Authors / CoAuthors
Mueller, N. | Curnow, S. | Melrose, R. | Purss, M. | Lewis, A.
Abstract
CONTROL ID: 1813538 TITLE: 'Big Data' can make a big difference: Applying Big Data to National Scale Change Analyses AUTHORS (FIRST NAME, LAST NAME): Norman Roland Mueller1, Steven Curnow1, Rachel Melrose1, Matthew Brian John Purss1, Adam Lewis1 INSTITUTIONS (ALL): 1. Geoscience Australia, Canberra, ACT, Australia. ABSTRACT BODY: The traditional method of change detection in remote sensing is based on acquiring a pair of images and conducting a set of analyses to determine what is different between them. The end result is a single change analysis for a single time period. While this may be repeated several times, it is generally a time consuming, often manual process providing a series of snapshots of change. As datasets become larger, and time series analyses become more sophisticated, these traditional methods of analysis are unviable. The Geoscience Australia 'Data Cube' provides a 25-year time series of all Landsat-5 and Landsat-7 data for the entire Australian continent. Each image is orthorectified to a standard set of pixel locations and is fully calibrated to a measure of surface reflectance (the 25m Australian Reflectance Grid [ARG25]). These surface reflectance measurements are directly comparable, between different scenes, and regardless of whether they are sourced from the Landsat-5 TM instrument or the Landsat-7 ETM+. The advantage of the Data Cube environment lies in the ability to apply an algorithm to every pixel across Australia (some 1013 pixels) in a consistent way, enabling change analysis for every acquired observation. This provides a framework to analyse change through time on a scene to scene basis, and across national-scale areas for the entire duration of the archive. Two examples of applications of the Data Cube are described here: surface water extent mapping across Australia; and vegetation condition mapping across the Murray-Darling Basin, Australia's largest river system.. Ongoing water mapping and vegetation condition mapping is required by the Australian government to produce information products for a range of requirements including ecological monitoring and emergency management risk planning. With a 25 year archive of Landsat-5 and Landsat-7 imagery hosted on an efficient High Performance Computing (HPC) environment, high speed analyses of long time series for water and vegetation condition are now viable. www.ga.gov.au KEYWORDS: 1906 INFORMATICS Computational models, algorithms, 1988 INFORMATICS Temporal analysis and representation, 1980 INFORMATICS Spatial analysis and representation. (No Image Selected) (No Table Selected) Additional Details Previously Presented Material: Contact Details CONTACT (NAME ONLY): Norman Mueller CONTACT (E-MAIL ONLY): norman.mueller@ga.gov.au TITLE OF TEAM:
Product Type
nonGeographicDataset
eCat Id
78465
Contact for the resource
Custodian
Point of contact
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia
Keywords
-
- External PublicationConference Paper
- Australian and New Zealand Standard Research Classification (ANZSRC)
-
- Earth Sciences
-
- Published_Internal
Publication Date
2013-01-01T00:00:00
Creation Date
Security Constraints
Legal Constraints
Status
Purpose
Maintenance Information
unknown
Topic Category
geoscientificInformation
Series Information
Lineage
Unknown
Parent Information
Extents
Reference System
Spatial Resolution
Service Information
Associations
Downloads and Links
Source Information
Source data not available.