Neural network classification of convective airmasses for a flood forecasting system

International Journal of Remote Sensing

Volumn 18, Issue 4, 1997, Pages 887-898

  Pankiewicz, G S ^a  

^a MET OFFICE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; FLOODS; OBJECT ORIENTED PROGRAMMING; PATTERN RECOGNITION; WEATHER FORECASTING; WEATHER SATELLITES;

AIRMASS CLASSIFICATION; METEOSAT IMAGE; SURFACE PRESSURE ANALYSIS;

NEURAL NETWORKS;

AIR MASS; AIR MASS CLASSIFICATION; CLASSIFICATION; CONVECTIVE STORM; FLOOD; FLOOD FORECASTING; FLOOD WARNING SYSTEM; GANDOLF; HAZARD MITIGATION; MULTILAYER PERCEPTRON; NATURAL HAZARD; NEURAL NETWORK; REMOTE SENSING; THUNDERSTORM; WEATHER FORECAST;

UK;

EID: 0031103948     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/014311697218818     Document Type: Article

References (16)

1. ALLam, R. J., Dibben, P., HoLpin, G., Smith, F., and Standley, A. P., 1990, The use of satellite imagery products for operational meteorology. Satallite Meteorology and Oceanography: Proceedings of the 5th Conference held in London, U.K., 3-7 September 1990 (Boston: American Meteorological Society), pp. 401-403.
2. Bankert, R. L., 1994, Cloud classification of AVHRR imagery in maritime regions using a probabilistic neural network. Journal of Applied Meteorology, 33, 909-918.
3. Conier, C. G., Hardaker, P. J., and Pierce, C. E., 1995, The GANDOLF system: an automatic procedure for forecasting convection. Proceedings of the 27th Conference on Radar Meteorology held in Vail, Colorado, 9-13 October 1995 (Boston: American Meteorological Society), pp. 606-608.
4. Foody, G. M., McCunoch, M. B., and Yates, W. B., 1995, The effect of training set size and composition on artificial neural network classification. International Journal of Remote Sensing, 16, 1707-1723.
5. Golding, B. W., 1994, Nimrod = FRONTIERS + NWP. Mercury: Newsletter of the U.K. Meteorological Office, 92, 8.
6. Gu, Z. Q., Duncan, C. N., Grant, P. M., Cowan, C. F. N., Renshaw, E., and MuggLestone, M. A 1991, Textural and spectral features as an aid to cloud classification. International Journal of Remote Sensing, 12, 953-968.
7. Hand, W. H., and Conway, B. C., 1995, An object-oriented approach to nowcasting showers. Weather and Forecasting, 10, 327-341.
8. Lee, J., Weger, R. C., Sengupta, S. K., and Welch, R. M., 1990, A neural network approach to cloud classification. I.E.E.E. Transactions on Geoscience and Remote Sensing, 28, 846-855.
9. MacLaren I., Walder, P., and Reid, C., 1994, Neural networks and cloud classification. Meteosat Scientific Users’ Conference: Proceedings of the 10th EUMETSAT Conference held in Cascais, Portugal, 5-9 September 1994, EUM P15 (Darmstadt: EUMETSAT), pp. 541-547.
10. Pankiewicz, G. S., 1995 a, Pattern recognition techniques for the identification of cloud and cloud systems. Meteorological Applications, 2, 257-271.
11. Pankiewicz, G. S., 1995 b, A neural network cloud classifier trained with AVHRR data for use on Meteosat imagery. Meteorological Satellite Data Users' Conference: Proceedings of the EUMETSAT Conference held in Winchester, U.K., 4-8 September 1995, EUM P17 (Darmstadt: EUMETSAT), pp. 393-400.
12. Peak, J. E., and Tag, P. M., 1992, Toward automated interpretation of satellite imagery for Navy shipboard applications. Bulletin of the American Meteorological Society, 73, 995-1008.
13. Pierce, C. E., Conier, C. G., and Hardaker, P. J., 1995, Forecasts of heavy convective rain for use within a flash flood warning system. National Hydrology Symposium: Proceedings of the 5th BHS Symposium held in Edinburgh, U.K., 4-7 September 1995 (British Hydrological Society), pp. 4.17-4.23.
14. Rumelhart, D. E., Hinton, G. E., and Winiams, R. J., 1986, Learning representations by back-propagating errors. Nature, 232, 533-536.
15. Tovinkere, V. R., Penaloza, M., Logar, A., Lee, J., Weger, R. C., Berendes, T. A., and Welch, R. M., 1993, An intercomparison of artificial intelligence approaches for polar scene classification. Journal of Geophysical Research, 98 D3, 5001-5016.
16. Welch, R. M., Sengupta, S. K., Goroch, A. K., Raindra, P., Rangaraj, N., and Navar, M. S., 1992, Polar cloud and surface classification using AVHRR imagery: an intercomparison of methods. Journal of Applied Meteorology, 31, 405-420.