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Earth Observation in Forest Biophysical/Biochemical Parameter Retrieval
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This reprint discusses advancements in forest research using Earth Observation datasets. Forests, which occupy about one-third of the terrestrial surface of Earth, play an indispensable role in monitoring global climate change and ecosystem dynamics. The health of forests has been affected in recent years by various stress factors, such as forest fragmentation and deforestation, biodiversity loss, climate change, invasive species, drought, and unsustainable management. This reprint focuses on the evaluation of different techniques for the retrieval of different biophysical/biochemical parameters using available Earth Observation data. The following topics have been covered in this reprint: Mangrove forest carbon assessment using EO data; Phenological ,etrics of plant species using NDVI time series data; fPAR for diversity relation; Forest/canopy height retrieval using Pol-InSAR modeling; Dominant species discrimination using LiDAR data; Biophysical parameters estimation of young oil palm using UAV;

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Keywords

  • Atlas
  • Bhitarkanika
  • Bhitarkanika Forest Reserve
  • Biology, Life Sciences
  • biophysical parameters
  • Blue Carbon
  • carbon stock
  • combined model
  • different altitudes
  • dynamic habitat index
  • field spectroradiometer
  • forest height
  • forest structure
  • forest vertical structure
  • fractional differentiation
  • Gaussian vertical backscatter (GVB) volume
  • GEDI
  • ground topography in forested terrain
  • hyperspectral data
  • ICESat
  • Indian biogeographic region
  • laser intensity
  • laser pointing angle
  • leaf N/P ratio
  • LiDAR
  • Machine learning
  • mangrove forest
  • Mathematics & science
  • mixed forest in karst areas
  • moderate resolution imaging spectroradiometer
  • MODIS
  • multi-baseline optimization
  • multifrequency
  • multispectral
  • NDVI
  • overcome overfitting
  • P-band polarimetric interferometric synthetic aperture radar (Pol-InSAR)
  • phenology
  • plant richness
  • PolInSAR inversion
  • random forest
  • Reference, information & interdisciplinary subjects
  • regression models
  • Remote sensing
  • Research & information: general
  • Sentinel-1
  • Sentinel-2
  • smoothing
  • spaceborne SAR
  • stand dominant species
  • stand volume
  • symbolic regression
  • UAV
  • young oil palm

Links

DOI: 10.3390/books978-3-0365-6526-2

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