Application
This unit of competency specifies the outcomes required to use computing platforms, software systems and image processing techniques to conduct advanced remote sensing analysis on hard copy and digital imagery. The unit covers preparing for work by analysing specifications and deciding appropriate techniques for collecting and analysing images, as well as appropriate hardware and software and image processing systems to perform the required image enhancements and manipulations. The unit also covers accessing and assessing available and suitable spatial datasets to identify constraints on use. The unit requires the ability to perform supervised and unsupervised classifications on datasets using classification algorithms, and to conduct related error analysis. It also requires the ability to merge remote sensing data and prepare data for geographic information system (GIS) integration.
The unit supports those who work in a technical management role in a spatial information services team, in areas such as cartography, town planning, mapping and GIS.
No licensing, legislative, regulatory, or certification requirements apply to this unit of competency at the time of endorsement.
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. | ||
1. | Determine image processing techniques. | 1.1. | Project specifications are identified and analysed to determine appropriate image, merger and modelling techniques according to organisational requirements. |
1.2. | Appropriate data collection and analysis techniques in remote sensing process are determined according to project specifications. | ||
1.3. | Suitable digital image processing techniques and digital image data formats are selected according to project specifications. | ||
1.4. | Additional characteristics of image and metadata are identified according to project specifications. | ||
2. | Select computing platforms and software systems for image processing. | 2.1. | Appropriate computing platforms and software systems are assessed for suitability according to project specifications. |
2.2. | Availability of suitable data is verified with potential suppliers according to project specifications. | ||
2.3. | Constraints on use of spatial data are assessed against project specifications and contingencies are planned according to organisational requirements. | ||
2.4. | Commercially available image processing systems are assessed to determine appropriate components, menu items, characteristics and statistics to meet project specifications. | ||
3. | Enhance and manipulate images. | 3.1. | Transformation routines using image calculations are conducted. |
3.2. | Edge enhancements and smoothing filters are applied using convolution matrices. | ||
3.3. | Image transformation is performed with channels of brightness, greenness and wetness. | ||
3.4. | Imagery for distribution is determined according to project specifications. | ||
4. | Perform classifications on datasets. | 4.1. | Thematic classifications and relative differentiations between supervised and unsupervised classification algorithms are determined. |
4.2. | Supervised classification algorithms are applied using training samples according to project specifications. | ||
4.3. | Error analysis is conducted to perform an approximate accuracy assessment of classifications. | ||
4.4. | Hard copy outputs are produced according to project specifications. | ||
5. | Conduct data merger and GIS integration. | 5.1. | Integration and merging techniques are identified and documented. |
5.2. | Techniques for integrating GIS data are identified and documented. | ||
5.3. | Remote sensing data is merged and integrated into GIS according to project specifications. | ||
Evidence of Performance
A person demonstrating competency in this unit must satisfy the requirements of the elements, performance criteria, foundation skills and range of conditions of this unit. The person must also use a computer and remote sensing software system to conduct advanced remote sensing analysis for two different projects.
While conducting the above advanced remote sensing analysis, the person must:
analyse and define job specifications, constraints and main work activities
analyse remote sensing data to identify and describe its characteristics, including:
metadata
soil
vegetation bodies
water
select and set up appropriate hardware and software systems to meet remote sensing project specifications
assess commercially available image processing systems to ensure their suitability in meeting project specifications
use remote sensing techniques to acquire spatial data from:
airborne platforms
ground observation
satellites
comply with organisational and legal requirements for accessing and using spatial data, including copyright, intellectual property and trade practices
comply with organisational requirements and industry-accepted standards relating to:
applying classification algorithms
quality and risk management
working safely when using above equipment
conduct web-based searches to identify available spatial data and verify its suitability to meet project specifications
exercise precision and accuracy when analysing and classifying remote sensing data
identify and assess constraints relating to use of remote sensing data
perform classifications on datasets using supervised and unsupervised classification algorithms and training samples
save digital images in a range of formats, including two of the following:
band interleaved by line (BIL)
band interleaved by pixel (BIP)
band sequential (BSQ)
run length encoding (RLE)
use integration and merging techniques to allow remote sensing data to be integrated into GIS
use digital image processing techniques to enhance and rectify images.
Evidence of Knowledge
A person demonstrating competency in this unit must demonstrate knowledge of:
industry-accepted techniques for applying supervised and unsupervised classification algorithms to remote sensing data
computer platforms and software systems for advanced remote sensing analysis and GIS integration
copyright and ownership constraints relating to spatial data
digital image processing techniques
digital image data formats, including BIL, BIP, BSQ and RLE
existing spatial datasets and dataset sources
image calculations required for transformation routines, including:
greenness ratios
greenness ratios plus dark value
normalised difference vegetation index (NDVI)
image enhancement, manipulation and merger techniques
methods for analysing metadata
methods for assessing commercially available image processing systems, including characteristics and statistics
methods for validating spatial data sources and constraints on use
key features of spatial referencing and coordinate systems
techniques for integrating GIS data, including:
cartographic modelling
environmental modelling
land cover classification.
Assessment Conditions
The following must be present and available to learners during assessment activities:
equipment:
computer, including computer-aided design (CAD) applications and software appropriate for developing two-dimensional (2-D) and three-dimensional (3-D) terrain visualisations
hardware, including printer, scanner, plotter and multimedia devices and peripherals
specifications:
project and design specifications
organisational policies, procedures and documentation relating to data privacy and information copyright
physical conditions:
access to equipped work station
relationships with team members and supervisor:
lead role in a team
relationships with client:
client consultation required.
Timeframe:
as specified by client and project requirements.
Assessor requirements
As a minimum, assessors must satisfy the assessor requirements in the Standards for Registered Training Organisations (RTOs) current at the time of assessment.
Foundation Skills
This section describes the language, literacy, numeracy and employment skills essential to performance in this unit but not explicit in the performance criteria. | |
Skill | Performance feature |
Learning skills to: | conduct research to source spatial data. |
Planning and organising skills to: | plan and prioritise activities to meet contractual requirements. |
Numeracy skills to: | analyse points, lines, curves and shapes in vector graphics apply and interpret algorithms to correctly classify images. |
Oral communication skills to: | liaise with clients and end users to identify remote sensing requirements. |
Reading skills to: | interpret graphical information in raster images. |
Technology skills to: | use computers and software applications to manipulate and enhance images use printers and plotters to produce hard copy outputs. |
Problem-solving skills to: | apply solutions to identified classification discrepancies. |
Range Statement
This section specifies work environments and conditions that may affect performance. Essential operating conditions that may be present (depending on the work situation, needs of the candidate, accessibility of the item, and local industry and regional contexts) are included. Bold italicised wording, if used in the performance criteria, is detailed below. | |
Metadata must include at least eight of the following: | availability conditions of use coordinate system currency custodian data accuracy data description date of acquisition licence quality source spatial data acquisition methodologies version control. |
Characteristics and statistics must include at least two of the following: | band selections hard copy outputs histogram plots look-up tables univariate and multivariate statistics. |
Image calculations must include at least one of the following: | greenness ratios greenness ratios plus dark value normalised difference vegetation index (NDVI). |
Techniques for integrating GIS data must include at least one of the following: | cartographic modelling environmental modelling land cover classification. |
Sectors
Surveying and spatial information services