Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia

Dyah R. Panuju, Bambang H. Trisasongko, Budi Susetyo, Mahmud A. Raimadoya, Brian G. Lees

Abstract


In addition to forest encroachment, forest fire is a serious problem in Indonesia. Attempts at managing its widespread and frequent occurrence has led to intensive use of remote sensing data. Coarse resolution images have been employed to derive hot spots as an indicator of forest fire. However, most efforts to verify the hot spot data and to verify fire accidents have been restricted to the use of medium or high resolution data. At present, it is difficult to verify solely upon those data due to severe cloud cover and low revisit time. In this paper, we present a method to validate forest fire using NDVI time series data. With the freely available NDVI data from SPOT VEGETATION, we successfully detected changes in time series data which were associated with fire accidents.

Full Text:

PDF

References


Mott, J.A., Mannino, D.M., Alverson, C.J., Kiyu, A., Hashim, J., Lee, T., Falter, K. & Redd, S.C., Cardiorespiratory Hospitalizations Associated with Smoke Exposure during the 1997 Southeast Asian Forest Fire, International Journal of Hygiene and Environmental Health, 208, 75-85, 2005.

Harden, J.W., Trumbore, S.E., Stocks, B.J., Hirsch, A., O’Neill, K.P. & Kasischke, E.S., The Role of Fire in the Boreal Carbon Budget, Global Change Biology, 6 (Supp 1), 174-184, 2000.

Keramitsoglou, I., Kiranoudis, C.T., Sarimveis, H., Sifakis, N., A Multidiscplinary Decision Support System for Forest Fire Crisis Management, Environmental Management, 33, 212-225, 2004.

Amiro, B.D., Orchansky, A.L., Barr, A.G., Black, T.A., Chambers, S.D., Chapin III, F.S., Goulden, M.L., Litvak, M., Liu, H.P., McCaughey, J.H., McMillan, A. & Randerson, J.T., The Effect of Post-Fire Stand Age on The Boreal Forest Energy Balance, Agricultural and Forest Meteorology, 140, 41-50, 2006.

Fuller, D.O. & Murphy, K. The ENSO-Fire Dynamic in Insular Southeast Asia, Climatic Change, 74, 435-455, 2006.

Liu, J., Chen, J.M. & Cihlar, J., Mapping Evapotranspiration Based on Remote Sensing: An Application to Canada’s Landmass, Water Resource Research, 39, doi:10.1029/2002WR001680, 2003.

Schwartz, M.D., Reed, B.C. & White, M.A., Assesing Satellite-Derived Start-of-Season Measures in The Conterminous USA, International Journal of Climate, 22, 1793-1805, 2002.

Julien, Y., Sobrino, J.A. & Verhoef, W., Changes in Land Surface Temperatures and NDVI Values Over Europe Between 1982 and 1999, Remote Sensing of Environment, 103, 43-55, 2006.

Ahl, D.E., Gower, S.T., Burrows, S.N., Shabanov, N.V., Myneni, R.B. & Knyazikhin, Y, Monitoring Spring Canopy Phenology of A Deciduous Broadleaf Forest Using MODIS, Remote Sensing of Environment, 104, 88-95, 2006.

Xiao, X., Hagen, S., Zhang, Q., Keller, M., Moore III, B., Detecting Phenology of Seasonally Moist Tropical Forests in South America with Multi-Temporal MODIS Images, Remote Sensing of Environment, 103, 465-473, 2006.

Chuvieco, E., Ventura, G., Martin, M.P. & Gomez, I., Assessment of Multitemporal Compositing Techniques of MODIS and AVHRR Images for Burned Land Mapping, Remote Sensing of Environment, 94, 450-462, 2005.

Holben, B.N., Characteristics of Maximum-Value Composite Images from Temporal AVHRR Data, International Journal of Remote Sensing, 7, 1417-1434, 1986.

Goetz, S.J., Fiske, G.J. & Bunn, A.G., Using Satellite Time-Series Data Sets to Analyze Fire Disturbance and Forest Recovery Across Canada, Remote Sensing of Environment, 101, 352-365, 2006.

Viovy, N., Automatic Classification of Time Series (ACTS): A New Clustering Method for Remote Sensing Time Series, International Journal of Remote Sensing, 21, 1537-1560, 2000.

Moleele, N., Ringrose, S., Arnberg, W., Lunden, B. & Vanderpost, C., Assessment of Vegetation Indexes Useful for Browse (Forage) Prediction In Semi-Arid Rangelands, International Journal of Remote Sensing, 22, 741-756, 2001.

Bradley, B.A., Jacob, R.W., Hermance, J.F. & Mustard, J.F., A Curve Fitting Procedure to Derive Inter-Annual Phenologies from Time Series of Noisy Satellite NDVI Data, Remote Sensing of Environment, 106, 137-145, 2007.

Busetto, L., Meroni, M. & Colombo, R., Combining Medium and Coarse Spatial Resolution Satellite Data to Improve The Estimation of Sub-Pixel NDVI Time Series, Remote Sensing of Environment, 112, 118-131, 2008.

Wei, W.W.S., Time Series Analysis: Univariate and Multivariate Methods, Pearson/Addison-Wesley, Boston, 2006.

Box, G.E.P. & Jenkins, G.M., Time Series Analysis: Forecasting and Control, Holden-Day, San Francisco, 1976.

Dagum, E.B., The X-11-ARIMA Seasonal Adjustment Method, Statistics Canada, 1980.

Findley, D.F., Monsell, B.C., Bell, W.R., Otto, M.C. & Chen, B-C., New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program, Journal of Business and Economic Statistics, 16, 127-152, 1998.

Pezzulli, S., Stephenson, B. & Hannachi, A., The Variability of Seasonality, Journal of Climate, 18, 71-88, 2005.

Adya, M., Collopy, F., Armstrong, J.S. & Kennedy, M., Automatic Identification of Time Series Features for Rule-Based Forecasting, International Journal of Forecasting, 17, 143-157, 2001.

Fox, A.J., Outliers in Time Series, Journal of Royal Statistical Society Series B, 34, 350-363, 1972.

Chang, I., Tiao, G.C. & Chen, C., Estimation of Time Series Parameters in The Presence of Outliers, Technometrics, 30, 193-204, 1988.

Tsay, R.S., Outliers, Level Shifts and Variance Changes in Time Series, Journal of Forecasting, 7, 1-20, 1988.

Chen, C. & Liu, L.M., Joint Estimation of Model Parameters and Outlier Effects in Time Series, Journal of American Statistical Association, 88, 284-297, 1993a.

Kaiser, R. & Maravall, A., Seasonal Outliers in Time Series, Banco de Espana, Madrid, Spain, 2001.

Chen, C. & Liu, L.M., Forecasting Time Series with Outliers, Journal of Forecasting, 12, 13-35, 1993b.

Lorenzo, E.P. & Munoz, C.P., Land Clearing without Fire: A Model for Preparing Timber Plantation Development in Indonesia, in Proceeding of Workshop on Peatland fire in Sumatera: problems and solutions, Palembang, 10-11 December 2003.

Stolle, F., Chomitz, K.M., Lambin, E.F. & Tomich, T.P., Land Use and Vegetation Fires in Jambi Province, Sumatera, Indonesia, Forest Ecology and Management, 179, 277-292, 2003.

Koutsias, N., Karteris, M. & Chuvieco, E., The Use of Intensity-Hue-Saturation Transformation of Landsat-5 Thematic Mapper Data for Burned Land Mapping, Photogrammetric Engineering and Remote Sensing, 66, 829-839, 2000.

Jia, G.J., Epstein, H.E. & Walker, D.A., Spatial Characteristics of AVHRR-NDVI along Latitudinal Transects in Northern Alaska, Journal of Vegetation Science, 13, 315-326, 2002.

Gomez, V. & Maravall, A., Program TRAMO and SEATS: Instructions for the User, Beta Version, Banco de Espana, Madrid, Spain, 1997.

Herrmann, S.M., Anyamba, A. & Tucker, C.J., Recent Trends in Vegetation Dynamics in The African Sahel and Their Relationship to Climate, Global Environmental Change, 15, 394-404, 2005.




DOI: http://dx.doi.org/10.5614%2Fitbj.sci.2010.42.1.5

Refbacks

  • There are currently no refbacks.


View my Stats

Creative Commons License
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

 

ITB Journal Publisher, LPPM ITB, Center for Research and Community Services (CRCS) Building, 6th & 7th Floor, Jalan Ganesha 10, Bandung 40132, Indonesia, Phone: +62-22-86010080, Fax.: +62-22-86010051; E-mail: jmfs@lppm.itb.ac.id