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Statistical Modeling on Weather Parameters to Develop Forest Fire Forecasting System
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 Title & Authors
Statistical Modeling on Weather Parameters to Develop Forest Fire Forecasting System
Trivedi, Manish; Kumar, Manoj; Shukla, Ripunjai;
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 Abstract
This manuscript illustrates the comparative study between ARIMA and Exponential Smoothing modeling to develop forest fire forecasting system using different weather parameters. In this paper, authors have developed the most suitable and closest forecasting models like ARIMA and Exponential Smoothing techniques using different weather parameters. Authors have considered the extremes of the Wind speed, Radiation, Maximum Temperature and Deviation Temperature of the Summer Season form March to June month for the Ranchi Region in Jharkhand. The data is taken by own resource with the help of Automatic Weather Station. This paper consists a deep study of the effect of extreme values of the different parameters on the weather fluctuations which creates forest fires in the region. In this paper, the numerical illustration has been incorporated to support the present study. Comparative study of different suitable models also incorporated and best fitted model has been tested for these parameters.
 Keywords
ARIMA;Exponential Smoothing;temperature;maximum;minimum;wind speed;radiation;
 Language
English
 Cited by
 References
1.
Agee, J. K. and Flewelling, R. (1983). A fire cycle model based on climate for the Olympic Mountains, Washington, In Proceeding of Fire and Forest Meteorology Conference, 1, 32-37

2.
Anderson, H. E. (1983). Predicting wind-driven wild land fire size and shape, USDA Forest Service Research Paper INT-305

3.
Baker, W. L. (1989a). A review of models of landscape change, Landscape Ecology, 2, 111-133 crossref(new window)

4.
Baker, W. L. (1989b). Landscape ecology and nature reserve design in the Boundary Waters Canoe area, Minnesota, Ecology, 10, 23-35

5.
Baker, W. L. (1992). The landscape ecology of large disturbances in the design and management of nature reserves, Landscape Ecology, 1, 181-194 crossref(new window)

6.
Baker, W. L., Egbert, S. L. and Frazier, G. F. (1991). A spatial model for studying the effects of climatic change on the structure of landscapes subject to large disturbance, Ecological Modelling, 56, 109-125 crossref(new window)

7.
Bonnicksen, T. M. and Stone, E. C. (1982). Reconstruction of a presettlement giant sequoia-mixed conifer forest community using the aggregation approach, Ecology, 63, 1134-1148 crossref(new window)

8.
Box, G. E. P. and Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control, Second Ed., Holden Day, San Francisco

9.
Brown, J. K., Marsden, M. A., Ryan, K. C. and Reinhardt, E. D. (1985). Predicting duff and woody fuel consumed by prescribed fire in the northern Rocky Mountains, USDA Forest Service Research Paper INT- 337, Intermountain Forest and Range Experiment Station, Ogden, Utah

10.
Burrows, D. A. (1988). The REFIRES Model: A C Program for Regional Fire Regime Simulation, Masters Thesis, UC Santa Barbara

11.
Chou, Y. H., Minnich, R. A., Salazar, L. A., Power, J. D. and Dezzani, R. J. (1990). Spatial autocorrelation of wildfire distribution in the Idyllwild Quadrangle, San Jacinto Mountain, California, Photogrammetric Engineering and Remote Sensing, 56, 1507-1513

12.
Clark, J. S. (1989). Ecological disturbance as a renewal process: Theory and application to fire history, Gikos, 56, 17-30

13.
Clark, J. S. (1990). Fire and climate change during the last 750 years in northwestern Minnesota, Ecological Monographs, 60, 135-159 crossref(new window)

14.
Fowler, P. M. and Asleson, D. O. (1984). The location of lightning-caused wildland fires in northern Idaho, Physical Geography, 5, 240-252

15.
Frandsen, W. H. and Andrews, P. L. (1979). Fire behavior in non-uniform fuels, USDA Forest Service Research Paper, INT-232, Intermountain Forest and Range Experiment Station, Ogden, Utah

16.
Green, D. G. (1983). Shapes of simulated fires in discrete fuels, Ecological Modelling, 20, 21-32 crossref(new window)

17.
Greig-Smith, P. (1964). Quantitative Plant Ecology, Butterworths, London

18.
Heinselman, M. L. (1973). Fire in the virgin forest of the Boundary Waters Canoe Area, Minnesota, Quaternary Research, 3, 329-382 crossref(new window)

19.
Johnson, E. A. and van Wagner, C. E. (1985). The theory and use of two fire history models, Canadian Journal of Forest Research, 15, 214-220 crossref(new window)

20.
Kilgore, B. M. (1971). The role of fire in managing .red fir forests, Transactions of the North American wildlife and Natural Resources Conference, 36, 405-416

21.
Kilgore, B. M. (1973). The ecological role of fire in Sierran conifer forests: Its application to national park management, Journal Quaternary Research, 3,496-513 crossref(new window)

22.
Ljung, G. M. and Box, G. E. P. (1978). On A measure of lack of fit in time series models, Biometrika, 65, 297-303 crossref(new window)

23.
Makridakis, S., Wheelwright, S. C. and Hyndman, R. J. (2003). FORECASTING: Methods and Applications Third Ed., Wiley, Chapter4, pp-136-180

24.
Martin, R. E. (1982). Fire history and its role in succession, Forest, Succession and Stand Development in the Northwest, 92-99

25.
McKelvey, K. S. and Busse, K. K. (1996). An evaluation of 20th century fire patterns on forest service lands in the Sierra Nevada, In Sierra Nevada Ecosystem Project: final report to Congress, vol. II, chap. 41. Davis: University of California, Centers for Water and Wildland Resources

26.
Meese, R. A. and Geweke, J. (1982). A Comparison of Autoregressive Univariate Forecasting Procedures for Macroeconomic Time Series, Unpublished Manuscript, University of California, Berkeley, California

27.
Minnich, R. A (1983). Fire mosaics in southern California and northern Baja California, Science, 219, 1287-1294 crossref(new window)

28.
Pankratz, A. (1983). Forecasting with univariate Box-Jenkins Models: Concepts and Cases, John Wiley & Sons, New York

29.
Pielou, E. C. (1977). Mathematical Ecology, John Wiley & Sons, New York

30.
Pindyck, R. S. and Rubinfeld, D. L. (1981). Econometric Models and Economic Forecasts, 2nd Ed., McGrawHill, New York

31.
Quenouille, M. H. (1949). Approximate tests of correlation in time-series, Journal of the Royal Statistical Society, B11, 68-84

32.
Romme, W. H. (1982). Fire and landscape diversity in subalpine forests of Yellowstone National Park, Ecological Monographs, 52, 199-221 crossref(new window)

33.
Rossi, R. E., Borth, P. W. and Tollefson, J. J. (1993). Stochastic simulation for characterizing ecological spatial patterns and appraising risk, Ecological Applications, 3, 719-735 crossref(new window)

34.
Rothermel, R. C. (1972). A mathematical model for predicting fire spread in wildland fuels, USDA Forest Service Research Paper, INT-115

35.
Rothermel, R. C., Wilson, R. A, Morris, G. A and Sackett, S. S. (1986). Modeling moisture content of fine dead wildland fuels: Input to the BEHAVE fire prediction system. USDA Forest Service Research Paper INT-359, Intermountain Forest and Range Experiment Station, Ogden, Utah

36.
Ryan, K. C. and Reinhardt, E. D. (1988). Predicting post-fire mortality of seven western conifers, Canadian Journal of Forest Research, 18, 1291-1297

37.
Swetnam, T. W. (1993). Fire history and climate change in giant sequoia groves, Science 262, 885-889 crossref(new window)

38.
van Wagtentonk, J. W. (1986). The role of fire in the Yosemite wilderness, Proceedings-National Wilderness Research Conference: Current Research, USDA Forest Service General Technical Report INT-212, Intermountain Research Station, Ogden, Utah, 2-9