Contextualizing the 2019-2020 Kangaroo Island Bushfires: Quantifying Landscape-Level Influences on Past Severity and Recovery with Landsat and Google Earth Engine
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[1] Kevin G. Tolhurst,et al. Effect of prescribed burning on wildfire severity: a landscape-scale case study from the 2003 fires in Victoria , 2016 .
[2] Neil Flood,et al. Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median) , 2013, Remote. Sens..
[3] Chengquan Huang,et al. Effects of fire severity and post-fire climate on short-term vegetation recovery of mixed-conifer and red fir forests in the Sierra Nevada Mountains of California , 2015 .
[4] Mark A. Adams,et al. Mega-fires, inquiries and politics in the eucalypt forests of Victoria, south-eastern Australia , 2013 .
[5] Matthias M. Boer,et al. Long-term impacts of prescribed burning on regional extent and incidence of wildfires : evidence from 50 years of active fire management in SW Australian forests , 2009 .
[6] S. Running,et al. Remote Sensing of Forest Fire Severity and Vegetation Recovery , 1996 .
[7] Nicholas C. Coops,et al. Forest recovery trends derived from Landsat time series for North American boreal forests , 2016 .
[8] Carol Miller,et al. Previous Fires Moderate Burn Severity of Subsequent Wildland Fires in Two Large Western US Wilderness Areas , 2013, Ecosystems.
[9] Robert E. Wolfe,et al. A Landsat surface reflectance dataset for North America, 1990-2000 , 2006, IEEE Geoscience and Remote Sensing Letters.
[10] K. Beven,et al. A physically based, variable contributing area model of basin hydrology , 1979 .
[11] Michael Dixon,et al. Google Earth Engine: Planetary-scale geospatial analysis for everyone , 2017 .
[12] David L. Verbyla,et al. Landscape-level interactions of prefire vegetation, burn severity, and postfire vegetation over a 16-year period in interior Alaska , 2005 .
[13] Michael A. Wulder,et al. Opening the archive: How free data has enabled the science and monitoring promise of Landsat , 2012 .
[14] Eric A. Lehmann,et al. Forest cover trends from time series Landsat data for the Australian continent , 2013, Int. J. Appl. Earth Obs. Geoinformation.
[15] Zhiqiang Yang,et al. Implementation of the LandTrendr Algorithm on Google Earth Engine , 2018, Remote. Sens..
[16] Fernando Pérez-Cabello,et al. Pinus halepensis regeneration after a wildfire in a semiarid environment: assessment using multitemporal Landsat images , 2011 .
[17] Mihai A. Tanase,et al. Mortality and recruitment of fire-tolerant eucalypts as influenced by wildfire severity and recent prescribed fire , 2016 .
[18] Joanne C. White,et al. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series , 2017 .
[19] Zhihua Liu. Effects of climate and fire on short-term vegetation recovery in the boreal larch forests of Northeastern China , 2016, Scientific Reports.
[20] M. Claverie,et al. Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. , 2016, Remote sensing of environment.
[21] Zhiqiang Yang,et al. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms , 2010 .
[22] Susan J. Prichard,et al. Prior wildfires influence burn severity of subsequent large fires , 2016 .
[23] H. Tian,et al. Continental-scale quantification of post-fire vegetation greenness recovery in temperate and boreal North America , 2017 .
[24] Laura J. Pollock,et al. Eucalypts face increasing climate stress , 2013, Ecology and evolution.
[25] Carl N. Skinner,et al. Factors influencing fire severity under moderate burning conditions in the Klamath Mountains, northern California, USA , 2017 .
[26] C. Woodcock,et al. Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images , 2015 .
[27] J. Evans,et al. Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics. , 2010, Ecology.
[28] Andrew K. Skidmore,et al. Using Landsat Spectral Indices in Time-Series to Assess Wildfire Disturbance and Recovery , 2018, Remote. Sens..
[29] Philip E. Dennison,et al. Remote Sensing Analysis of Vegetation Recovery following Short-Interval Fires in Southern California Shrublands , 2014, PloS one.
[30] Joanne C. White,et al. Analyzing spatial and temporal variability in short-term rates of post-fire vegetation return from Landsat time series , 2018 .
[31] Olga Viedma,et al. Assessing Landscape Fire Hazard by Multitemporal Automatic Classification of Landsat Time Series Using the Google Earth Engine in West-Central Spain , 2019, Forests.
[32] Ross A. Bradstock,et al. Remote sensing of fire severity in the Blue Mountains: influence of vegetation type and inferring fire intensity , 2006 .
[33] Su Ye,et al. A near-real-time approach for monitoring forest disturbance using Landsat time series: stochastic continuous change detection , 2021 .
[34] O. Viedma,et al. Modeling rates of ecosystem recovery after fires by using landsat TM data , 1997 .
[35] Andrew J. Pitman,et al. Regional signatures of future fire weather over eastern Australia from global climate models , 2011 .
[36] D. Mulligan,et al. Detecting the dynamics of vegetation disturbance and recovery in surface mining area via Landsat imagery and LandTrendr algorithm. , 2018 .
[37] Leon Bren,et al. Remote sensing of post-fire vegetation recovery; a study using Landsat 5 TM imagery and NDVI in North-East Victoria , 2012 .
[38] F. Lloret,et al. Influence of fire severity on plant regeneration by means of remote sensing imagery , 2003 .
[39] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[40] Yuhang Wang,et al. Century‐scale patterns and trends of global pyrogenic carbon emissions and fire influences on terrestrial carbon balance , 2015 .
[41] Sally A. Kenny,et al. Habitat or fuel? Implications of long‐term, post‐fire dynamics for the development of key resources for fauna and fire , 2011 .
[42] D. Roberts,et al. Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems , 2016 .
[43] M. Wulder,et al. Mapping wildfire and clearcut harvest disturbances in boreal forests with Landsat time series data , 2011 .
[44] Juli G. Pausas,et al. Fire regime and post-fire Normalized Difference Vegetation Index changes in the eastern Iberian peninsula (Mediterranean basin) , 2006 .
[45] Hankui K. Zhang,et al. Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. , 2016, Remote sensing of environment.
[46] J. Franklin,et al. Influence of short-interval fire occurrence on post-fire recovery of fire-prone shrublands in California, USA , 2013 .
[47] Alfonso Fernández-Manso,et al. Assessment of the influence of biophysical properties related to fuel conditions on fire severity using remote sensing techniques: a case study on a large fire in NW Spain , 2019, International Journal of Wildland Fire.
[48] R. Kennedy,et al. Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types , 2019, Fire Ecology.