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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
Technology: general issues --- 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.
Research & information: general --- 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
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It is increasingly being recognized that land use and land cover changes driven by anthropogenic pressures are impacting terrestrial and aquatic ecosystems and their services, human society, and human livelihoods and well-being. This Special Issue contains 12 original papers covering various issues related to land use and land use changes in various parts of the world (see references), with the purpose of providing a forum to exchange ideas and progress in related areas. Research topics include land use targets, dynamic modelling and mapping using satellite images, pressures from energy production, deforestation, impacts on ecosystem services, aboveground biomass evaluation, and investigations on libraries of legends and classification systems.
Environmental monitoring --- savannah --- multifunctionality --- protected areas --- conservation --- airborne laser scanning --- aboveground woody biomass --- CORINE land cover --- mapping of changes --- GIS tools --- land cover flows --- Low Tatras National Park --- land use and land cover --- ecosystem service value --- Google Earth Engine (GEE) --- forest fragmentation --- transboundary landscape --- Himalaya --- land-cover change --- MSPA --- cluster analysis --- land use management --- synthesis of land use/land cover definitions --- meta-analysis studies in land use/land cover --- challenges and knowledge gaps in land use/land cover assessments --- literature review --- land use change --- modeling --- scenario --- deforestation --- DINAMICA EGO --- PFBC landscapes --- Democratic Republic of the Congo --- tree diversity --- ecosystem resilience --- native tree --- urban environment --- urbanization --- land cover --- land use --- change mapping --- land use pressures --- energy production --- forestry --- caatinga domain --- digital classification --- remote sensing --- land consumption --- land re-naturalization --- developed land recycling --- urban land use efficiency --- interoperability --- standards --- geospatial --- semantic ontology --- harmonization --- classification --- urban growth --- land cover change --- driving forces --- n/a
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This Special Issue (SI), entitled "Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass”, resulted from 13 peer-reviewed papers dedicated to Forestry and Biomass mapping, characterization and accounting. The papers' authors presented improvements in Remote Sensing processing techniques on satellite images, drone-acquired images and LiDAR images, both aerial and terrestrial. Regarding the images’ classification models, all authors presented supervised methods, such as Random Forest, complemented by GIS routines and biophysical variables measured on the field, which were properly georeferenced. The achieved results enable the statement that remote imagery could be successfully used as a data source for regression analysis and formulation and, in this way, used in forestry actions such as canopy structure analysis and mapping, or to estimate biomass. This collection of papers, presented in the form of a book, brings together 13 articles covering various forest issues and issues in forest biomass calculation, constituting an important work manual for those who use mixed GIS and RS techniques.
Research & information: general --- Geography --- AGB estimation and mapping --- mangroves --- UAV LiDAR --- WorldView-2 --- terrestrial laser scanning --- above-ground biomass --- nondestructive method --- DBH --- bark roughness --- Landsat dataset --- forest AGC estimation --- random forest --- spatiotemporal evolution --- aboveground biomass --- variable selection --- forest type --- machine learning --- subtropical forests --- Landsat 8 OLI --- seasonal images --- stepwise regression --- map quality --- subtropical forest --- urban vegetation --- biomass estimation --- Sentinel-2A --- Xuzhou --- forest biomass estimation --- forest inventory data --- multisource remote sensing --- biomass density --- ecosystem services --- trade-off --- synergy --- multiple ES interactions --- valley basin --- norway spruce --- LiDAR --- allometric equation --- individual tree detection --- tree height --- diameter at breast height --- GEOMON --- ALOS-2 L band SAR --- Sentinel-1 C band SAR --- Sentinel-2 MSI --- ALOS DSM --- stand volume --- support vector machine for regression --- ordinary kriging --- forest succession --- leaf area index --- plant area index --- machine learning algorithms --- forest growing stock volume --- SPOT6 imagery --- Pinus massoniana plantations --- sentinel 2 --- landsat --- remote sensing --- GIS --- shrubs biomass --- bioenergy --- vegetation indices
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Agricultural diversification can occur in many forms (e.g., genetic variety, species, structural) and can be created temporally and over different spatially scales (e.g., within crop, within field, and landscape level). Crop diversification is the practice of growing more than one crop species within a farming area in the form of rotations (two or more crops on the same field in different years), multiple crops (more than one crop in the same season on the same field) or intercropping (at least two crops simultaneously on the same field).Various cropping strategies and management practices, such as diversification of cropping systems by crop rotation, conservation tillage, and the use of cover crops, have been promoted to enhance crop productivity and ecosystem services. However, the opportunities and means differ among regions and the actual effects of diversification on cropping system sustainability still need more investigation.This Special Issue covers the state-of-the-art and recent progress in different aspects related to agricultural diversification to increase the sustainability and resilience of a wide range of cropping systems (grassland, horticultural crops, fruit trees) and in a scenario of environmental challenges due to climate change: Crop production and quality; Impact of crop diversification on soil quality and biodiversity; Environmental impact and delivery of ecosystem services by crop diversification.
Research. --- Environmental economics. --- blue prawn --- black tiger shrimp --- economic efficiency --- farming systems --- salinity intrusion --- soil salinity --- white-legged shrimp --- big blue stem --- Cave in rock --- claypan --- forbs --- legumes --- intercropping --- cropping systems --- Sub-Saharan Africa --- millet and sorghum --- diversification --- monocultivar --- mixed-species plantation --- biodiversity --- arthropod --- soil --- on-farm biodiversity indicators --- lupin --- triticale --- weeds --- nitrogen --- convolutional neural network --- light competition --- transfer learning --- growth stages --- mixed cropping --- accumulate growing degree days --- phyllochron --- grass regrowth --- leaf sheaths --- blades --- agricultural sustainability --- crop rotation --- rice --- eco-economic benefit --- externality --- perennial cropping systems --- grape production --- medicinal and aromatic plants --- grapevine yield --- must quality --- experimental design --- aboveground mass --- black medick --- Egyptian clover --- grain yield --- nutrients --- white clover --- foodshed --- archipelago --- city region --- food modelling --- food self-sufficiency --- self-reliance --- food security --- agricultural diversification --- food planning --- regional food system --- crop diversification --- small farms --- HHI-Index --- Poland --- biochar --- sunflower husk --- soil respiration --- soybean --- n/a
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The use of electronics, close-range sensing, and artificial intelligence has changed the management paradigm in many contemporary industries in which Big Data analytics by automated processes has become the backbone of decision making and improvement. Acknowledging the integration of electronics, devices, sensors, and intelligent algorithms in much of the equipment used in forest operations, as well as their use in various forestry-related applications, it is apparent that many disciplines within forestry and forest science still rely on data collected traditionally, which is resource-intensive. In turn, this brings limitations in characterizing the specific behaviors of forest product systems and wood supply chains, and often prevents the development of solutions for improvement or inferring the laws behind the operation and management of such systems. Undoubtedly, many solutions still need to be developed in the future to provide the technology required for the effective management of forests. In this regard, the Special Issue entitled “Electronics, Close-Range Sensors and Artificial Intelligence in Forestry” highlights many examples of how technological improvements can be brought to forestry and to other related fields of science and practice.
Research & information: general --- Biology, life sciences --- Forestry & related industries --- forest fire detection --- deep learning --- ensemble learning --- Yolov5 --- EfficientDet --- EfficientNet --- big data --- automation --- artificial intelligence --- multi-modality --- acceleration --- classification --- events --- performance --- motor-manual felling --- willow --- Romania --- region detection of forest fire --- grading of forest fire --- weakly supervised loss --- fine segmentation --- region-refining segmentation --- lightweight Faster R-CNN --- ultrasound sensors --- road scanner --- terrestrial laser scanning --- TLS --- forest road maintenance --- forest road monitoring --- crowned road surface --- digital twinning --- climate smart --- LiDAR --- digitalization --- forest loss --- land-cover change --- machine learning --- spatial heterogeneity --- random forest model --- geographically weighted regression --- aboveground biomass --- estimation --- remote sensing --- Sentinel-2 --- Iran --- multiple regression --- artificial neural network --- k-nearest neighbor --- random forest --- canopy --- drone --- leaf --- leaves --- foliar --- samples --- sampling --- Aerial robotics --- UAS --- UAV --- IoT --- forest ecology --- accessibility --- wood --- diameter --- length --- close-range sensing --- Augmented Reality --- comparison --- accuracy --- effectiveness --- potential --- forestry 4.0 --- wood technology --- sawmilling --- productivity --- prediction --- long-term --- tree ring --- forestry detection --- resistance sensor --- micro-drilling resistance method --- signal processing --- Signal-to-Noise Ratio (SNR) --- n/a
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The production of industrial and bioenergy crops has been the subject of scientific research for many years; however, the implementation of previously proposed solutions for commercial production is still at an early stage. It should be emphasized that when developing the production of industrial and bioenergy crops on agricultural lands, it is important to avoid land-use competition with the production of food and feed. It is well justified, for initiating the sustainable production of industrial and bioenergy crops, to promote efficient species for growing on marginal lands, which are unsuitable or less suitable for food or feed production. Another important point is that industrial and bioenergy crops should include nonfood and nonfeed crops and generate agricultural products categorized as commodities and/or raw materials for industrial goods and bioenergy. These industrial and bioenergy crops can become an important source of biomass. Of course, the concept of their cultivation for nonfood (and/or nonfeed) uses is not new but, despite considerable investment in research and development, little progress has been made with regard to the introduction of such crops and their products into the market. Therefore, the papers focus on innovations and perspectives regarding sustainable industrial and bioenergy crops production, logistic chains, biomass quality, utilization and cascade biomass use for bioeconomy, socio-economic and energy analyses, etc.
Technology: general issues --- History of engineering & technology --- harvesting --- work productivity --- supply chain --- harvesting efficiency --- Salix --- genoype × site interaction --- survivability --- biometric features --- plant height --- fresh biomass yield --- dry biomass yield --- Miscanthus --- nitrogen fertilization --- rhizomes --- stem --- leaves --- consumer choices --- eucalyptus --- firewood --- Italy --- multilevel logistic regression model --- willingness to consume --- tobacco biomass --- energy yield --- higher heating value --- biogas potential --- Nicotiana tabacum --- energy crops --- planting density --- calorific value --- SRC --- hulled wheat species --- energy --- life cycle assessment --- Tenebrio molitor --- edible insects --- larval development --- feed conversion ratio --- agricultural and industrial residues --- lignocellulosic biomass --- bioconversion --- agroforestry --- biodiversity --- bioeconomy --- biomass supply --- circular economy --- organic farming --- perennial crops --- quarry --- syntropy --- vegetation restoration --- willow --- varieties --- yield --- marginal soil --- biological diversity --- marginal land --- cup plant --- perennial energy crop --- energy expenses --- biogas --- biomass yield --- willow SRC --- energy plants --- ground beetles --- Carabidae --- ecosystem services --- invertebrate biodiversity --- willow-leaf sunflower --- Jerusalem artichoke --- supercritical extraction --- water as co-solvent --- antimicrobial activity --- biocidal effect --- bioenergy crop --- groundwater --- growth --- invasive potential --- reproductive potential --- Silphium perfoliatum --- soil moisture --- water table distance --- energy biomass --- yields --- invasive behavior --- economics --- common osier --- fertilization --- dry matter yield --- soil chemical parameters --- soil bulk density --- water-stable aggregates --- soil microbial carbon --- willow browse --- soluble carbohydrates --- browsing damage --- cervids --- gas chromatography --- aboveground --- belowground part of Miscanthus × giganteus --- ash --- potassium --- calcium --- sulphur content --- uptake --- bioproduction --- CAP payments --- sustainable agriculture --- Poland --- unutilized agricultural areas (uUAA) --- abandoned areas --- land use and land-use change --- carbon sequestration --- soil properties (physical and chemical) --- polyphenols --- supercritical CO2 extraction --- perennial industrial crops --- antioxidant activity --- silvergrass --- willowleaf sunflower --- prairie cordgrass --- n/a
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