155ISDP Introduction to Spatial Data Processing: Porovnání verzí

Z GeoWikiCZ
← Porovnání se starší verzíPorovnání s novější verzí →
Vizuální
29.4. - fix time and place
(Není zobrazeno 10 mezilehlých verzí od jednoho dalšího uživatele.)
Řádek 3: Řádek 3:
* Code: 155ISDP
* Code: 155ISDP
* Lectures: {{lide|Ing. Martin Landa, Ph.D.}}
* Lectures: {{lide|Ing. Martin Landa, Ph.D.}}
* Practical classes: {{lide|Ing. Martin Landa, Ph.D.}} (head of the classes), {{lide|Ing. Ondřej Pešek, PhD.}}
* Practical classes: {{lide|Ing. Martin Landa, Ph.D.}} (head of the classes), {{lide|Ing. Ondřej Pešek, Ph.D.}}
* lectures per week: 2 hours  
* lectures per week: 2 hours  
* exercises per week: 2 hours
* exercises per week: 2 hours
Řádek 16: Řádek 16:
==Lectures==
==Lectures==


'''Course tutors:''' {{lide|Ing. Martin Landa, Ph.D.}} (ML), {{lide|Ing. Ondřej Pešek, PhD.}} (OP)
'''Course tutors:''' {{lide|Ing. Martin Landa, Ph.D.}} (ML), {{lide|Ing. Ondřej Pešek, Ph.D.}} (OP)


* Wednesday 4-5:40pm room: B-870
* Wednesday 4-5:40pm room: B-870
Řádek 31: Řádek 31:
# <strike>(16+17.4.)</strike> Class cancelled
# <strike>(16+17.4.)</strike> Class cancelled
# (23+24.4.) [ML] Geospatial data in SQL
# (23+24.4.) [ML] Geospatial data in SQL
# (29.4+7.5.) [ML] Geospatial data processing in SQL (change: 29.4. 4-5:40pm B-870)
# (29.4+7.5.) [ML] Geospatial data processing in SQL (change: 29.4. 9-10:40am B-s111)
# (14+15.5.) [TB?] Cloud-based geospatial data processing
# (14+15.5.) [TB] Cloud-based geospatial data processing


==Exercises==
==Exercises==
Řádek 41: Řádek 41:


JupyterHub: http://gislab.fsv.cvut.cz:8000/hub
JupyterHub: http://gislab.fsv.cvut.cz:8000/hub
== Assignments ==
Each student will work on two mini-projects, one using Python and the other using SQL. Student's evaluation is based on successful fulfillment of these two assignments.
Project requirements:
* use open geospatial data as input
* demonstrate knowledge of automated geospatial data processing and its analysis
* provide results interpretation (discussion, graphs, tables, ...)
=== Python-based project assignment  ===
* Assignment 27.3.
* Presentation 24.4.
Expected submission form: Jupyter Notebook or Python script
=== SQL-based project assignment  ===
* Assignment 24.4.
* Presentation 15.5.
Expected submission form: SQL file


== Install instructions for MS Windows ==
== Install instructions for MS Windows ==


* [https://github.com/jupyterlab/jupyterlab-desktop JupyterLab]
* [https://qgis.org/download/ QGIS]
* [https://grass.osgeo.org/download/ GRASS GIS] (on MS Windows GRASS GIS is installed together with QGIS)
* [https://www.python.org/downloads/ Python] + [https://github.com/jupyterlab/jupyterlab-desktop JupyterLab]


In Jupyter notebook run
In Jupyter notebook run
Řádek 54: Řádek 80:
== Literature ==
== Literature ==


<bibtex>
* [https://link.springer.com/book/10.1007/978-0-387-68574-8 Open Source GIS: A Grass GIS Approach]
@book{neteler2004open,
* [https://books.google.cz/books/about/Desktop_GIS.html?id=xZ7tHwAACAAJ&redir_esc=y Desktop GIS: Mapping the Planet With Open Source Tools]
  title={Open Source GIS: A Grass GIS Approach},
* [http://books.google.cz/books?id=JZNuu8XODQMC Open Source Approaches in Spatial Data Handling]
  author={Neteler, M. and Mitasova, H.},
* [http://books.google.cz/books?id=AnCNQQAACAAJ OpenStreetMap: Using and Enhancing the Free Map of the World]
  isbn={9781402080647},
* [http://books.google.cz/books?id=SULMdT8qPwEC Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools]
  lccn={04051566},
  series={The International Series in Engineering and Computer Science Series},
  url={http://books.google.cz/books?id=Qvp9iFg\_WPEC},
  year={2004},
  publisher={Kluwer Academic Pub}
}
</bibtex>
<bibtex>
@book{sherman2008desktop,
  title={Desktop GIS: Mapping the Planet With Open Source Tools},
  author={Sherman, G.E.},
  isbn={9781934356067},
  lccn={2010280046},
  series={Pragmatic Bookshelf Series},
  url={http://books.google.cz/books?id=xZ7tHwAACAAJ},
  year={2008},
  publisher={Pragmatic Bookshelf}
}
</bibtex>
<bibtex>
@book{hall2008open,
  title={Open Source Approaches in Spatial Data Handling},
  author={Hall, G.B. and Leahy, M.G.},
  isbn={9783540748311},
  lccn={2008932589},
  series={Advances in geographic information science},
  url={http://books.google.cz/books?id=JZNuu8XODQMC},
  year={2008},
  publisher={Springer London, Limited}
}
</bibtex>
<bibtex>
@book{ramm2010openstreetmap,
  title={OpenStreetMap: Using and Enhancing the Free Map of the World},
  author={Ramm, F. and Topf, J. and Chilton, S.},
  isbn={9781906860110},
  url={http://books.google.cz/books?id=AnCNQQAACAAJ},
  year={2010},
  publisher={Uit Cambridge Limited}
}
</bibtex>
<bibtex>
@book{de2007geospatial,
  title={Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools},
  author={De Smith, M.J. and Goodchild, M.F. and Longley, P.A.},
  isbn={9781905886609},
  url={http://books.google.cz/books?id=SULMdT8qPwEC},
  year={2007},
  publisher={Matador}
}
</bibtex>

Verze z 24. 3. 2025, 11:07

Basic Information

  • Up-to-date and complete information are ON THIS PAGE
  • Code: 155ISDP
  • Lectures:

Ing. Martin Landa, Ph.D.

  • Practical classes:

Ing. Martin Landa, Ph.D. (head of the classes), Ing. Ondřej Pešek, Ph.D.

  • lectures per week: 2 hours
  • exercises per week: 2 hours
  • Credits: 6
  • finished with: an exam / project
  • summer semester

Anotation

Introduction into geospatial data processing. Various workflow automation techniques (interactive tools, Python programming language, and Structured Query Language). Demonstration of various processing environments (desktop applications, database environments, cloud-based computing).

Lectures

Course tutors: Ing. Martin Landa, Ph.D. (ML), Ing. Ondřej Pešek, Ph.D. (OP)

  • Wednesday 4-5:40pm room: B-870
  • Thursday 9-10:40am room: B-s111
  1. (19+20.2.) [ML] Introduction into GIS, open geospatial datasets
  2. (26+27.3.) [OP] Geospatial data and web services
  3. (05+06.3.) [OP/ML] Data processing automation
  4. (12+13.3.) [ML] Introduction into Python data processing (Esri)
  5. (19+20.3.) [OP] Introduction into Python data processing (open source)
  6. (26+27.3.) [OP] Geospatial Python packages
  7. (02+03.4.) [ML] Space-time geospatial data processing
  8. (09+10.4.) [ML] Introduction into databases, SQL
  9. (16+17.4.) Class cancelled
  10. (23+24.4.) [ML] Geospatial data in SQL
  11. (29.4+7.5.) [ML] Geospatial data processing in SQL (change: 29.4. 9-10:40am B-s111)
  12. (14+15.5.) [TB] Cloud-based geospatial data processing

Exercises

Materials: https://geo.fsv.cvut.cz/courses/155isdp/

Sample data: https://geo.fsv.cvut.cz/courses/155isdp/data

JupyterHub: http://gislab.fsv.cvut.cz:8000/hub

Assignments

Each student will work on two mini-projects, one using Python and the other using SQL. Student's evaluation is based on successful fulfillment of these two assignments.

Project requirements:

  • use open geospatial data as input
  • demonstrate knowledge of automated geospatial data processing and its analysis
  • provide results interpretation (discussion, graphs, tables, ...)

Python-based project assignment

  • Assignment 27.3.
  • Presentation 24.4.

Expected submission form: Jupyter Notebook or Python script

SQL-based project assignment

  • Assignment 24.4.
  • Presentation 15.5.

Expected submission form: SQL file

Install instructions for MS Windows

In Jupyter notebook run 

!pip install pandas geopandas

Literature

Citováno z „https://geo.fsv.cvut.cz/index.php?title=155ISDP_Introduction_to_Spatial_Data_Processing&oldid=42924“