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By knowing in advance the programming level of the participants will help us to set a better the course syllabus. No previous programming skills are required to attend the training, but we expect the participants to have strong motivation in learning command-line interface.
Please spend a moment to answer:
Never used = I never used
Yes but very basic level = I started to use few months ago but I still writing simple scripts
Yes intermediate level = I use from several years and I'm able to combine few languages.
Yes advance level = I use from several years and I'm able to combine few languages in multicore enviroment.
Never used = I never used
I know very basic commands = I use simple commands but only in the terminal
I can write simple scripts = I can use for loop and if condition
I am a very experienced user = I can combine several languages using bash and i can use xargs & qsub for multicore
Never used = I never used
I know very basic commands = I use simple commands but only in the python terminal
I can write simple scripts = I can use for loop and if condition
I am a very experienced user = I can work with matrix and do complex math operation
I am a very web experienced user = I use python manly for web developing
Never used = I never used
Only graphical user interface = I use graphical user interface but I started to use command lines
I can write basic scripts = I can write basic scripts using if condition and for loop
I am an experienced user = I write my own functions and use libraries for parallel processing.
Never used = I never used
Basic knowledge = I just use print $1 and some if conditions
I am an experienced user = I use for loop to loop trough the columns, indexing and associative array.
Never used = I never used in my life
Only graphical user interface = I use graphical user interface
I can write basic scripts = I can write basic scripts using combining the different GRASS commands
I am an experienced user = I write complex scripts, build Location/Mapset on the flight set GRASS variable for batch processing
Never used = I never used
Only used in QGIS graphical user interface = I use only the QGIS plugging
I can write basic scripts = I can use GDAL/OGR commands in simple scripts
I am a good user = I combine GDAL/OGR with GRASS under BASH or Python
I am an experienced user = I use GDAL/OGR API under Python
In this section the course participants can post comments/suggestions or what you would like to achieve with this course. Remember to write your name in the “real-name box” in order to show who wrote the post.
Questionnaire Discussion Forum
I am interested in achieving a stronger ability to approach spatial data analysis and representation. I am specifically interested in R because I am trying to develop my coding skills for data analysis and generating figures using that program, so it would be nice to consolidate my skills. However, I anticipate that the skills acquired during this short-course will extend beyond a particular program, but will increase confidence in how to acquire and use spatial data for research.
Since I am very new to R and command line interfaces, I would like to develop a level of comfort with basic statistical analyses and a familiarity with the resources available for spatio-temporal data analysis that will enable me to pursue more advanced questions in the future. My project relies on analyzing large amounts of spatial data on animal locations in relation to environmental variables. Any case studies or examples related to animal movement would be much appreciated.
Thanks!
I am familar with ArcGis and some software for mapping because my major is in cartography and GIS. I am very interesting in the analysis of spatial and temporal data and visualization. Also I am very interesting in how to integrate the result of data capturing, data analysing and data visualization.If you can introduce the technique of how to use the high performance computing for the big data analysis, I will be very glad. Thanks Jie
I have some experience in R and Python (and ArcPy library) making iterative analysis. I would like to learn how to do these kind of scripts in a such powerful tool as GRASS/AwK/GDAL and if is possible 'call' GRASS executions trough R commands.
Greetings from Colombia
Yes, all these points will be address in the course.
I would like to get a better sense of strengths, weaknesses of the alternative FOSS programs for different geospatial tasks. I'm also keenly interested in learning how to integrate tools into one workflow (e.g., calling other functions or scripts using one software from another - I've done some of this with the system function in R, but I still have a lot to learn). Karis
I would like to make the same: call functions from another software. I hope that we can learn how-to. Greetings
Yes Karis and Ivan, we will have a dedicate session of sw integration to build up dynamic scripting procedure.
My interest in the workshop is threefold: First, I'd like to learn about capabilities of open source software for geospatial analysis. I am an ArcGIS user, and I have experience with ERDAS, so I'd like to see if I can conduct analysis at same level of complexity using open source software. Second, I'd like to learn how to integrate R and Python into geospatial/remote sensing analysis. Three, I'd like to conduct data formatting in Python (I have much more experience in R than Python, so in the past, I have called on R from python to format data in ArcGIS environment, and I'd like to know how to do that without R for simplicity ( I realize this last one may be a bit out of scope of the workshop, but if we can get provided some examples of code how to do that, that would be great). It would be very beneficial for my learning if the workshop focused on specific examples, and we could go through scripts together to understand what each line of code does. Lectures with a lot of programming jargon typically get me disengaged fairly quickly.
I would like to be able to integrate the spatial domain in the temporal analysis of Vegetation Indexes, such as the MODIS/NDVI. I have been working with Southern Brazilian Pampa grasslands and trying to relate its phenology with different environmental and meteorogical characteristics.
Aquire new skills to apply in research areas of interest: bigdata processing of Landsat imagery; Integration of multiple datasets over space and time; NDVI analysis with specific thresholds for different regions and integration with other datasets (e.g. DEM). New to coding, but extensive experience with RS analysis using ENVI & ERMapper.
I am working with OpenStreetMap planet files and history files. The history files contain every edit along with metadata and a time stamp. I am interested in time series analysis to better understand the development of this dataset as it relates to data quality.
I hope to gain a deeper understanding of the best uses for different software platforms, and some of the computing language details for making those platforms efficient. I want to become more capable with maximizing the efficiency of computing in general and try using cluster and web-based computing. I am also interested in using these platforms for data management if possible.
Please consider that we will not cover any web application and real data management. We will focus more in data analysis using scripting routines in local pc and in remote server.
I'm currently a user of ArcGIS, ENVI, python and R, however I'm interested in open-source software for research purposes, potentially including open-source tools to process lidar (PDAL). Additionally, I want to learn more about OS software for educational purposes to design courses to teach these tools to undergrads and grads at the University level.
I'm interested in integrating large datasets into an ecological and epidemiological/genetic data modelling framework, particularly using LIDAR data in conjunction with land use, plant ID, soil qualities, management regimes, disease prevalence, and genetic distributions. I have used R extensively at a basic to an intermediate level, ArcGIS to a limited degree, and made varying attempts to teach myself QGIS and Python. After learning Mathematica and LaTeX I grew much more comfortable with coding and am looking forward to developing a more powerful platform for future research.
Pieter will have a nice example of LIDAR and Land Use classification.
I have basic to intermediate knowledge of all the softwares and libraries in this survey. I would like to further hone these skills and learn how to link them together to leverage the strengths of each of these packages.