Reprint

Remote Sensing of Above Ground Biomass

Edited by
August 2019
264 pages
  • ISBN978-3-03921-209-5 (Paperback)
  • ISBN978-3-03921-210-1 (PDF)

This is a Reprint of the Special Issue Remote Sensing of Above Ground Biomass that was published in

Engineering
Environmental & Earth Sciences
Summary

Above ground biomass has been listed by the Intergovernmental Panel on Climate Change as one of the five most prominent, visible, and dynamic terrestrial carbon pools. The increased awareness of the impacts of climate change has seen a burgeoning need to consistently assess carbon stocks to combat carbon sequestration. An accurate estimation of carbon stocks and an understanding of the carbon sources and sinks can aid the improvement and accuracy of carbon flux models, an important pre-requisite of climate change impact projections. Based on 15 research topics, this book demonstrates the role of remote sensing in quantifying above ground biomass (forest, grass, woodlands) across varying spatial and temporal scales. The innovative application areas of the book include algorithm development and implementation, accuracy assessment, scaling issues (local–regional–global biomass mapping), and the integration of microwaves (i.e. LiDAR), along with optical sensors, forest biomass mapping, rangeland productivity and abundance (grass biomass, density, cover), bush encroachment biomass, and seasonal and long-term biomass monitoring.

Format
  • Paperback
License and Copyright
© 2019 by the authors; CC BY-NC-ND license
Keywords
multi-angle remote sensing; forest structure information; vegetation indices; forest biomass; Bidirectional Reflectance Distribution Factor; biomass; yield; AquaCrop model; spectral index; particle swarm optimization; winter wheat; TerraSAR-X; Landsat; pasture biomass; Wambiana grazing trial; foliage projective cover; fractional vegetation cover; ALOS2; mixed forest; biomass; lidar; NDVI; grass biomass; SPLSR; vegetation indices; estimation accuracy; pasture biomass; ground-based remote sensing; ultrasonic sensor; field spectrometry; sensor fusion; short grass; alpine grassland conservation; anthropogenic disturbance; ecological policies; climate change; grazing exclusion; grazing management; regional sustainability; rice; biomass; dry matter index; chlorophyll index; CIRed-edge; NDLMA; forest above ground biomass (AGB); random forest; mapping; alpine meadow grassland; above-ground biomass; inversion model; error analysis; applicability evaluation; Land Surface Phenology; wetlands; above ground biomass; NDVI; MODIS time series; food security; Sahel; Niger; rangeland productivity; livestock; MODIS; NDVI; aboveground biomass; Atriplex nummularia; carbon mitigation; carbon inventory; forage crops; remote sensing; vegetation index; stem volume; dry biomass; conifer; broadleaves; light detection and ranging (LiDAR); regression analysis; correlation coefficient; n/a

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