We are pleased to share that AUC Geographica was awarded an Impact Factor of 0.5 in the 2023 Journal Citation Reports™ released by Clarivate in June 2024. AUC Geographica ranks in Q3 in the field of 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 2023
Web of Science
Impact factor (JCR®): 0.5
Journal Citation Indicator (JCI): 0.20
Rank (JCI): Q3 in Geography
Scopus
Cite Score: 1.2
Rank (ASJC): Q3 in Geography, Planning and Development; Q3 in General Earth and Planetary Sciences
The journal is archived in Portico.
AUC GEOGRAPHICA, Vol 45 No 2 (2010), 101–113
A Comparison of LUCC Detection Algorithms in a Mesoamerican Lowland Tropical Forest
Laurel Sutter, David López-Carr
DOI: https://doi.org/10.14712/23361980.2015.51
published online: 02. 06. 2019
abstract
Land use and land cover changes occur throughout the world, but none is more concerning than tropical deforestation, much of it for agricultural purposes. Rural-rural frontier migrant farmers such as those colonizing the Sierra del Lacandón National Park in Petén, Guatemala act as a primary direct agent in this land cover conversion. This paper seeks to compare three different algorithms for monitoring changes in forested land cover, making use of freely available remotely sensed Landsat images from two years, 1991 and 2000. In the intervening 9 years, some forested land was converted to cropped, pasture, or fallow land, while other areas experienced no change. This paper contains a detailed description of the methods employed for three different change detection techniques, producing a total of five land change maps: multidate principal components analysis (PCA), normalized difference vegetation index (NDVI ) image differencing, and brightness greenness wetness (BGW) image differencing. Of the five land change maps produced, the Greenness component of the BGW transformation had the highest overall accuracy, at 86%, and is conservative in detecting change. The amount of change detected by this algorithm represents approximately 300 km2 of forest loss, or 11.9% of the area examined.
keywords: LUCC; Landsat; PCA; NDVI; BGW
A Comparison of LUCC Detection Algorithms in a Mesoamerican Lowland Tropical Forest 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
