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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.
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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Irrigation is becoming an activity of precision, where combining information collected from various sources is necessary to optimally manage resources. New management strategies, such as big data techniques, sensors, artificial intelligence, unmanned aerial vehicles (UAV), and new technologies in general, are becoming more relevant every day. As such, modeling techniques, both at the water distribution network and the farm levels, will be essential to gather information from various sources and offer useful recommendations for decision-making processes. In this book, 10 high quality papers were selected that cover a wide range of issues that are relevant to the different aspects related to irrigation management: water source and distribution network, plot irrigation systems, and crop water management.
lined irrigation open-canal --- unmeasured discharges estimation --- hydraulic modelling --- irrigation DSS --- actual evapotranspiration (ETA) --- Calathea --- container-grown plants --- daily water requirements --- ornamental foliage plants --- Stromanthe --- water need index (WNI) --- water resources management --- Aswan High Dam --- weed algorithm --- irrigation demands --- hydropower --- irrigation networks --- combinatorial analysis --- statistical analysis --- pump-as-turbine --- payback period --- irrigation network --- energy consumption --- variable speed --- well --- water depth --- summer maize --- drip irrigation --- evapotranspiration --- crop transpiration --- the stable carbon isotope technique --- rotator spray sprinkler --- low-pressure --- ballistic simulation --- modified drag model --- energy losses --- modelling --- AquaCrop --- calibration --- sugar beet --- irrigation water allocation --- water productivity --- hydraulic model --- variable topography --- energy consumption --- variable speed --- center pivot system --- reclaimed water --- fertigation scheduling --- precision irrigation --- olive orchard --- water-energy nexus --- decision support systems --- soil-water-plant-atmosphere models --- optimization
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Human needs like food and clean water are directly related to good maintenance of healthy and productive soils. A good understanding of human impact on the natural environment is therefore necessary to preserve and manage soil and water resources. This knowledge is particularly important in semi-arid and arid regions, where the increasing demands on limited water supplies require urgent efforts to improve water quality and water use efficiency. It is important to keep in mind that both soil and water are limited resources. Thus, wise use of these natural resources is a fundamental prerequisite for the sustainability of human societies. This book collects 15 original scientific contributions addressing the state of the art of soil and water conservation research. Contributions cover a wide range of topics, including (1) recovery of soil hydraulic properties; (2) erosion risk; (3) novel modeling, monitoring and experimental approaches for soil hydraulic characterization; (4) improvement of crop yields; (5) water availability; and (6) soil salinity. This collection provides more insights into conservation strategies for effective and sustainable soil and water management.
soil moisture storage --- van Genuchten model --- distributed model --- Xin’anjiang model --- TOPMODEL --- bimsoils --- critical hydraulic gradient (CHG) --- response surface methodology --- multi-parameter evaluation --- laboratory experiment --- soil block --- subsurface flow --- macropore network --- spatial scale --- polyurethane foam --- hillslope --- soil water content --- field observation --- three-dimensional model --- numerical model --- delta plain --- shallow groundwater --- unsaturated soil --- Richards equation --- the Trefftz method --- transient --- the meshless method --- vineyards --- infiltration rate --- age of planting --- saturated hydraulic conductivity --- Malawi --- conservation agriculture --- peer effects --- decision tree modeling --- olive grove --- sap flow --- relative transpiration --- FDR sensor --- EM38 --- fraction transpiration soil water --- transdisciplinary research --- Follow-the-Innovation --- innovation development --- electromagnetic induction meter (EM) --- The Agricultural Production Systems sIMulator (APSIM) software --- AquaCrop --- cereals --- DSSAT --- field scattering --- food security --- microdose fertilization --- rainfall variability --- tied ridges --- upgrading strategies --- soil properties --- saturated soil hydraulic conductivity --- soil infiltration --- Beerkan method --- post-fire soil hydraulic characterization --- infiltration --- bottomless bucket method --- single-ring infiltrometer --- field-saturated soil hydraulic conductivity --- data analysis procedures --- environmental change --- local perception --- food security --- adaptation --- soil tillage --- tillage erosion --- seedbed preparation --- water infiltration --- nitrogen use efficiency --- specific leaf water content --- vegetable production --- soil --- yield --- water and soil conservation --- sustainable land management --- soil erosion --- soil water storage --- water infiltration --- water availability --- crop yields
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Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling,
crop residue management --- remote sensing --- satellite images --- hyperspectral sensor --- vegetation index --- yield monitoring --- remote sensing --- proximal sensing --- crop modeling --- soil --- plant --- management zone --- spatial variability --- temporal variability --- precision agriculture --- Á Trous algorithm --- conservation agriculture --- crop inventory --- remote sensing --- spectral-weight variations in fused images --- soil stoichiometry --- land use change --- soil organic carbon --- nitrogen --- Tarim Basin --- SPAD --- leaf nitrogen concentration --- nitrogen nutrition index --- grain yield --- dynamic model --- wheat --- disease --- yield --- septoria tritici blotch --- leaf area index --- crop modelling --- decision support system for agrotechnology transfer (DSSAT) --- Cropsim-CERES Wheat --- sorghum biomass --- prediction modeling --- machine learning --- fAPAR --- Sentinel-2 satellite imagery --- big data technology --- remote sensing --- UAV --- vegetation indices --- relative frequencies --- yield --- precision agriculture --- cultivars --- crop growth model --- data assimilation --- Leaf Area Index --- Sentinel-2 --- EPIC model --- yield estimation --- NDVI --- remote sensing --- GIS --- precision farming --- variable rate technology --- yield mapping --- protein content --- wheat --- canopy temperature depression --- NDVI --- RGB images --- grain yield --- ?13C --- UAV chemical application --- droplet drift --- flat-fan atomizer --- simulation analysis --- control variables --- agricultural land-cover --- multi-spectral --- generalized model --- machine learning --- crop type mapping --- Integrated Administration and Control System --- remote sensing --- hydroponic --- vegetable monitoring --- crop production --- spectral simulation --- hyperspectral data --- n/a --- fractional cover --- irrigation --- satellite --- crop simulation model --- AquaCrop --- yield mapping --- remote sensing --- durum wheat --- precision agriculture --- large cardamom --- remote sensing --- species modelling --- habitat assessment --- climate change
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