Acta Universitatis Carolinae, Geographica.
Journal metrics 2022
Web of Science
Impact factor (JCR®): 0.6
Journal Citation Indicator (JCI): 0.24
Rank (JCI): Q3 in Geography
Scopus
Cite Score: 1.1
Rank (ASJC): Q3 in Geography, Planning and Development; Q3 in General Earth and Planetary Sciences
The journal is archived in Portico.
AUC GEOGRAPHICA, Vol 53 No 2 (2018), 149–155
Spatial prediction of soil infiltration using functional geostatistics
Diego Leonardo Cortes-D, Jesus Hernan Camacho-Tamayo, Ramon Giraldo
DOI: https://doi.org/10.14712/23361980.2018.15
published online: 28. 08. 2018
abstract
The infiltration of water into the soil is a necessary parameter for irrigation systems design. Characterizing its spatial behavior allows a site-specific management of water according to soil conditions and crop requirements. The aim of this study is to establish the spatial distribution of infiltration in an Andisol by means of two geostatistical approaches: on the one hand by means of functional kriging, taking as input infiltration curves (obtained after a smoothing stage), and on the other hand by using classical ordinary kriging on the parameters of the Kostiakov and Phillip models. The comparison between these methodologies is carried out taking as a criterion the sum of squared errors of a leave-one-out cross-validation analysis. The results show a high correlation between observations and predictions (R2 values around 99%), which indicates that the use of functional geostatistics in this context could be a good alternative. Moreover, from a descriptive point of view, we can point out that the contour maps of basic infiltration (BI), cumulative infiltration (Ci), saturated hydraulic conductivity (Ks), and sorptivity (S) obtained with the observed data, as well as the predictions by functional geostatistics, show a very similar behavior, which empirically validates the use of this methodology.
keywords: functional data; functional kriging; Kostiakov; Philip; spatial variability
Spatial prediction of soil infiltration using functional geostatistics is licensed under a Creative Commons Attribution 4.0 International License.
210 x 297 mm
periodicity: 2 x per year
print price: 200 czk
ISSN: 0300-5402
E-ISSN: 2336-1980
