Assessing postfire recovery of chamise chaparral using multi-temporal spectral vegetation index trajectories derived from Landsat imagery

Remote Sensing of Environment

Volumn 183, Issue , 2016, Pages 53-64

  Storey, Emanuel A ^a   Stow, Douglas A ^a   O'Leary, John F ^a  

^a SAN DIEGO STATE UNIVERSITY   (United States)

Author keywords

Chamise chaparral; Fire ecology; Growth form classification; Land management; Landsat time series; Postfire recovery metrics; Postfire resilience; Remote sensing; Type conversion

Indexed keywords

ECOLOGY; FORESTRY; PLANTS (BOTANY); REMOTE SENSING; SATELLITE IMAGERY; TIME SERIES; TRAJECTORIES; VEGETATION;

CHAMISE CHAPARRAL; FIRE ECOLOGY; GROWTH FORM; LAND MANAGEMENTS; LANDSAT TIME SERIES; POST-FIRE; POSTFIRE RECOVERY;

RECOVERY;

CHAPARRAL; LANDSAT; LONG-TERM CHANGE; MEDITERRANEAN ENVIRONMENT; NDVI; REGROWTH; REMOTE SENSING; SATELLITE IMAGERY; SHRUBLAND; SPATIAL RESOLUTION; SURFACE REFLECTANCE; TIME SERIES ANALYSIS; VEGETATION INDEX;

ADENOSTOMA FASCICULATUM;

EID: 84974628498     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2016.05.018     Document Type: Article

References (53)

1. Baret F., Guyot G. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sensing of Environment 1991, 35(2):161-173.
2. Carreiras J., Pereira J., Pereira J. Estimation of tree canopy cover in evergreen oak woodlands using remote sensing. Forest Ecology and Management 2006, 223(1):45-53.
3. Chen X., Vogelmann J., Rollins M., Ohlen D., Key C. Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest. International Journal of Remote Sensing 2011, 32(23):7905-7927.
4. Chuvieco E. Measuring changes in landscape pattern from satellite images: short-term effects of fire on spatial diversity. International Journal of Remote Sensing 1999, 20(12):2331-2346.
5. Chuvieco E. and Kasischke E.S., Remote sensing information for fire management and fire effects assessment.
6. Clemente R., Navarro-Cerrillo R., Gitas I. Monitoring post-fire regeneration in Mediterranean ecosystems by employing multitemporal satellite imagery. International Journal of Wildland Fire 2009, 18(6):648-658.
7. Diaz-Delgado R., Salvador R., Pons X. Monitoring of plant regeneration after fire by remote sensing. Fire management and landscape ecology 1998, 315-326.
8. Diaz-Delgado R., Lloret F., Pons X., Terradas J. Satellite evidence of decreasing resilience in Mediterranean plant communities after recurrent wildfires. Ecology 2002, 83(8):2293-2303.
9. Finney M.A., Ryan K.C. Use of the FARSITE fire growth model for fire prediction in US National Parks. In international emergency management and engineering conference. Paris, France: International Emergency Management and Engineering Society 1995, May. J.D. Sullivan, J.L. Wybo, L. Buisson (Eds.).
10. Fraser R., Olthof I., Carrière M., Deschamps A., Pouliot D. Detecting long-term changes to vegetation in northern Canada using the Landsat satellite image archive. Environmental Research Letters 2011, 6(4):045502.
11. Gitas I., Mitri G., Veraverbeke S., Polychronaki A. Advances in remote sensing of post-fire vegetation recovery monitoring-a review 2012, INTECH, (Open Access Publisher).
12. Haidinger T., Keeley J. Role of high fire frequency in destruction of mixed chaparral. Madroño 1993, 40:141-147.
13. Hansen M., Stehman S., Potapov P. Quantification of global gross forest cover loss. Proceedings of the National Academy of Sciences 2010, 107(19):8650-8655.
14. Hardisky M., Klemas V., Smart R. The influences of soil salinity, growth form, and leaf moisture on the spectral reflectance of Spartina alterniflora canopies. Photogrammetric Engineering and Remote Sensing 1983, 49:77-83.
15. Henry M., Hope A. Monitoring post-burn recovery of chaparral vegetation in southern California using SPOT XS data. International Journal of Remote Sensing 1998, 19(16):3097-3107.
16. Henry M.C., Yool S.R. Characterizing fire-related spatial patterns in the Arizona Sky Islands using Landsat TM data. Photogrammetric Engineering and Remote Sensing 2002, 68(10):1011-1020.
17. Holland R.F. Preliminary descriptions of the terrestrial natural communities of California 1986.
18. Hope A., Tague C., Clark R. Characterizing post-fire vegetation recovery of California chaparral using TM/ETM+ time series data. International Journal of Remote Sensing 2007, 28(6):1339-1354.
19. Horton J., Kraebel C. Development of vegetation after fire in the chamise chaparral of southern California. Ecology 1955, 36(2):244-262.
20. Huete A. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment 1988, 25:295-309.
21. Huete A., Justice C., van Leeuwen W. MODIS vegetation index (MOD13) algorithm theoretical basis document (NASA Goddard space flight center) (Retrieved from). http://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf.
22. Idris M., Kuraji K., Suzuki M. Evaluating vegetation recovery following large scale forest fires in Borneo and northeastern China using multi-temporal NOAA/AVHRR images. Journal of Forest Research 2005, 10(2):101-111.
23. Keeley J. Chaparral. North American terrestrial vegetation 2000, 204-253. Cambridge University Press, Cambridge, UK. M. Barbour, W. Billings (Eds.).
24. Keeley J., Brennan T. Fire-driven alien invasion in a fire-adapted ecosystem. Oecologia 2012, 169(4):1043-1052.
25. Keeley J., Keeley S. Post-fire regeneration of southern California chaparral. American Journal of Botany 1981, 68:524-530.
26. Keeley J., Safford H., Fotheringham C., Franklin J., Moritz M. The 2007 southern California wildfires: Lessons in complexity. Journal of Forestry 2009, 107(6):287-296.
27. Key C.H., Benson N.C. Measuring and remote sensing of burn severity: The CBI and NBR. Poster abstract. Proceedings joint fire science conference and workshop 1999, II. University of Idaho and International Association of Wildland Fire, Boise, ID. L. Neuenschwander, K. Ryan (Eds.).
28. Key C.H., Benson N.C. Landscape assessment (LA). FIREMON: Fire effects monitoring and inventory system. Gen. Tech. Rep. RMRS-GTR-164-CD, Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station 2006.
29. Li M., Qu J., Hao X. Detecting vegetation change with satellite remote sensing over 2007 Georgia wildfire regions. Journal of Applied Remote Sensing 2008, 2(1):021505.
30. Lippitt C., Stow D., O'Leary J., Franklin J. Influence of short-interval fire occurrence on post-fire recovery of fire-prone shrublands in California, USA. International Journal of Wildland Fire 2013, 22(2):184-193.
31. Lloret F., Calvo E., Pons X., Díaz-Delgado R. Wildfires and landscape patterns in the eastern Iberian peninsula. Landscape Ecology 2002, 17(8):745-759.
32. Masek J., Huang C., Wolfe R., Cohen W., Hall F., Kutler J., Nelson P. North American forest disturbance mapped from a decadal Landsat record. Remote Sensing of Environment 2008, 112(6):2914-2926.
33. Masek J., Goward S., Kennedy R., Cohen W., Moisen G., Schleeweis K., Huang C. United States Forest disturbance trends observed using Landsat time series. Ecosystems 2013, 16(6):1087-1104. 10.1007/s10021-013-9669-9.
34. McMichael C., Hope A., Roberts D., Anaya M. Post-fire recovery of leaf area index in California chaparral: A remote sensing-chronosequence approach. International Journal of Remote Sensing 2004, 25(21):4743-4760.
35. Miller J.D., Thode A.E. Quantifying burn severity in a heterogeneous landscape with a relative version of the delta normalized burn ratio (dNBR). Remote Sensing of Environment 2007, 109(1):66-80.
36. Narasimhan R., Stow D. Daily MODIS products for analyzing early season vegetation dynamics across the north slope of Alaska. Remote Sensing of Environment 2010, 114(6):1251-1262.
37. Peterson S., Stow D. Using multiple image endmember spectral mixture analysis to study chaparral regrowth in southern California. International Journal of Remote Sensing 2003, 24(22):4481-4504.
38. Qi J., Kerr Y., Chehbouni A. External factor consideration in vegetation index development. Proceedings of physical measurements and signatures in remote sensing, ISPRS 1994, France, val d'isere.
39. Quayle B., Brewer K., Williams K. Monitoring post-fire vegetation recovery of wildland fire areas in the western United States using MODIS data. Proceedings of Pecora 16: Global Priorities in Land Remote Sensing 2005, American Society for Photogrammetry and Remote Sensing, Sioux Falls, South Dakota, USA, October 23-27.
40. Riaño D., Chuvieco E., Ustin S., Zomer R., Dennison P., Roberts D., Salas J. Assessment of vegetation regeneration after fire through multitemporal analysis of AVIRIS images in the Santa Monica Mountains. Remote Sensing of Environment 2002, 79(1):60-71.
41. Roder A., Hill J., Duguy B., Alloza J., Vallejo R. 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 2008, 112(1):259-273.
42. Rouse J., Haas R.H., Schell J.A., Deering D.W. Monitoring vegetation systems in the Great Plains with ERTS 1974, 351:309-317. NASA special publication.
43. Skole D., Tucker C. Tropical deforestation and habitat fragmentation in the Amazon: Satellite data from 1978 to 1988. Science 1993, 260(5116):1905-1910.
44. Storey J., Scaramuzza G., Schmidt J. Landsat-7 scan line corrector-off gap filled product development. Proceedings of Pecora 16: global priorities in land remote sensing 2005, American Society for Photogrammetry and Remote Sensing, Sioux Falls, South Dakota, USA, October 23-27.
45. Tucker C., Townshend J. Strategies for monitoring tropical deforestation using satellite data. International Journal of Remote Sensing 2000, 21(6-7):1461-1471.
46. van Leeuwen W., Casady G., Neary D., Bautista S., Alloza J., Carmel Y., Orr B. Monitoring post-wildfire vegetation response with remotely sensed time series data in Spain, USA and Israel. International Journal of Wildland Fire 2010, 19(1):75-93.
47. Viedma O., Melia J., Segarra D., García-Haro J. Modeling rates of ecosystem recovery after fires by using Landsat TM data. Remote Sensing of Environment 1997, 61(3):383-398.
48. Viedma O., Moreno J.M., Rieiro I. Interactions between land use/land cover change, forest fires and landscape structure in sierra de Gredos (Central Spain). Environmental Conservation 2006, 33(3):212-222.
49. Vila G., Barbosa P. Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data. Ecological Modelling 2010, 221(1):75-84.
50. Wing M., Burnett J., Sessions J. Remote sensing and unmanned aerial system technology for monitoring and quantifying forest fire impacts. International Journal of Remote Sensing Applications 2014, 4(1):18-35.
51. Wulder M., White J., Cranny M., Hall R., Luther J., Beaudoin A., Dechka J. Monitoring Canada's forests. Part 1: Completion of the EOSD land cover project. Canadian Journal of Remote Sensing 2008, 34(6):549-562.
52. Zedler P., Gautier C., McMaster G. Vegetation change in response to extreme events: The effect of a short interval between fires in California chaparral and coastal scrub. Ecology 1983, 64(4):809-818.
53. Zhu Z., Woodcock C. Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment 2012, 118(15):83-94.