International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
Priority; High Error / High Change -High Update Priority; Low
Error / Low Change -Low Update Priority; Low Error / High
Change -Medium Update Priority (Figure 3). The decision
boundaries were initially set to 20% definite errors and 50,000
ha (20% of the highest change rate). Using these thresholds it is
recommended that mapsheets SIS0 and SG56 are updated as a
matter of high priority; a further seven mapsheets (SD52, SI53,
SH56, SH55, SH50, SF55 and SG55) should be updated with a
medium priority. The remaining 27 mapsheets performed well
in the error rate versus quantum of change analysis and have a
low update priority.
4. CONCLUSIONS
The fuzzy evaluation methodology presented here was
developed as a useful means for determining if there are
problems inherent in the land cover change maps for multiple
periods produced from satellite imagery, and in the
classification methodology used to produce them. Although the
fuzzy nature of the information produced does not provide a
readily understood means of | determining the
accuracy/inaccuracy of a land cover change map, we believe
that having information that forces an analyst to examine a
variety of aspects of classification accuracy is a positive aspect
of the methodology because it forces a map consumer to take
responsibility for the ultimate use to which the map information
is put. The qualitative statements made by photo-interpreters
regarding general observations about photographic quality or
the general misclassification of an area covered by an aerial
photograph are also instructive for subsequent improvement
cycles. The combination of textual and statistical (tabulated)
information provides for continuous improvement in addition to
static reliability statements.
The continuous improvement approach executed in this
program aims to do more than just verify the reliability of the
NCAS mapping. Continuous improvement responds to the
ongoing development and updating of the NCAS land cover
program by looking at the source and significance of potential
errors. This allows for a targeted and prioritised rectification of
any problems that can be assessed and, if necessary, further
amended on each round of updating and continuous
improvement.
Further work:
The most recent verification period (2000-2002) employed
IKONOS imagery as the high-spatial resolution reference data.
The effect of this new dataset and inter-comparison to the aerial
photographic archive has not been quantified.
Acknowledgements:
The help and advice of following individuals is acknowledged:
Alexander Mager, Suzanne Liebchen, Suzanne Furby.
References:
Cacetta, P., 1997. Remote sensing, GIS and Bayesian
knowledge-based methods for monitoring land condition. Ph.D.
thesis, School of Computing, Curtin University of Technology,
Perth, Western Australia.
Cohen, J., 1960. A coefficient of agreement for nominal scales.
Education and Psychological Measurement 20:37-40.
Congalton, R., 1991. A review of assessing the accuracy of
classifications of remotely sensed data. Remote Sensing of the
Environment 37:35-46.
Danaher, T., Wu, X., Campbell, N., 2001. Bidirectional
reflectance distribution function approaches to radiometric
calibration of Landsat TM imagery, Proceedings: IGARSS
2001, Sydney, Australia.
Foody, G., 1996. Approaches for the production and evaluation
of fuzzy land cover classifications from remotely-sensed data.
International Journal of Remote Sensing 17:1317-1340.
Furby, S., 2002. Land Cover Change: Specification for Remote
Sensing Analysis. National Carbon Accounting System,
Technical Report No. 9, Australian Greenhouse Office,
Canberra, ACT ISSN: 1442 6838.
Furby, S., Campbell, N., 2001. Calibrating images from
different dates to “like value” digital counts. Remote Sensing of
the Environment 77:186-196.
Furby, S., Woodgate, P., 2001 Pilot Testing Of Remote Sensing
Methodology For Mapping Land Cover Change, National
Carbon Accounting System Technical Report No. 16 ISSN:
1442 6838
Gopal, S., Woodcock, C., 1994. Theory and methods for
accuracy assessment of thematic maps using fuzzy sets.
Photogrammetric Engineering and Remote Sensing 60:181-188.
Jones, S., Lowell, K., Woodgate, P., Buxton, L., Mager, A.
Liebchen, S., 2004 Update On The National Carbon Accounting
System Continuous Improvement And Verification
Methodology, National Carbon Accounting System Technical
Report No. 46 ISSN: 1442 6838
Justice, C., Belward, A., Morisette, J., Lewis, P., Privette, J., &
Baret, F., 2000 Developments in the ‘validation’ of satellite
sensor products for the study of the land surface. International
Journal of Remote Sensing, 21(17), 3383- 3390.
Lein, J., 2003. Applying evidential reasoning methods to
agricultural land cover classification. International Journal of
Remote Sensing 24(21):4161-4180.
Lowell, K., Woodgate, P., Jones, S., Richards, G., 2003
Continuous Improvement of the National Carbon Accounting
System Land Cover Change Mapping, National Carbon
Accounting System Technical Report No. 39 ISSN: 1442 6838
Reguzzoni, M., Sanso, F., Venuti, G., Brivio, P., 2003.
Bayesian classification by data augmentation. International
Journal of Remote Sensing 24(20):3961-3981.
Richards, G., Furby, S., 2003 Sub-hectare Land Cover
Monitoring; Developing a National Scale Time-Series Program
The 11th Australasian Remote Sensing and Photogrammetry
Conference, Brisbane, Queenland, Australia [SBN 0-9581366-
0-2
Tian Y.. Woodcock C. E., Wang Y., Privette J. L., Shabanov N.
V., Zhou L., Zhang Y., Buermann W., Dong J., Veikkanen B.,
Hame T., Andersson K., Ozdogan M., Knyazikhin Y., Myneni
R. B., 2002 Multiscale analysis and validation of the MODIS
LAI product I. Uncertainty assessment Remote Sensing of
Environment 83, 414—430.
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