In: Wagner W„ Sz^kely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
Blasco, F., M. F. Bellan, and M. U. Chaudhury, 1992. 
Estimating the extent of floods in Bangladesh using SPOT data. 
Remote Sensing Environment. 39, pp. 167-178. 
Breiman, L., 2004. Random Forests. Machine Learning, 45 (1), 
pp. 5-32. 
Breiman, L., J. H. Friedman, R. A. Olshen, C. J. Stone, 1984. 
Classification and Regression Trees. Wadsworth & 
Brooks/Cole Advanced Books & Software, Pacific Grove, CA, 
1984. 
Deutsch, M., F. Ruggles, 1974. Optical data processing and 
projected applications of the ERTS-1 imagery covering the 
1973 Mississippi River Valley floods. Water Resource Bulletin, 
10 (5), pp. 1023-1039. 
Domenikiotis, C., A. Loukas, N. R. Dalezios, 2003. The use of 
NOAA/AVHRR satellite data for monitoring and assessment of 
forest fires and floods. Natural Hazards Earth System Science, 
3, pp. 115-128. 
France, M. J., P. D. Hedges, 1986. A hydrological comparison 
of Landsat TM, Landsat MSS, and black and white aerial 
photography in Damen. Smit, and Verstappen (Eds),” 
Proceedings 7th International Symposium, ISPRS (International 
Society Photogrammetry and Remote Sensing) Commission 
VII, Enschede, pp. 717-720. 
Gale, S. J., S. Bainbridge, 1990: The floods in eastern Australia. 
Nature, 345, pp. 767. 
Gao, B.-C., 1996. NDWI - A normalized difference water index 
for remote sensing of vegetation liquid water from space. 
Remote Sensing of Environment, 58, pp. 257-266. 
Gupta R. P., S. Baneiji, 1985. Monitoring of reservoir volume 
using Landsat data. Journal of Hydrology, 77, pp. 159-170. 
Hallberg, G. R., B. E. Hoyer, A. Rango, 1973. Application of 
ERTS-1 imagery to flood inundation mapping. NASA Special 
Pub. No. 327, Symposium on significant results obtained from 
the Earth Resources Satellite-1, Vol. 1, Technical presentations, 
section A, 745-753. 
Hansen, M.C., R.S. DeFries, J.R.G. Townshend,R. Sohlberg, C. 
Dimiceli , M. Carroll, 2002. Towards an operational MODIS 
continuous field of percent tree cover algorithm: examples 
using AVHRR and MODIS data. Remote Sensing of 
Environment 83, 303-319. 
Han, J.W., Kamber, M., 2001. Data Mining: Concept and 
Techniques. Morgan Kaufmann Publishers, San Francisco, CA, 
550pp. 
Kohavi, R., 1996. Scaling Up the Accuracy of Naive-Bayes 
Classifiers: a Decision-Tree Hybrid. Proceedings of the Second 
International Conference on Knowledge Discovery and Data 
Mining, 1996. 
Jensen, J. R., M. E. Hodgson, E. Christensen, H. E., Jr. Mackey, 
L. R. Tinney, R. Sharitz, 1986. Remote sensing inland 
wetlands: a multispectral approach, Photogrammetric 
Engineering Remote Sensing, 52, pp. 87-100. 
McGinnis, D. F. and A. Rango, 1975. Earth Resources Satellite 
systems for flood monitoring. Geophysical Research Letters, 2 
(4), pp. 132-135. 
Morrison, R. B., P. G. White, 1976. Monitoring flood 
inundation. U.S. Geol. Surv. Prof. Pap. 929, ERTS-1, A New 
Window on Our Planet, pp. 196-208. 
Pope, K. O., E. J. Sheffner, K. J. Linthicum, C. L. Bailey, T. M. 
Logan, E. S. Kasichke, K. Bimey, A. R. Njogu, C. R. Roberts, 
1992. Identification of Central Kenyan Rift Valley Fever vims 
vector habitats with Landsat TM and evaluation of their 
flooding status with airboume imaging radar. Remote Sensing of 
Environment, 40, 185-196. 
Quinlan, R. J., 1992. Learning with Continuous Classes. In: 5th 
Australian Joint Conference on Artificial Intelligence, 
Singapore, pp. 343-348. 
Quinlan, J.R., 1993. C4.5: Programs for Machine Learning. 
Morgan Kaufmann Publishers, San Francisco, CA, 316pp. 
Rasid, H., M. A. H. Pramanik, 1993. Areal extent of the 1988 
flood in Bangladesh: how much did the satellite imagery show? 
Natural Hazards, 8, pp. 189-200. 
Running, S., T. R. Loveland, L. Pierce, 1995. A Remote 
Sensing Based Vegetation Classification Logic for Global Land 
Cover Analysis. Remote Sensing Environment, 51, pp. 39-48. 
Sheng, Y., P. Gong, Q. Xiao, 2001. Quantitative dynamic flood 
monitoring with NOAA AVHRR. International Journal of 
remote sensing, 22 (9), pp. 1709-1724. 
Smith, L. C., 1997. Satellite remote sensing of river inundation 
area, stage, and discharge: A review. Hydrological Processes, 
11 (10), pp. 1427-1439. 
Toyra, J., A. Pietroniro, L. W. Martz LW, et al., 2002. A multi 
sensor approach to wetland flood monitoring. Hydrological 
Processes, 16 (8), pp. 1569-1581. 
Toyra, J., A. Pietroniro, L. W. Martz, 2001. Multisensor 
hydrologic assessment of a freshwater wetland. Remote Sensing 
of Environment, 75 (2), pp. 162-173. 
Vila da Silva, J. S., H. J. H. Kux, 1992. Thematic mapper and 
GIS data integration toevaluate the flooding dynamics within 
the Panatal, Mato Grosso do Sul State, Brazil, Proceedings, 
1992. Int. Geosci. Remote Sens. Symp. (IGARSS '92), pp. 1478- 
1480. 
Wang ,Y., Witten, I. H., 1997. Induction of model trees for 
predicting continuous classes. Poster papers of the 9th European 
Conference on Machine Learning, 1997. 
Watson, J. P., 1991. A visual interpretation of a Landsat mosaic 
of the Okavango Delta and surrounding area. Remote Sensing of 
Environment 35, 1-9. 
ACKNOWLEDGEMENTS 
This study was supported by the GOES-R program through the 
GOES-R Algorithm Working Group. The manuscript contents 
are solely the opinions of the authors and do not constitute a 
statement of policy, decision, or position on behalf of NOAA or 
the U. S. Government.