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The Elbe river
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Ing. Markéta Potůčková Ph.D.
Academic staff at Faculty of Science
8 classes
121 publications
Classes
class
Applied Geoinformatics
MZ300E007 |
Faculty of Science
class
Remote Sensing Image Processing II.
MZ370G06 |
Faculty of Science
class
Processing of imaging radar data
MZ370G17 |
Faculty of Science
class
Precessing of 3D point clouds
MZ370G19 |
Faculty of Science
class
Visiting professor in geoinformatics and cartography
MZ370G27 |
Faculty of Science
class
Time series analysis in RS
MZ370G31 |
Faculty of Science
class
Extraction of Topographic Information
MZ370P05 |
Faculty of Science
class
Matlab
MZ370P28 |
Faculty of Science
Publications
publication
An incremental facility location clustering with a new hybrid constrained pseudometric
2023 |
Faculty of Science, Faculty of Mathematics and Physics
publication
Can canopy temperature acquired from an airborne level be a tree health indicator in an urban environment?
2023 |
Faculty of Science
publication
Multisource point cloud fusion for forest and post-fire forest mapping: Case study from the Bohemian Switzerland National Park
2023 |
Faculty of Science
publication
Towards reliable monitoring of grass species in nature conservation: Evaluation of the potential of UAV and PlanetScope multi-temporal data in the Central European tundra
2023 |
Faculty of Science
publication
Evaluation of the bark beetle green attack detectability in spruce forest from multitemporal multispectral UAV imagery
2023 |
Faculty of Science
publication
Retrieval of Harmonized LAI Product of Agricultural Crops from Landsat OLI and Sentinel-2 MSI Time Series
2022 |
Faculty of Science, Central Library of Charles University
publication
Critical Catalog of the Exhibition: The Heritage of Defunct Landscapes of the Czechia 2
2022 |
Faculty of Science
publication
Outputs of the team of the department of applied geoinformatics and cartography
2022 |
Faculty of Science
publication
Improvements to airborne laser scanning data filtering in sandstone landscapes
2022 |
Faculty of Science
publication
Weakly supervised learning for treeline ecotone classification based on aerial orthoimages and an ancillary DSM
2022 |
Faculty of Science
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