Articles | Volume 11, issue 18
https://doi.org/10.5194/bg-11-5181-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-11-5181-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Land surface phenological response to decadal climate variability across Australia using satellite remote sensing
M. Broich
Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, NSW 2007, Australia
now at: Centre of Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington NSW 2052, Australia
Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, NSW 2007, Australia
M. G. Tulbure
Centre of Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington NSW 2052, Australia
X. Ma
Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, NSW 2007, Australia
Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
M. Paget
CSIRO Marine and Atmospheric Research, Pye Laboratory, Acton, ACT, 2600, Australia
N. Restrepo-Coupe
Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, NSW 2007, Australia
K. Davies
Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, NSW 2007, Australia
R. Devadas
Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, NSW 2007, Australia
A. Held
CSIRO Marine and Atmospheric Research, Pye Laboratory, Acton, ACT, 2600, Australia
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Cited
83 citations as recorded by crossref.
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- Dryland vegetation response to wet episode, not inherent shift in sensitivity to rainfall, behind Australia's role in 2011 global carbon sink anomaly V. Haverd et al. 10.1111/gcb.13202
- Evaluating land surface phenology from the Advanced Himawari Imager using observations from MODIS and the Phenological Eyes Network D. Yan et al. 10.1016/j.jag.2019.02.011
- Modeling grassland spring onset across the Western United States using climate variables and MODIS-derived phenology metrics Q. Xin et al. 10.1016/j.rse.2015.02.003
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81 citations as recorded by crossref.
- Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland B. Lara & M. Gandini 10.1080/2150704X.2016.1168945
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- Assessment of Regional Vegetation Response to Climate Anomalies: A Case Study for Australia Using GIMMS NDVI Time Series between 1982 and 2006 W. De Keersmaecker et al. 10.3390/rs9010034
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- Satellite-observed shifts in C3/C4 abundance in Australian grasslands are associated with rainfall patterns Q. Xie et al. 10.1016/j.rse.2022.112983
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- High Resolution Forest Masking for Seasonal Monitoring with a Regionalized and Colourimetrically Assisted Chorologic Typology R. Aravena et al. 10.3390/rs15143457
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- A spatio-temporal analysis of canopy dynamics and intra-stand competition in a riparian forest, south-eastern Australia E. Curtis et al. 10.1016/j.foreco.2018.08.044
- Essential dryland ecosystem variables B. Wu et al. 10.1016/j.cosust.2020.10.007
- Changes in foliage projective cover and its implications for mapping groundwater dependent vegetation across a precipitation gradient B. Parker et al. 10.1002/eco.1937
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- A spatially explicit land surface phenology data product for science, monitoring and natural resources management applications M. Broich et al. 10.1016/j.envsoft.2014.11.017
- Dryland vegetation response to wet episode, not inherent shift in sensitivity to rainfall, behind Australia's role in 2011 global carbon sink anomaly V. Haverd et al. 10.1111/gcb.13202
- Evaluating land surface phenology from the Advanced Himawari Imager using observations from MODIS and the Phenological Eyes Network D. Yan et al. 10.1016/j.jag.2019.02.011
- Modeling grassland spring onset across the Western United States using climate variables and MODIS-derived phenology metrics Q. Xin et al. 10.1016/j.rse.2015.02.003
- Sensitivity of remote sensing-based vegetation proxies to climate and sea surface temperature variabilities in Australia and parts of Southeast Asia S. Arjasakusuma et al. 10.1080/01431161.2020.1782509
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- Canopy leaf area of a mature evergreen Eucalyptus woodland does not respond to elevated atmospheric [CO2] but tracks water availability R. Duursma et al. 10.1111/gcb.13151
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- Assessing spatial and temporal patterns in land surface phenology for the Australian Alps (2000–2014) J. Thompson & D. Paull 10.1016/j.rse.2017.06.032
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- Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics A. Lausch et al. 10.3390/rs8121029
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- A Semiprognostic Phenology Model for Simulating Multidecadal Dynamics of Global Vegetation Leaf Area Index Q. Xin et al. 10.1029/2019MS001935
- Analysis and prediction of rubber tree phenological changes during Pestalotiopsis infection using Sentinel-2 imagery and random forest Y. Herdiyeni et al. 10.1117/1.JRS.18.014524
- Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation (NVDI) with MODIS NDVI C. Burton et al. 10.5194/essd-16-4389-2024
- Assessing woody vegetation trends in Sahelian drylands using MODIS based seasonal metrics M. Brandt et al. 10.1016/j.rse.2016.05.027
- Phenology estimation of subtropical bamboo forests based on assimilated MODIS LAI time series data X. Li et al. 10.1016/j.isprsjprs.2021.01.018
- Climatic and non-climatic vegetation cover changes in the rangelands of Africa F. D'Adamo et al. 10.1016/j.gloplacha.2021.103516
- Variability and evolution of global land surface phenology over the past three decades (1982–2012) I. Garonna et al. 10.1111/gcb.13168
- Land surface phenology derived from normalized difference vegetation index (NDVI) at global FLUXNET sites C. Wu et al. 10.1016/j.agrformet.2016.11.193
- Detecting dryland degradation using Time Series Segmentation and Residual Trend analysis (TSS-RESTREND) A. Burrell et al. 10.1016/j.rse.2017.05.018
- Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography C. Moore et al. 10.5194/bg-13-5085-2016
- Development of a global annual land surface phenology dataset for 1982–2018 from the AVHRR data by implementing multiple phenology retrieving methods W. Wu et al. 10.1016/j.jag.2021.102487
- Abrupt shifts in phenology and vegetation productivity under climate extremes X. Ma et al. 10.1002/2015JG003144
- Land cover change during a period of extensive landscape restoration in Ningxia Hui Autonomous Region, China A. Cadavid Restrepo et al. 10.1016/j.scitotenv.2017.04.124
- Sentinel-2 time series: a promising tool in monitoring temperate species spring phenology E. Grabska-Szwagrzyk et al. 10.1093/forestry/cpad039
- A remote sensing spatio-temporal framework for interpreting sparse indicators in highly variable arid landscapes E. Lawley et al. 10.1016/j.ecolind.2015.01.042
- Using Multi-Temporal Satellite Data to Analyse Phenological Responses of Rubber (Hevea brasiliensis) to Climatic Variations in South Sumatra, Indonesia F. Azizan et al. 10.3390/rs13152932
- Hydrologic connectivity drives extremes and high variability in vegetation productivity across Australian arid and semi-arid ecosystems A. Norton et al. 10.1016/j.rse.2022.112937
- Remote sensing monitoring of the spatiotemporal dynamics of urban forest phenology and its response to climate and urbanization M. Hu et al. 10.1016/j.uclim.2024.101810
- Temporal Trends and Spatial Variability of Vegetation Phenology over the Northern Hemisphere during 1982-2012 S. Wang et al. 10.1371/journal.pone.0157134
- Multi-climate mode interactions drive hydrological and vegetation responses to hydroclimatic extremes in Australia Z. Xie et al. 10.1016/j.rse.2019.111270
- Attribution of NDVI Dynamics over the Globe from 1982 to 2015 C. Liu et al. 10.3390/rs14112706
- The Addition of Temperature to the TSS-RESTREND Methodology Significantly Improves the Detection of Dryland Degradation A. Burrell et al. 10.1109/JSTARS.2019.2906466
- Impacts of extreme climate on Australia's green cover (2003–2018): A MODIS and mascon probe A. Saleem et al. 10.1016/j.scitotenv.2020.142567
- Spatiotemporal patterns of remotely sensed phenology and their response to climate change and topography in subtropical bamboo forests during 2001-2017: a case study in Zhejiang Province, China X. Li et al. 10.1080/15481603.2022.2163575
- Toward a Novel Method for General On-Orbit Earth Surface Anomaly Detection Leveraging Large Vision Models and Lightweight Priors J. Xu et al. 10.1109/TGRS.2024.3432749
- Woody plant cover estimation in drylands from Earth Observation based seasonal metrics M. Brandt et al. 10.1016/j.rse.2015.10.036
- Spatiotemporal patterns of vegetation phenology change and relationships with climate in the two transects of East China X. Wang et al. 10.1016/j.gecco.2017.01.010
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