@ARTICLE{Lemenkova_Polina_Environmental_2023,
 author={Lemenkova, Polina and Debeir, Olivier},
 volume={vol. 72},
 number={No 2},
 pages={e45},
 journal={Advances in Geodesy and Geoinformation},
 howpublished={online},
 year={2023},
 publisher={Commitee on Geodesy PAS},
 abstract={In this paper, the climate and environmental datasets were processed by the scripts of Generic Mapping Tools (GMT) and R to evaluate changes in climate parameters, vegetation patters and land cover types in Burkina Faso. Located in the southern Sahel zone, Burkina Faso experiences one of the most extreme climatic hazards in sub-saharan Africa varying from the extreme floods in Volta River Basin, to desertification and recurrent droughts.. The data include the TerraClimate dataset and satellite images Landsat 8-9 Operational Land Imager (OLI) and Thermal Infrared (TIRS) C2 L1. The dynamics of target climate characteristics of Burkina Faso was visualised for 2013-2022 using remote sensing data. To evaluate the environmental dynamics the TerraClimate data were used for visualizing key climate parameter: extreme temperatures, precipitation, soil moisture, downward surface shortwave radiation, vapour pressure deficit and anomaly. The Palmer Drought Severity Index (PDSI) was modelled over the study area to estimate soil water balance related to the soil moisture conditions as a prerequisites for vegetation growth. The land cover types were mapped using the k-means clustering by R. Two vegetation indices were computed to evaluate the changes in vegetation patterns over recent decade. These included the Normalized Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI) The scripts used for cartographic workflow are presented and discussed. This study contributes to the environmental mapping of Burkina Faso with aim to highlight the links between the climate processes and vegetation dynamics in West Africa.},
 type={Article},
 title={Environmental mapping of Burkina Faso using TerraClimate data and satellite images by GMT and R scripts},
 URL={http://journals.pan.pl/Content/128921/art-e45.pdf},
 doi={10.24425/agg.2023.146157},
 keywords={environmental monitoring, cartography, image processing, sub-saharan Africa, R programming},
}