Remote Sensing of Biophysical Parameters

Vegetation plays an essential role in the study of the environment through plant respiration and photosynthesis. Therefore, the assessment of the current vegetation status is critical to modeling terrestrial ecosystems and energy cycles. Canopy structure (LAI, fCover, plant height, biomass, leaf ang...

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description Vegetation plays an essential role in the study of the environment through plant respiration and photosynthesis. Therefore, the assessment of the current vegetation status is critical to modeling terrestrial ecosystems and energy cycles. Canopy structure (LAI, fCover, plant height, biomass, leaf angle distribution) and biochemical parameters (leaf pigmentation and water content) have been employed to assess vegetation status and its dynamics at scales ranging from kilometric to decametric spatial resolutions thanks to methods based on remote sensing (RS) data.Optical RS retrieval methods are based on the radiative transfer processes of sunlight in vegetation, determining the amount of radiation that is measured by passive sensors in the visible and infrared channels. The increased availability of active RS (radar and LiDAR) data has fostered their use in many applications for the analysis of land surface properties and processes, thanks to their insensitivity to weather conditions and the ability to exploit rich structural and texture information. Optical and radar data fusion and multi-sensor integration approaches are pressing topics, which could fully exploit the information conveyed by both the optical and microwave parts of the electromagnetic spectrum.This Special Issue reprint reviews the state of the art in biophysical parameters retrieval and its usage in a wide variety of applications (e.g., ecology, carbon cycle, agriculture, forestry and food security).
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spelling doab-20.500.12854ir-920522024-03-27T16:34:40Z Remote Sensing of Biophysical Parameters García-Haro, Francisco Javier Fang, Hongliang Campos-Taberner, Manuel hyperspectral spectroscopy equivalent water thickness canopy water content agriculture EnMAP LAI LCC FAPAR FVC CCC PROSAIL GPR machine learning active learning Landsat 8 surface reflectance LEDAPS LaSRC 6SV SREM NDVI artificial neural networks canopy chlorophyll content INFORM leaf area index SAIL fluorescence in vivo spectrometry ASD Field Spec lead ions remote sensing indices meteosat second generation (MSG) biophysical parameters (LAI FAPAR) SEVIRI climate data records (CDR) stochastic spectral mixture model (SSMM) Satellite Application Facility for Land Surface Analysis (LSA SAF) the fraction of radiation absorbed by photosynthetic components (FAPARgreen) triple-source leaf area index (LAI) woody area index (WAI) clumping index (CI) Moderate Resolution Imaging Spectroradiometer (MODIS) soil albedo unmanned aircraft vehicle multispectral sensor vegetation indices rapeseed crop site-specific farming Sentinel-2 forest vegetation radiative transfer model Discrete Anisotropic Radiative Transfer (DART) model MODIS fraction of photosynthetically active radiation absorbed by vegetation (FPAR) three-dimensional radiative transfer model (3D RTM) uncertainty assessment vertical foliage profile (VFP) terrestrial laser scanning (TLS) airborne laser scanning (ALS) spaceborne laser scanning (SLS) riparian invasive vegetation burn severity canopy loss wildfire thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Vegetation plays an essential role in the study of the environment through plant respiration and photosynthesis. Therefore, the assessment of the current vegetation status is critical to modeling terrestrial ecosystems and energy cycles. Canopy structure (LAI, fCover, plant height, biomass, leaf angle distribution) and biochemical parameters (leaf pigmentation and water content) have been employed to assess vegetation status and its dynamics at scales ranging from kilometric to decametric spatial resolutions thanks to methods based on remote sensing (RS) data.Optical RS retrieval methods are based on the radiative transfer processes of sunlight in vegetation, determining the amount of radiation that is measured by passive sensors in the visible and infrared channels. The increased availability of active RS (radar and LiDAR) data has fostered their use in many applications for the analysis of land surface properties and processes, thanks to their insensitivity to weather conditions and the ability to exploit rich structural and texture information. Optical and radar data fusion and multi-sensor integration approaches are pressing topics, which could fully exploit the information conveyed by both the optical and microwave parts of the electromagnetic spectrum.This Special Issue reprint reviews the state of the art in biophysical parameters retrieval and its usage in a wide variety of applications (e.g., ecology, carbon cycle, agriculture, forestry and food security). 2022-09-16T13:46:24Z 2022-09-16T13:46:24Z 2022 book ONIX_20220916_9783036549019_38 9783036549019 9783036549026 https://directory.doabooks.org/handle/20.500.12854/92052 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/5926 https://mdpi.com/books/pdfview/book/5926 10.3390/books978-3-0365-4902-6 10.3390/books978-3-0365-4902-6 MDPI - Multidisciplinary Digital Publishing Institute 9783036549019 9783036549026 274 Basel open access
spellingShingle hyperspectral
spectroscopy
equivalent water thickness
canopy water content
agriculture
EnMAP
LAI
LCC
FAPAR
FVC
CCC
PROSAIL
GPR
machine learning
active learning
Landsat 8
surface reflectance
LEDAPS
LaSRC
6SV
SREM
NDVI
artificial neural networks
canopy chlorophyll content
INFORM
leaf area index
SAIL
fluorescence
in vivo
spectrometry
ASD Field Spec
lead ions
remote sensing indices
meteosat second generation (MSG)
biophysical parameters (LAI
FAPAR)
SEVIRI
climate data records (CDR)
stochastic spectral mixture model (SSMM)
Satellite Application Facility for Land Surface Analysis (LSA SAF)
the fraction of radiation absorbed by photosynthetic components (FAPARgreen)
triple-source
leaf area index (LAI)
woody area index (WAI)
clumping index (CI)
Moderate Resolution Imaging Spectroradiometer (MODIS)
soil albedo
unmanned aircraft vehicle
multispectral sensor
vegetation indices
rapeseed crop
site-specific farming
Sentinel-2
forest
vegetation radiative transfer model
Discrete Anisotropic Radiative Transfer (DART) model
MODIS
fraction of photosynthetically active radiation absorbed by vegetation (FPAR)
three-dimensional radiative transfer model (3D RTM)
uncertainty assessment
vertical foliage profile (VFP)
terrestrial laser scanning (TLS)
airborne laser scanning (ALS)
spaceborne laser scanning (SLS)
riparian
invasive vegetation
burn severity
canopy loss
wildfire
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
Remote Sensing of Biophysical Parameters
title Remote Sensing of Biophysical Parameters
title_full Remote Sensing of Biophysical Parameters
title_fullStr Remote Sensing of Biophysical Parameters
title_full_unstemmed Remote Sensing of Biophysical Parameters
title_short Remote Sensing of Biophysical Parameters
title_sort remote sensing of biophysical parameters
topic hyperspectral
spectroscopy
equivalent water thickness
canopy water content
agriculture
EnMAP
LAI
LCC
FAPAR
FVC
CCC
PROSAIL
GPR
machine learning
active learning
Landsat 8
surface reflectance
LEDAPS
LaSRC
6SV
SREM
NDVI
artificial neural networks
canopy chlorophyll content
INFORM
leaf area index
SAIL
fluorescence
in vivo
spectrometry
ASD Field Spec
lead ions
remote sensing indices
meteosat second generation (MSG)
biophysical parameters (LAI
FAPAR)
SEVIRI
climate data records (CDR)
stochastic spectral mixture model (SSMM)
Satellite Application Facility for Land Surface Analysis (LSA SAF)
the fraction of radiation absorbed by photosynthetic components (FAPARgreen)
triple-source
leaf area index (LAI)
woody area index (WAI)
clumping index (CI)
Moderate Resolution Imaging Spectroradiometer (MODIS)
soil albedo
unmanned aircraft vehicle
multispectral sensor
vegetation indices
rapeseed crop
site-specific farming
Sentinel-2
forest
vegetation radiative transfer model
Discrete Anisotropic Radiative Transfer (DART) model
MODIS
fraction of photosynthetically active radiation absorbed by vegetation (FPAR)
three-dimensional radiative transfer model (3D RTM)
uncertainty assessment
vertical foliage profile (VFP)
terrestrial laser scanning (TLS)
airborne laser scanning (ALS)
spaceborne laser scanning (SLS)
riparian
invasive vegetation
burn severity
canopy loss
wildfire
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
topic_facet hyperspectral
spectroscopy
equivalent water thickness
canopy water content
agriculture
EnMAP
LAI
LCC
FAPAR
FVC
CCC
PROSAIL
GPR
machine learning
active learning
Landsat 8
surface reflectance
LEDAPS
LaSRC
6SV
SREM
NDVI
artificial neural networks
canopy chlorophyll content
INFORM
leaf area index
SAIL
fluorescence
in vivo
spectrometry
ASD Field Spec
lead ions
remote sensing indices
meteosat second generation (MSG)
biophysical parameters (LAI
FAPAR)
SEVIRI
climate data records (CDR)
stochastic spectral mixture model (SSMM)
Satellite Application Facility for Land Surface Analysis (LSA SAF)
the fraction of radiation absorbed by photosynthetic components (FAPARgreen)
triple-source
leaf area index (LAI)
woody area index (WAI)
clumping index (CI)
Moderate Resolution Imaging Spectroradiometer (MODIS)
soil albedo
unmanned aircraft vehicle
multispectral sensor
vegetation indices
rapeseed crop
site-specific farming
Sentinel-2
forest
vegetation radiative transfer model
Discrete Anisotropic Radiative Transfer (DART) model
MODIS
fraction of photosynthetically active radiation absorbed by vegetation (FPAR)
three-dimensional radiative transfer model (3D RTM)
uncertainty assessment
vertical foliage profile (VFP)
terrestrial laser scanning (TLS)
airborne laser scanning (ALS)
spaceborne laser scanning (SLS)
riparian
invasive vegetation
burn severity
canopy loss
wildfire
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
url ONIX_20220916_9783036549019_38