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Remote sensing


Remote sensing in support of marine environmental monitoring

Other Details: 

Kimberley Marine Research Program: Project 1.4
Location: Kimberley Region
Project Leader:  David Antoine, Curtin University
Telephone: 9266 3572
Email: /

Download the Project Update


  • Phase I produced a review of remote sensing work and procedures with respect to the development of remote sensing methods to support improved and cost effective monitoring and management of the Kimberley region.
  • Phase II to quantify the reliability of remotely sensed turbidity products for use in  the Kimberley Region.

Proposed Methods

  • Data recorded remotely through platforms such as satellite and plane
  • Computer analysis and modelling

Project duration: 2013‐2016

Geographic range: The Kimberley region at various scales


  • A good understanding by management agencies of the applicability and reliability of remote sensed data as a management and monitoring tool, including knowledge of how to access data.
  • An improved understanding of the application and limitations of remotely sensed data for monitoring and managing the Kimberley region.
  • Improved access to remotely sensed data in appropriate formats
  • Increased uptake of remotely sensed data, at appropriate cost and with relevant information content
  • A good understanding of which remotely sensed products may be related to environmental indicators of condition
  • A good understanding by management agencies of the appropriate space and time scales required to monitor various environmental values (e.g. condition, change, classification) and the appropriateness of remotely sensed data for these tasks: i.e. assessing whether the information from remotely sensed data is “fit‐for‐purpose” and the suitability of surrogate measurements

Longer term goals beyond the life of the project: Use remotely sensed data to monitor change in the environment and values in a cost‐effective and meaningful way for the management of the Kimberley coastal region.


KMRP Lunch and Learn: Remote Sensing & Mapping Productivity (Monday, 28 November 2016) (Link to event page)

(Fearns ppt slides)

(Greenwood ppt slides)


Research Articles

Dorji P, Fearns P. A. (2016) Quantitative Comparison of Total Suspended Sediment Algorithms: A Case Study of the Last Decade for MODIS and Landsat-Based Sensors. Remote Sensing. 2016; 8(10):810 doi:10.3390/rs8100810

Dorji P, Fearns P, Broomhall M (2016) A Semi-Analytic Model for Estimating Total Suspended Sediment Concentration in Turbid Coastal Waters of Northern Western Australia Using MODIS-Aqua 250 m Data. Remote Sensing. 2016; 8(7):556 doi:10.3390/rs8070556