As the project is closed, visitors should forward their requests to coordination-team@earthmonitor.org (+31) (0)317 427537

Martin Landa

CTU in Prague
 https://gitlab.com/geoharmonizer_inea/eumap

Martin Landa is a senior researcher at the Department of Geomatics, Czech Technical University in Prague, Faculty of Civil Engineering and an experienced GIS developer.

Martin is specialized in spatial data analysis with GRASS GIS, GRASS GIS development, Open Earth Observation and GeoSpatial DBs.

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All Sessions by Martin Landa

  • Day 2

    June 14, 2022

  • 9:00  - 10:30
    Workshop room 2 - C223 Introduction to the new version 8 of GRASS GIS, a few concepts Showcase the heavily redesigned graphical user interface Interaction with data (visualization, styling, map elements) Analysis of data from different domains Introduction to automated processing Hints on Python 3 scripting, spatio-temporal data analysis, and more. Candidate datasets: improved ERA5 land air temperature, surface temperature and precipitation (daily data) The software requirements are: GRASS GIS 8
    AI
    Machine Learning
    Software

  • 11:00  - 12:30
    Workshop room 2 - C223 GRASS GIS supports time series processing for vector, raster, and volume data Micro-introduction to Landsat and Sentinel satellite data archives, and the various ways to access them Introduction to the i.sentinel toolset which allows querying Sentinel data coverage for a region of interest, downloading from multiple data sources, performing atmospheric and topographic corrections, and cloud/shadow masking Preparation of data for multitemporal analyses is enabled in the t.sentinel and t.rast.mosaic extensions through automatic creation of space-time raster datasets (strds) and temporal aggregation to obtain cloud-free temporal mosaics of arbitrary granularity. Computation of NDVI time series Candidate datasets: Use Sentinel, ERA5 land air temperature, surface temperature and precipitation (daily data)
    AI
    Big Data
    Earth Observation
    Machine Learning
    Software

  • 13:30  - 15:00
    Workshop room 1 - C221 Introduction into web processing (OGC WPS, OGC API - Processes, REST API) in a comparative view Accessing WPS processes Accessing WPS processes from Python code using OWSLib Accessing WPS processes from QGIS actinia cloud computing with REST API (@neteler @metzm) explain how REST and actinia work actinia in Jupyter notebook actinia-QGIS plugin
    Climate data
    Data Cubes
    Land cover
    Software
    Soil data
    Training sessions
    Vegetation mapping

  • 15:30  - 17:00
    Workshop room 1 - C221 Introduction to LUCAS dataset provided by Eurostat Harmonized LUCAS dataset Accessing LUCAS dataset using Python API (Jupyter notebooks) Land product validation with LUCAS points (use case) Accessing LUCAS dataset from QGIS
    Big Data
    Earth Observation
    Training sessions

  • Day 3

    June 15

  • 9:00  - 9:25
    Welcome session - Welcome to participants, Introduction of the GeoHarmonizer project, its scopes, goals and outcomes, Introduction of all partners involved.
    Conference
    Where
    Conference room - C202

  • 16:10  - 16:30
    LUCAS (Land Use and Coverage Area frame Survey) is an activity that performs repeated in-situ surveys over Europe every three years since 2006. The dataset is unique in many aspects, however, it is currently not available through a standardized interface, machine-to-machine. Moreover, the evolution of the surveys limits the change analysis with the dataset. Our goal was to develop an open-source system to fill these gaps.
    Big Data
    Conference
    Data Cubes
    Land cover
    Machine Learning
    Where
    Conference room - C202

  • Day 4

    June 16

  • 16:40  - 16:50
    Closing ceremony with training sessions and conferene evaluation. Overview and evaluation of the GeoHarmonizer project, farawell from all project partners
    Awards
    Conference
    Where
    Conference room - C202




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Martin Landa