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Maximising automation in land cover monitoring with change detection

Citation

Wessels, K and van den Bergh, F and Steenkamp, K and Swanpoel, D and McAlister, B and Salmon, B and Roy, D and Kovalskyy, V, Maximising automation in land cover monitoring with change detection, International Conference of the African Association of Remote Sensing of the Environment 2014: Programme, 27-31 October 2014, University of Johannesburg, South Africa, pp. 1-8. (2014) [Refereed Conference Paper]


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Copyright 2014 the Author

Official URL: http://www.aarse2014.org/

Abstract

With the availability of free moderate spatial resolution Landsat satellite data land cover mapping systems are moving away from classifying single date cloud-free images to classifying data time-series. This requires the ability to handle large volumes of data, which in turn requires high levels of automation in data pre-processing, image classification and change detection. This paper reports on the progress made towards the development of a more automated land cover monitoring system for South Africa. We firstly employed a local installation of the Web-enabled Landsat Data (WELD) system to serve as the data "backbone" for pre-processing and storing large amounts of Landsat data sensed over South Africa. A system was developed to rapidly update land cover maps for previous mapped areas using highly-automated, training data generation, scalable random forest classification, accuracy assessment, change detection and rapid, online operator validation. The technology is aimed at assisting government and industry to provide land cover data at a much higher update frequency to address ever-increasing demands for land cover products and services.

Item Details

Item Type:Refereed Conference Paper
Keywords:land cover, change detection, Landsat
Research Division:Engineering
Research Group:Environmental Engineering
Research Field:Environmental Technologies
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Engineering
Author:Salmon, B (Dr Brian Salmon)
ID Code:101959
Year Published:2014
Deposited By:Engineering
Deposited On:2015-07-21
Last Modified:2018-04-05
Downloads:264 View Download Statistics

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