Trend analysis of medium- and coarse-resolution time series image data for burned area mapping in a Mediterranean ecosystem
Thomas Katagis A D , Ioannis Z. Gitas A , Pericles Toukiloglou A , Sander Veraverbeke B and Rudi Goossens C
+ Author Affiliations
- Author Affiliations
A Laboratory of Forest Management and Remote Sensing, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, PO Box 248, Greece.
B University of California, 2224 Croul Hall, Irvine, CA 92697, USA.
C Department of Geography, Ghent University, Krijgslaan 281 S8, BE-9000 Ghent, Belgium.
D Corresponding author. Email: thkatag@for.auth.gr
International Journal of Wildland Fire 23(5) 668-677 https://doi.org/10.1071/WF12055
Submitted: 1 April 2012 Accepted: 2 January 2014 Published: 7 March 2014
Abstract
In this study, the Breaks for Additive Seasonal and Trend (BFAST), a recently introduced trend analysis technique, was employed for the detection of fire-induced changes in a Mediterranean ecosystem. BFAST enables the decomposition of time series into trend, seasonal and noise components, resulting in the detection of gradual and rapid land cover changes. Normalised Difference Vegetation Index (NDVI) time series derived from the MODIS and VEGETATION (VGT) standard products were analysed. The time series decomposition resulted in the mapping of the burned area and the demonstration of the post-fire vegetation recovery trend. The observed gradual changes revealed an increase of NDVI values over time, indicating post-fire vegetation recovery. Spatial validation of the generated burned area maps with a higher resolution reference map was performed and probability statistics were derived. Both maps achieved a high probability of detection – 0.90 for MODIS and 0.87 for VGT – and a low probability of false alarms, 0.01 for MODIS and 0.02 for VGT. In addition, the Pareto boundary theory was implemented to account for the low-resolution bias of the maps. BFAST facilitated detection of fire-induced changes using image time series, without having to set thresholds, select specific seasons or adjust to certain land cover types. Further evaluation of the approach should focus on a more comprehensive assessment across regions and time.
Additional keywords: change detection, linear models, Normalised Difference Vegetation Index, time-series decomposition.
References
Abdel Malak D, Pausas J (2006) Fire regime and post-fire Normalized Difference Vegetation Index changes in the eastern Iberian peninsula. International Journal of Wildland Fire 15, 407–413.| Fire regime and post-fire Normalized Difference Vegetation Index changes in the eastern Iberian peninsula.Crossref | GoogleScholarGoogle Scholar |
Al-Rawi KR, Casanova JL, Calle A (2001) Burned area mapping system and fire detection system, based on neural networks and NOAA-AVHRR imagery. International Journal of Remote Sensing 22, 2015–2032.
Bai J (1994) Least squares estimation of a shift in linear processes. Journal of Time Series Analysis 15, 453–472.
| Least squares estimation of a shift in linear processes.Crossref | GoogleScholarGoogle Scholar |
Bai J, Perron P (1998) Estimating and testing linear models with multiple structural changes. Econometrica 66, 47–78.
| Estimating and testing linear models with multiple structural changes.Crossref | GoogleScholarGoogle Scholar |
Bai J, Perron P (2003) Computation and analysis of multiple structural change models. Journal of Applied Econometrics 18, 1–22.
| Computation and analysis of multiple structural change models.Crossref | GoogleScholarGoogle Scholar |
Bartalev S, Egorov V, Loupian E, Uvarov I (2007) Multi-year circumpolar assessment of the area burnt in boreal ecosystems using SPOT-VEGETATION. International Journal of Remote Sensing 28, 1397–1404.
| Multi-year circumpolar assessment of the area burnt in boreal ecosystems using SPOT-VEGETATION.Crossref | GoogleScholarGoogle Scholar |
Boschetti L, Flasse SP, Brivio PA (2004) Analysis of the conflict between omission and commission in low spatial resolution dichotomic thematic products: the Pareto boundary. Remote Sensing of Environment 91, 280–292.
| Analysis of the conflict between omission and commission in low spatial resolution dichotomic thematic products: the Pareto boundary.Crossref | GoogleScholarGoogle Scholar |
Boschetti M, Stroppiana D, Brivio PA (2010) Mapping burned areas in a Mediterranean environment using soft integration of spectral indices from high-resolution satellite images. Earth Interactions 14, 1–20.
| Mapping burned areas in a Mediterranean environment using soft integration of spectral indices from high-resolution satellite images.Crossref | GoogleScholarGoogle Scholar |
Carlson T, Ripley T (1997) On the relation between NDVI, fractional vegetation cover and leaf area index. Remote Sensing of Environment 62, 241–252.
| On the relation between NDVI, fractional vegetation cover and leaf area index.Crossref | GoogleScholarGoogle Scholar |
Casady G, van Leeuwen W, Marsh S (2010) Evaluating post-wildfire vegetation regeneration as a response to multiple environmental determinants. Environmental Modeling and Assessment 15, 295–307.
| Evaluating post-wildfire vegetation regeneration as a response to multiple environmental determinants.Crossref | GoogleScholarGoogle Scholar |
Chuvieco E (1997) Foreword. In ‘A Review of Remote Sensing Methods for the Study of Large Wildland Fires.’ (Ed. E Chuvieco) pp. 3–5. (Departamento de Geografía, Universidad de Alcalá, Alcalá de Henares)
Chuvieco E, Martin MP, Palacios A (2002) Assessment of different spectral indices in the red–near-infrared spectral domain for burned land discrimination. Remote Sensing of Environment 23, 5103–5110.
| Assessment of different spectral indices in the red–near-infrared spectral domain for burned land discrimination.Crossref | GoogleScholarGoogle Scholar |
Chuvieco E, Ventura G, Martín MP, Gómez I (2005) Assessment of multitemporal compositing techniques of MODIS and AVHRR images for burned land mapping. Remote Sensing of Environment 94, 450–462.
| Assessment of multitemporal compositing techniques of MODIS and AVHRR images for burned land mapping.Crossref | GoogleScholarGoogle Scholar |
Chuvieco E, Englefield P, Trishchenko AP, Luo Y (2008) Generation of long time series of burn area maps of the boreal forest from NOAA-AVHRR composite data. Remote Sensing of Environment 112, 2381–2396.
| Generation of long time series of burn area maps of the boreal forest from NOAA-AVHRR composite data.Crossref | GoogleScholarGoogle Scholar |
Cleveland RB, Cleveland WS, Mcrae JE, Terpenning I (1990) STL: a seasonal-trend decomposition procedure based on loess. Journal of Official Statistics 6, 3–73.
Congalton R (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment 37, 35–46.
| A review of assessing the accuracy of classifications of remotely sensed data.Crossref | GoogleScholarGoogle Scholar |
Coppin P, Jonckheere I, Nackaerts K, Muys B, Lambin E (2004) Digital change-detection methods in ecosystem monitoring: a review. International Journal of Remote Sensing 25, 1565–1596.
| Digital change-detection methods in ecosystem monitoring: a review.Crossref | GoogleScholarGoogle Scholar |
de Beurs KM, Henebry GM (2005) A statistical framework for the analysis of long image time series. International Journal of Remote Sensing 26, 1551–1573.
| A statistical framework for the analysis of long image time series.Crossref | GoogleScholarGoogle Scholar |
Duchemin B, Maisongrande P, Dedieu G, Leroy M (2000) A 10-days compositing method accounting for bidirectional effects. Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International 5, 2155–2157.
| A 10-days compositing method accounting for bidirectional effects.Crossref | GoogleScholarGoogle Scholar |
European Commission (2005) Forest Fires in Europe 2004. Office for Official Publications of the European Communities, S.P.I.05.147. (Luxembourg)
Fernandez A, Illera P, Casanova JL (1997) Automatic mapping of surfaces affected by forest fires in Spain using AVHRR NDVI composite image data. Remote Sensing of Environment 60, 153–162.
| Automatic mapping of surfaces affected by forest fires in Spain using AVHRR NDVI composite image data.Crossref | GoogleScholarGoogle Scholar |
Flannigan M, Stocks B, Wotton B (2000) Climate change and forest fires. The Science of the Total Environment 262, 221–229.
| Climate change and forest fires.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3cXotleru78%3D&md5=d5c8854d998e7e1693117465482ef697CAS | 11087028PubMed |
Fuller DO (1998) Trends in NDVI time series and their relation to rangeland and crop production in Senegal, 1987–1993. International Journal of Remote Sensing 19, 2013–2018.
| Trends in NDVI time series and their relation to rangeland and crop production in Senegal, 1987–1993.Crossref | GoogleScholarGoogle Scholar |
Giglio L, Csiszar I, Restás A, Morisette JT, Schroeder W, Morton D, Justice CO (2008) Active fire detection and characterization with the advanced spaceborne thermal emission and reflection radiometer (ASTER). Remote Sensing of Environment 112, 3055–3063.
| Active fire detection and characterization with the advanced spaceborne thermal emission and reflection radiometer (ASTER).Crossref | GoogleScholarGoogle Scholar |
Gitas IZ, Mitri HG, Ventura G (2004) Object-oriented image classification for burned area mapping of Creus Cape, Spain, using NOAA-AVHRR imagery. Remote Sensing of Environment 92, 409–413.
| Object-oriented image classification for burned area mapping of Creus Cape, Spain, using NOAA-AVHRR imagery.Crossref | GoogleScholarGoogle Scholar |
Gitas IZ, Polychronaki A, Katagis T, Mallinis G (2008) Contribution of remote sensing to disaster management activities: a case study of the large fires in the Peloponnese, Greece. International Journal of Remote Sensing 29, 1847–1853.
| Contribution of remote sensing to disaster management activities: a case study of the large fires in the Peloponnese, Greece.Crossref | GoogleScholarGoogle Scholar |
Goetz S, Fiske G, Bunn A (2006) Using satellite time-series data sets to analyze fire disturbance and forest recovery across Canada. Remote Sensing of Environment 92, 411–423.
Haywood J, Randal J (2008) Trending seasonal data with multiple structural breaks. NZ visitor arrivals and the minimal effects of 9/11. Victoria University of Wellington, Research report 08/10. (Wellington, New Zealand) Available at http://msor.victoria.ac.nz/twiki/pub/Main/ResearchReportSeries/mscs08–10.pdf [Verified 20 January 2014]
Jakubauskas ME, Legates DR, Kastens JH (2001) Harmonic analysis of time-series AVHRR NDVI data. Photogrammetric Engineering and Remote Sensing 67, 461–470.
Jönsson P, Eklundh L (2004) TIMESAT – a program for analyzing time-series of satellite sensor data. Computers & Geosciences 30, 833–845.
| TIMESAT – a program for analyzing time-series of satellite sensor data.Crossref | GoogleScholarGoogle Scholar |
Justice CO, Giglio L, Korontzi S, Owens J, Morisette JT, Roy D, Descloitres J, Alleaume S, Petitcolin F, Kaufman Y (2002) The MODIS fire products. Remote Sensing of Environment 83, 244–262.
| The MODIS fire products.Crossref | GoogleScholarGoogle Scholar |
Lambin EF, Strahler AH (1994) Change-vector analysis in multitemporal space – a tool to detect and categorize land-cover change processes using high temporal resolution satellite data. Remote Sensing of Environment 48, 231–244.
| Change-vector analysis in multitemporal space – a tool to detect and categorize land-cover change processes using high temporal resolution satellite data.Crossref | GoogleScholarGoogle Scholar |
Le Houerou HN (1987) Vegetation wildfires in the Mediterranean basin: evolution and trends. Ecologia Mediterranea 13, 12–15.
Lentile L, Holden Z, Smith A, Falkowski M, Hudak A, Morgan P, Lewis S, Gessler P, Benson N (2006) Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire 15, 319–345.
| Remote sensing techniques to assess active fire characteristics and post-fire effects.Crossref | GoogleScholarGoogle Scholar |
Loboda T, O'Neal K, Csiszar I (2007) Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data. Remote Sensing of Environment 109, 429–442.
| Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data.Crossref | GoogleScholarGoogle Scholar |
Lu D, Mausel P, Brondizio E, Moran E (2004) Change detection techniques. International Journal of Remote Sensing 25, 2365–2401.
| Change detection techniques.Crossref | GoogleScholarGoogle Scholar |
Maingi J, Henry M (2007) Factors influencing wildfire occurrence and distribution in eastern Kentucky, USA. International Journal of Wildland Fire 16, 23–33.
| Factors influencing wildfire occurrence and distribution in eastern Kentucky, USA.Crossref | GoogleScholarGoogle Scholar |
Milne A (1986) The use of remote sensing in mapping and monitoring vegetational change associated with bushfire events in eastern Australia. Geocarto International 1, 25–32.
| The use of remote sensing in mapping and monitoring vegetational change associated with bushfire events in eastern Australia.Crossref | GoogleScholarGoogle Scholar |
Mitri G, Gitas IZ (2010) Mapping post-fire vegetation recovery using EO-1 Hyperion Imagery. IEEE Transactions on Geoscience and Remote Sensing 48, 1613–1618.
| Mapping post-fire vegetation recovery using EO-1 Hyperion Imagery.Crossref | GoogleScholarGoogle Scholar |
Moody A, Johnson DM (2001) Land-surface phenologies from AVHRR using the discrete Fourier transform. Remote Sensing of Environment 75, 305–323.
| Land-surface phenologies from AVHRR using the discrete Fourier transform.Crossref | GoogleScholarGoogle Scholar |
Pausas J (2004) Changes in fire and climate in the eastern Iberian peninsula (Mediterranean Basin). Climatic Change 63, 337–350.
| Changes in fire and climate in the eastern Iberian peninsula (Mediterranean Basin).Crossref | GoogleScholarGoogle Scholar |
Pereira JMC, Mota B, Privette JL, Caylor KK, Silva JMN, Sa ACL, Ni-Meister W (2004) A simulation analysis of the detectability of understory burns in Miombo woodlands. Remote Sensing of Environment 93, 296–310.
| A simulation analysis of the detectability of understory burns in Miombo woodlands.Crossref | GoogleScholarGoogle Scholar |
Pérez-Cabello F, de la Riva Fernández J, Montorio Llovería R, García-Martín A (2006) Mapping erosion-sensitive areas after wildfires using fieldwork, remote sensing, and geographic information systems techniques on a regional scale. Journal of Geophysical Research 111, G04S10
| Mapping erosion-sensitive areas after wildfires using fieldwork, remote sensing, and geographic information systems techniques on a regional scale.Crossref | GoogleScholarGoogle Scholar |
Polychronaki A, Gitas IZ (2010) The development of an operational procedure for burned-area mapping using object-based classification and ASTER imagery. International Journal of Remote Sensing 31, 1113–1120.
| The development of an operational procedure for burned-area mapping using object-based classification and ASTER imagery.Crossref | GoogleScholarGoogle Scholar |
Roder A, Hill J, Duguy B, Alloza J, Vallejo R (2008) Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region (eastern Spain). Remote Sensing of Environment 112, 259–273.
| Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region (eastern Spain).Crossref | GoogleScholarGoogle Scholar |
Roy DP, Jin Y, Lewis PE, Justice CO (2005) Prototyping a global algorithm for systematic fire affected area mapping using MODIS time series data. Remote Sensing of Environment 97, 137–162.
| Prototyping a global algorithm for systematic fire affected area mapping using MODIS time series data.Crossref | GoogleScholarGoogle Scholar |
Savitzky A, Golay M (1964) Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry 36, 1627–1639.
| Smoothing and differentiation of data by simplified least squares procedures.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaF2cXksVCjur8%3D&md5=3c662daeaaf9c28384dfcd8723b3e4fbCAS |
Stroppiana D, Pinnock S, Pereira JMC, Grégoire JM (2002) Radiometric analysis of SPOTVEGETATION images for burnt area detection in Northern Australia. Remote Sensing of Environment 82, 21–37.
| Radiometric analysis of SPOTVEGETATION images for burnt area detection in Northern Australia.Crossref | GoogleScholarGoogle Scholar |
Tansey K, Grégoire J-M, Binaghi E, Boschetti L, Brivio PA, Ershov D, Flasse S, Fraser R, Graetz D, Maggi M, Peduzzi P, Pereira JMC, Silva J, Sousa A, Stroppiana D (2004) A global inventory of burned areas at 1-km resolution for the year 2000 derived from Spot vegetation data Climatic Change 67, 345–377.
| A global inventory of burned areas at 1-km resolution for the year 2000 derived from Spot vegetation dataCrossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXitlKhs7Y%3D&md5=6208bb40b8fee45ad08d58e935537640CAS |
Tucker CJ (1979) Red and photographic infrared linear combinations monitoring vegetation. Remote Sensing of Environment 8, 127–150.
| Red and photographic infrared linear combinations monitoring vegetation.Crossref | GoogleScholarGoogle Scholar |
van der Werf GR, Randerson JT, Giglio L, Collatz GJ, Kasibhatla PS, Arellano AF (2006) Interannual variability in global biomass burning emissions from 1997 to 2004. Atmospheric Chemistry and Physics 6, 3423–3441.
| Interannual variability in global biomass burning emissions from 1997 to 2004.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XhtV2hs7nI&md5=50303de2a8e1c3a6a5fa4635fb03241fCAS |
Venables WN, Ripley BD (2002) ‘Modern Applied Statistics with S’, 4th edn. (Springer: New York)
Veraverbeke S, Lhermitte S, Verstraeten WW, Goossens R (2010) The temporal dimension of differenced Normalized Burn Ratio (dNBR) fire/burn severity studies: the case of the large 2007 Peloponnese wildfires in Greece. Remote Sensing of Environment 114, 2548–2563.
| The temporal dimension of differenced Normalized Burn Ratio (dNBR) fire/burn severity studies: the case of the large 2007 Peloponnese wildfires in Greece.Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Lhermitte S, Verstraeten WW, Goossens R (2011) A time-integrated MODIS burn severity assessment using the multi-temporal differenced normalized burn ratio (dNBRMT). International Journal of Applied Earth Observation and Geoinformation 13, 52–58.
| A time-integrated MODIS burn severity assessment using the multi-temporal differenced normalized burn ratio (dNBRMT).Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Gitas I, Katagis T, Polychronaki A, Somers B, Goossens R (2012) Assessing post-fire vegetation recovery using red–near infrared vegetation indices: accounting for background and vegetation variability. ISPRS Journal of Photogrammetry and Remote Sensing 68, 28–39.
| Assessing post-fire vegetation recovery using red–near infrared vegetation indices: accounting for background and vegetation variability.Crossref | GoogleScholarGoogle Scholar |
Verbesselt J, Hyndman R, Newnham G, Culvenor D (2010a) Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment 114, 106–115.
| Detecting trend and seasonal changes in satellite image time series.Crossref | GoogleScholarGoogle Scholar |
Verbesselt J, Hyndman R, Zeileis A, Culvenor D (2010b) Phenological change detection while accounting for abrupt and gradual trends in satellite image time series. Remote Sensing of Environment 114, 2970–2980.
| Phenological change detection while accounting for abrupt and gradual trends in satellite image time series.Crossref | GoogleScholarGoogle Scholar |
Vilà M, Lloret F, Ogheri E, Terradas J (2001) Positive fire–grass feedback in Mediterranean basin shrub land. Forest Ecology and Management 147, 3–14.
| Positive fire–grass feedback in Mediterranean basin shrub land.Crossref | GoogleScholarGoogle Scholar |
Young SS, Wang CY (2001) Land-cover change analysis of China using global-scale Pathfinder AVHRR Landcover (PAL) data, 1982–92. International Journal of Remote Sensing 22, 1457–1477.
Zeileis A (2005) A unified approach to structural change tests based on ML scores, F statistics, and OLS residuals. Econometric Reviews 24, 445–466.
| A unified approach to structural change tests based on ML scores, F statistics, and OLS residuals.Crossref | GoogleScholarGoogle Scholar |
Zeileis A, Kleiber C, Krämer W, Hornik K (2003) Testing and dating of structural changes in practice. Computational Statistics & Data Analysis 44, 109–123.
| Testing and dating of structural changes in practice.Crossref | GoogleScholarGoogle Scholar |
