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Articles

ESTIMATION OF RUNOFF INDEX USING LANDSAT (TM) DATA AND AN ARTIFICIAL NEURAL NETWORK SYSTEM

Pages 155-166 | Published online: 23 Jan 2013

References

  • An , P. and Chung , C. F. 1994 . “Neural Network Approach for Geological Mapping: Technical Background and Case Study.” . Canadian Journal of Remote Sensing , 20 ( 3 ) : 293 – 301 .
  • Bishof , H. , Schneider , W. and Pinz , A. J. 1992 . “Multi-spectral Classification of Landsat Images Using Neural Networks.” . IEEE Transaction on Geoscience and Remote Sensing , 30 ( 3 ) : 482 – 490 .
  • Bolwes , D. S. and Connell , P. E. 1991 . Recent Advances in the Modeling of Hydrologic Systems London : Kluwer Academic Publishers .
  • Blanchard , B. J. 1975 . Investigation of Use of Space Data in Watershed Hydrology. Final Report, NASA Contract S-70251-AG, Goddard Space Flight Center, Greenbelt, Maryland
  • Bondelid , T. R. , Jackson , T. J. and McCuen , R. H. 1980 . Comparison of Conventional and Remote Sensed Estimates of Runoff Curve Numbers in Southeastern Pennsylvania. American Congress of Surveying and Mapping/American Society of Photogrammetry Convention, St Louis , MO
  • Civco , D. 1993 . “Artificial Neural Networks for Land-Cover Classification and Mapping.” . International Journal of Geographic Information Systems , 7 ( 2 ) : 173 – 186 .
  • Decatur , S. E. 1989 . Applications of Neural Networks to Terrain Classification. M.Sc. thesis, Massachusetts Institute of Technology
  • Eastman , J. R. 1992 . IDRISI User's Guide. Clark University, Massachusetts 178
  • Emaruchi , B. , Jin , Y. , Sauchyn , D. and Kite , G. 1994 . Land Cover Mapping Using an Artificial Neural Network. Proceedings of the Commission IV Symposium on Mapping and Geographic Information Systems (May 31 — June 3, 1994), UK., RICS Books
  • Heerman , H. D. and Khozenie , N. 1992 . “Classification of Multi-spectral Remote Sensing Image Data Using Back Propagation Neural Network.” . IEEE Transaction on Geoscience and Remote Sensing , 30 ( 1 ) : 81 – 88 .
  • Hepner , G. F. 1990 . “Artificial Neural Network Classification Using a Minimal Training Set: Comparison to Conventional Supervised Classification.” . Photogrammetric Engineering and Remote Sensing , 56 ( 4 ) : 469 – 473 .
  • NeuralWare . 1991 . Neural Computing. NeuralWare Inc., Pittsburgh, PA
  • Ragan , R. M. and Jackson , T. J. 1980 . “Runoff Synthesis Using Landsat and SCS Model.” . Journal of the Hydraulic Division, ASCE , 5 : 667 – 678 .
  • Rango , A. 1985 . “Assessment of Remote Sensing Input to Hydrologie Models.” . Water Resources Bulletin , 21 ( 3 ) : 423 – 432 .
  • Rumelhart , D. E. , Hinton , G. and McClelland , J. L. 1986 . Parallel Distributed Processing, vol 1 Cambridge : MIT Press .
  • Sharma , K. D. and Singh , S. 1992 . “Runoff Estimation Using Landsat Thematic Mapper Data and the SCS Model.” . Hydrological Science Journal , 37 : 39 – 52 .
  • Slack , R. B. and Welch , R. 1980 . “Soil Conservation Service Runoff Curve Number Estimates from Landsat Data.” . Water Resources Bulletin , 16 : 887 – 893 .
  • Still , D. A. and Shih , S. F. 1985 . “Using Landsat to Classify Land Use for Assessing the Basinwide Runoff Index.” . Water Resources Bulletin , 21 ( 6 ) : 931 – 940 .
  • Stuebe , M. M. and Johnston , D. M. 1990 . “Runoff Volume Estimation Using GIS Techniques.” . Water Resources Bulletin , 26 ( 4 ) : 611 – 620 .
  • Tiwari , K. N. , Kumar , P. , Sebastian , M. and Pal , D. K. 1991 . “Hydrologie Modelling for Runoff Determination: Remote Sensing Techniques.” . Water Resources Development , 7 : 178 – 184 .
  • U.S. Soil Conservation Service. 1972 . National Engineering Handbook, Section 4, Hydrology. United States Department of Agriculture Washington , DC : United States Government Printing Office .
  • Wann , M. , Hediger , T. and Greenbaun , N. N. 1990 . The Influence of Training Sets on Generalization in FeedForward Neural Networks. Proceeding of IEEE Fourth International Conference in Neural Networks, 3 137 – 142 .
  • Zevenbergen , A. W. 1985 . Runoff Curve Numbers for Rangeland from Landsat Data. Hydrology Laboratory Technical Report HL85–1, Agricultural Research Service, Beltsville, Maryland
  • Zurada , J. M. 1992 . Introduction to Artificial Neural Systems. West Publishing Company

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