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Selection: Lucas:R [3 articles] 

Publications by author Lucas:R.
 

New global forest/non-forest maps from ALOS PALSAR data (2007–2010)

  
Remote Sensing of Environment, Vol. 155 (December 2014), pp. 13-31, https://doi.org/10.1016/j.rse.2014.04.014

Abstract

[Highlights] [::] Global mosaics of ALOS-SAR data were generated annually from 2007 to 2010. [::] Region variability in L-band HH and HV gamma-naught (γ0) for forests was observed. [::] Region-specific thresholds were applied to produce a global forest/non-forest map. [::] The overall agreement was 95%. [::] Annual decreases of HH and HV γ0 suggest a decrease in forest and smoothing Earth. [Abstract] Four global mosaics of Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) HH and HV polarization data were generated at 25 m ...

 

An integrated pan-tropical biomass map using multiple reference datasets

  
Global Change Biology, Vol. 22, No. 4. (April 2016), pp. 1406-1420, https://doi.org/10.1111/gcb.13139

Abstract

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns ...

 

Challenges and opportunities in harnessing satellite remote-sensing for biodiversity monitoring

  
Ecological Informatics (September 2015), https://doi.org/10.1016/j.ecoinf.2015.08.006

Abstract

Monitoring biodiversity changes have become a major concern for governmental agencies. Remote-sensing can deliver very high resolution (VHR) data on habitats. We describe the challenges to be faced when using such data. We further propose VHR baseline conditions to improve future monitoring. The ability of remote-sensing technologies to rapidly deliver data on habitat quantity (e.g., amount, configuration) and quality (e.g., structure, distribution of individual plant species, habitat types and/or communities, persistence) across a range of spatial resolutions and temporal frequencies ...

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Integrated Natural Resources Modelling and Management - Meta-information Database. http://mfkp.org/INRMM/author/Lucas:R

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