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While international efforts in the development of short rotation woody crops (SRWCs) have historically focused on the production of biomass for bioenergy, biofuels, and bioproducts, research and deployment over the past decade has expanded to include broader objectives of achieving multiple ecosystem services. In particular, silvicultural prescriptions developed for SRWCs have been refined to include woody crop production systems for environmental benefits such as carbon sequestration, water quality and quantity, and soil health. In addition, current systems have been expanded beyond traditional fiber production to other environmental technologies that incorporate SRWCs as vital components for phytotechnologies, urban afforestation, ecological restoration, and mine reclamation. In this Special Issue of the journal Forests, we explore the broad range of current research dedicated to our topic: International Short Rotation Woody Crop Production Systems for Ecosystem Services and Phytotechnologies

rhizospheric soil --- allocation --- acidic soil --- abandoned farmland --- carbon sequestration --- bioenergy --- mycorrhizal fungi --- leaf area index --- foliar nutrient and metal concentration --- aboveground biomass --- inoculation --- stocking level --- site reclamation --- willow --- Salix --- spacing trial --- agricultural field experiment --- Populus --- Populus canadensis --- species variation --- ecosystem services

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The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was conducted in different parts of the world. Knowledge and understanding gained from this book can be used for the sustainable management of mangrove forests of the world

Landsat --- estuary --- protected area --- land use --- land cover --- change detection --- time series --- Great Barrier Reef --- Sentinel-2 --- ALOS-2 PALSAR-2 --- mangrove --- above-ground biomass --- extreme gradient boosting --- Can Gio biosphere reserve --- Vietnam --- LiDAR --- random forest --- GLAS --- aboveground biomass --- mangrove plantation --- aboveground biomass estimation --- optical images --- SAR --- DSM --- vegetation index --- color --- RGB --- accuracy assessment --- transgression --- mangrove development --- machine learning --- mangrove condition --- classification --- remote sensing --- ecosystem --- upscaling --- Worldview-2 --- Niger Delta Region --- mangroves --- land cover dynamics --- intensity analysis --- fragmentation --- spectral-temporal metrics --- land degradation --- ALOS PALSAR-2 --- JERS-1 --- GLCM --- Markov chain --- cellular automata --- data fusion --- forest monitoring --- Google Earth Engine --- mangrove forests --- multi-temporal analysis --- satellite earth observation --- time series analysis --- GEEMMM --- google earth engine --- Myanmar --- cloud computing --- digital earth --- GAMs --- Generalized Additive Models --- EVI --- phenology --- n/a

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Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

artificial neural network --- downscaling --- simulation --- 3D point cloud --- European beech --- consistency --- adaptive threshold --- evaluation --- photosynthesis --- geographic information system --- P-band PolInSAR --- validation --- density-based clustering --- structure from motion (SfM) --- EPIC --- Tanzania --- signal attenuation --- trunk --- canopy closure --- REDD+ --- unmanned aerial vehicle (UAV) --- forest --- recursive feature elimination --- Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) --- aboveground biomass --- random forest --- uncertainty --- household survey --- spectral information --- forests biomass --- root biomass --- biomass --- unmanned aerial vehicle --- Brazilian Amazon --- VIIRS --- global positioning system --- LAI --- photochemical reflectance index (PRI) --- allometric scaling and resource limitation --- R690/R630 --- modelling aboveground biomass --- leaf area index --- forest degradation --- spectral analyses --- terrestrial laser scanning --- BAAPA --- leaf area index (LAI) --- stem volume estimation --- tomographic profiles --- polarization coherence tomography (PCT) --- canopy gap fraction --- automated classification --- HemiView --- remote sensing --- multisource remote sensing --- Pléiades imagery --- photogrammetric point cloud --- farm types --- terrestrial LiDAR --- altitude --- RapidEye --- forest aboveground biomass --- recovery --- southern U.S. forests --- NDVI --- machine-learning --- conifer forest --- satellite --- chlorophyll fluorescence (ChlF) --- tree heights --- phenology --- point cloud --- local maxima --- clumping index --- MODIS --- digital aerial photograph --- Mediterranean --- hemispherical sky-oriented photo --- managed temperate coniferous forests --- fixed tree window size --- drought --- GLAS --- smartphone-based method --- forest above ground biomass (AGB) --- forest inventory --- over and understory cover --- sampling design

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Savannas and woodlands are one of the most challenging targets for remote sensing. This book provides a current snapshot of the geographical focus and application of the latest sensors and sensor combinations in savannas and woodlands. It includes feature articles on terrestrial laser scanning and on the application of remote sensing to characterization of vegetation dynamics in the Mato Grosso, Cerrado and Caatinga of Brazil. It also contains studies focussed on savannas in Europe, North America, Africa and Australia. It should be important reading for environmental practitioners and scientists globally who are concerned with the sustainability of the global savanna and woodland biome.

Savanna --- alternative stable states --- MODIS VCF --- land surface temperature --- albedo --- Cerrado --- Amazon --- vegetation type --- optical --- sar --- synergism --- mapping --- savanna --- post oak --- vegetation index --- ecosystem function --- phenology --- encroachment --- evergreen --- deciduous --- vegetation --- grassland --- fractional cover --- trend --- ecoregion --- bare soil --- livestock --- production systems --- remote sensing --- vegetation dynamics --- vegetation persistence --- conservation --- savannas --- Africa --- vegetation indices --- oak-grass savanna --- hydrology --- Sentinel-2 --- land cover --- grasslands --- forests --- monitoring --- random forest --- spectral indexes --- vegetation seasonality --- aboveground biomass --- Cerrado ecosystem --- SAR --- allometry --- biomass --- carbon --- cost-effective --- LiDAR --- TLS --- plant water availability --- tree phenology --- phenocams --- MODIS --- terrestrial laser scanning (TLS) --- Above Ground Biomass (AGB) --- 3D point cloud --- vegetation structure --- n/a

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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.

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