Formats and tools
- Unit Description
- Reconstruct the unit from the xml and display it as an HTML page.
- Assessment Tool
- an assessor resource that builds a framework for writing an assessment tool
- Assessment Template
- generate a spreadsheet for marking this unit in a classroom environment. Put student names in the top row and check them off as they demonstrate competenece for each of the unit's elements and performance criteria.
- Assessment Matrix
- a slightly different format than the assessment template. A spreadsheet with unit names, elements and performance criteria in separate columns. Put assessment names in column headings to track which performance criteria each one covers. Good for ensuring that you've covered every one of the performance criteria with your assessment instrument (all assessement tools together).
- Wiki Markup
- mark up the unit in a wiki markup codes, ready to copy and paste into a wiki page. The output will work in most wikis but is designed to work particularly well as a Wikiversity learning project.
- Evidence Guide
- create an evidence guide for workplace assessment and RPL applicants
- Competency Mapping Template
- Unit of Competency Mapping – Information for Teachers/Assessors – Information for Learners. A template for developing assessments for a unit, which will help you to create valid, fair and reliable assessments for the unit, ready to give to trainers and students
- Observation Checklist
- create an observation checklist for workplace assessment and RPL applicants. This is similar to the evidence guide above, but a little shorter and friendlier on your printer. You will also need to create a seperate Assessor Marking Guide for guidelines on gathering evidence and a list of key points for each activity observed using the unit's range statement, required skills and evidence required (see the unit's html page for details)
- Self Assessment Survey
- A form for students to assess thier current skill levels against each of the unit's performance criteria. Cut and paste into a web document or print and distribute in hard copy.
- Moodle Outcomes
- Create a csv file of the unit's performance criteria to import into a moodle course as outcomes, ready to associate with each of your assignments. Here's a quick 'how to' for importing these into moodle 2.x
- Registered Training Organisations
- Trying to find someone to train or assess you? This link lists all the RTOs that are currently registered to deliver CPPSIS6037, 'Conduct advanced remote sensing analysis'.
- Google Links
- links to google searches, with filtering in place to maximise the usefulness of the returned results
- Reference books for 'Conduct advanced remote sensing analysis' on fishpond.com.au. This online store has a huge range of books, pretty reasonable prices, free delivery in Australia *and* they give a small commission to ntisthis.com for every purchase, so go nuts :)
Elements and Performance Criteria
Elements describe the essential outcomes.
Performance criteria describe the performance needed to demonstrate achievement of the element. Where bold italicised text is used, further information is detailed in the range of conditions.
Determine image processing techniques.
Project specifications are identified and analysed to determine appropriate image, merger and modelling techniques according to organisational requirements.
Appropriate data collection and analysis techniques in remote sensing process are determined according to project specifications.
Suitable digital image processing techniques and digital image data formats are selected according to project specifications.
Additional characteristics of image and metadata are identified according to project specifications.
Select computing platforms and software systems for image processing.
Appropriate computing platforms and software systems are assessed for suitability according to project specifications.
Availability of suitable data is verified with potential suppliers according to project specifications.
Constraints on use of spatial data are assessed against project specifications and contingencies are planned according to organisational requirements.
Commercially available image processing systems are assessed to determine appropriate components, menu items, characteristics and statistics to meet project specifications.
Enhance and manipulate images.
Transformation routines using image calculations are conducted.
Edge enhancements and smoothing filters are applied using convolution matrices.
Image transformation is performed with channels of brightness, greenness and wetness.
Imagery for distribution is determined according to project specifications.
Perform classifications on datasets.
Thematic classifications and relative differentiations between supervised and unsupervised classification algorithms are determined.
Supervised classification algorithms are applied using training samples according to project specifications.
Error analysis is conducted to perform an approximate accuracy assessment of classifications.
Hard copy outputs are produced according to project specifications.
Conduct data merger and GIS integration.
Integration and merging techniques are identified and documented.
Techniques for integrating GIS data are identified and documented.
Remote sensing data is merged and integrated into GIS according to project specifications.