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Remote Sensing of Above Ground Biomass

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ISBN: 9783039212095 9783039212101 Year: Pages: 264 DOI: 10.3390/books978-3-03921-210-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-12-09 11:49:15
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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.

Keywords

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

Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers

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ISBN: 9783039212057 9783039212064 Year: Pages: 132 DOI: 10.3390/books978-3-03921-206-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Environmental Sciences
Added to DOAB on : 2019-12-09 16:10:12
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In recent decades, there has been an increase in the development of strategies for water ecosystem mapping and monitoring. Overall, this is primarily due to legislative efforts to improve the quality of water bodies and oceans. Remote sensing has played a key role in the development of such approaches—from the use of drones for vegetation mapping to autonomous vessels for water quality monitoring. Within the specific context of vegetation characterization, the wide range of available observations—from satellite imagery to high-resolution drone aerial imagery—has enabled the development of monitoring and mapping strategies at multiple scales (e.g., micro- and mesoscales). This Special Issue, entitled “Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers”, collates recent advances in remote sensing-based methods applied to ocean, river, and lake vegetation characterization, including seaweed, kelp, submerged and emergent vegetation, and floating-leaf and free-floating plants. A total of six manuscripts have been compiled in this Special Issue, ranging from area mapping substrates in riverine environments to the identification of macroalgae in marine environments. The work presented leverages current state-of-the-art methods for aquatic vegetation monitoring and will spark further research within this field.

Carbon Capture and Storage

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ISBN: 9783039213993 9783039214006 Year: Pages: 178 DOI: 10.3390/books978-3-03921-400-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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Climate change is one of the main threats to modern society. This phenomenon is associated with an increase in greenhouse gas (GHGs, mainly carbon dioxide—CO2) emissions due to anthropogenic activities. The main causes are the burning of fossil fuels and land use change (deforestation). Climate change impacts are associated with risks to basic needs (health, food security, and clean water), as well as risks to development (jobs, economic growth, and the cost of living). The processes involving CO2 capture and storage are gaining attention in the scientific community as an alternative for decreasing CO2 emissions, reducing its concentration in ambient air. The carbon capture and storage (CCS) methodologies comprise three steps: CO2 capture, CO2 transportation, and CO2 storage. Despite the high research activity within this topic, several technological, economic, and environmental issues as well as safety problems remain to be solved, such as the following needs: increase of CO2 capture efficiency, reduction of process costs, and verification of the environmental sustainability of CO2 storage.

Remote Sensing Applications for Agriculture and Crop Modelling

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ISBN: 9783039282265 9783039282272 Year: Pages: 308 DOI: 10.3390/books978-3-03928-227-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2020-04-07 23:07:08
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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,

Keywords

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

Microwave Indices from Active and Passive Sensors for Remote Sensing Applications

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ISBN: 9783038978206 9783038978213 Year: Pages: 224 DOI: 10.3390/books978-3-03897-821-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Geography --- Science (General)
Added to DOAB on : 2019-12-09 11:49:16
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Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices.

The Long-Term Perspective of Human Impact on Landscape for Environmental Change and Sustainability

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ISBN: 9783039217960 9783039217977 Year: Pages: 258 DOI: 10.3390/books978-3-03921-797-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Environmental Sciences
Added to DOAB on : 2019-12-09 11:49:16
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The research studies included in this Special Issue highlight the fundamental contribution of the knowledge of environmental history to conscious and efficient environment conservation and management. The long-term perspective of the dynamics that govern the human–climate ecosystem is becoming one of the main focuses of interest in biological and earth system sciences. Multidisciplinary bio-geo-archaeo investigations into the underlying processes of human impact on the landscape are crucial to envisage possible future scenarios of biosphere responses to global warming and biodiversity losses. This Special Issue seeks to engage an interdisciplinary dialog on the dynamic interactions between nature and society, focusing on long-term environmental data as an essential tool for better-informed landscape management decisions to achieve an equilibrium between conservation and sustainable resource exploitation.

3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function

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ISBN: 9783039217823 9783039217830 Year: Pages: 188 DOI: 10.3390/books978-3-03921-783-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Ecology
Added to DOAB on : 2019-12-09 11:49:16
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Dear Colleagues, The composition, structure and function of forest ecosystems are the key features characterizing their ecological properties, and can thus be crucially shaped and changed by various biotic and abiotic factors on multiple spatial scales. The magnitude and extent of these changes in recent decades calls for enhanced mitigation and adaption measures. Remote sensing data and methods are the main complementary sources of up-to-date synoptic and objective information of forest ecology. Due to the inherent 3D nature of forest ecosystems, the analysis of 3D sources of remote sensing data is considered to be most appropriate for recreating the forest’s compositional, structural and functional dynamics. In this Special Issue of Forests, we published a set of state-of-the-art scientific works including experimental studies, methodological developments and model validations, all dealing with the general topic of 3D remote sensing-assisted applications in forest ecology. We showed applications in forest ecology from a broad collection of method and sensor combinations, including fusion schemes. All in all, the studies and their focuses are as broad as a forest’s ecology or the field of remote sensing and, thus, reflect the very diverse usages and directions toward which future research and practice will be directed.

Drones for Biodiversity Conservation and Ecological Monitoring

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ISBN: 9783039219803 9783039219810 Year: Pages: 176 DOI: 10.3390/books978-3-03921-981-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2020-01-07 09:08:26
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Unmanned aerial vehicles (UAV) have already become an affordable and cost-efficient tool to quickly map a targeted area for many emerging applications in the arena of ecological monitoring and biodiversity conservation. Managers, owners, companies, and scientists are using professional drones equipped with high-resolution visible, multispectral, or thermal cameras to assess the state of ecosystems, the effect of disturbances, or the dynamics and changes within biological communities inter alia. We are now at a tipping point on the use of drones for these type of applications over natural areas. UAV missions are increasing but most of them are testing applicability. It is time now to move to frequent revisiting missions, aiding in the retrieval of important biophysical parameters in ecosystems or mapping species distributions. This Special Issue shows UAV applications contributing to a better understanding of biodiversity and ecosystem status, threats, changes, and trends. It documents the enhancement of knowledge in ecological integrity parameters mapping, long-term ecological monitoring based on drones, mapping of alien species spread and distribution, upscaling ecological variables from drone to satellite images: methods and approaches, rapid risk and disturbance assessment using drones, mapping albedo with UAVs, wildlife tracking, bird colony and chimpanzee nest mapping, habitat mapping and monitoring, and a review on drones for conservation in protected areas.

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Authors: --- ---
ISBN: 9783039212392 9783039212408 Year: Pages: 334 DOI: 10.3390/books978-3-03921-240-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
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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.

Keywords

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

Ten Years of TerraSAR-X—Scientific Results

Authors: --- ---
ISBN: 9783038977247 9783038977254 Year: Pages: 422 DOI: 10.3390/books978-3-03897-725-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-04-25 16:37:17
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This Special Issue is a collection of papers addressing the scientific use of data acquired in the course of the TerraSAR-X mission 10 years after launch. The articles deal with the mission itself, the accuracy of the products, with differential interferometry, and with applications in the domains cryosphere, oceans, wetlands, and urban areas.

Keywords

synthetic aperture radar --- TerraSAR-X --- geolocation --- absolute localization accuracy --- stereo sar --- imaging geodesy --- TerraSAR-X --- internal calibration --- geometric and radiometric calibration --- antenna model verification --- antenna pointing determination --- radiometric accuracy --- calibration targets --- long term performance monitoring --- TerraSAR-X --- TanDEM-X --- LEO --- POD --- SLR --- SAR --- Satellite Laser Ranging --- radar ranging --- satellite orbit --- validation --- InSAR coherence --- NDVI --- damage assessment --- density map --- tsunami --- earthquake --- GIS --- TSX Staring spotlight --- high resolution InSAR --- small-scale movements --- atmospheric phase --- layover --- DSM blending --- SAR --- internal waves --- Andaman Sea --- radar --- satellite --- remote sensing --- SAR --- TerraSAR-X --- operations --- ground segment --- orbit --- mission --- global --- urban footprint --- processing --- validation --- community survey --- sustainability --- synthetic aperture radar --- X-band --- marine --- estuarine --- lacustrine --- riverine --- palustrine --- time-series --- SAR applications --- vegetation --- remote sensing data --- DInSAR --- landslide monitoring --- PSI --- super high-spatial resolution TerraSAR-X images --- pixel selection --- measurement pixels’ density --- synthetic aperture radar --- PolSAR --- TerraSAR-X --- surface water monitoring --- flooded vegetation --- classification --- segmentation --- InSAR --- landslide --- phase unwrapping --- phase demodulation --- TerraSAR-X --- RADARSAT-2 --- ALOS-1 --- ERS --- synthetic aperture radar --- TerraSAR-X --- habitat mapping --- monitoring --- remote sensing --- Wadden Sea --- mussel beds --- intertidal bedforms --- tidal gullies --- remote sensing --- film slicks on the sea surface --- dual co-polarized microwave radar --- surface wind waves --- wave breaking --- Snow Cover Extent (SCE) --- TerraSAR-X --- Landsat --- wet snow --- small Arctic catchments --- satellite time series --- TerraSAR-X --- synthetic aperture radar (SAR), radar mission --- remote sensing --- land subsidence --- TerraSAR-X --- SAR interferometry --- coastal environments --- Venice lagoon --- multi-baseline --- multi-pass --- PS --- DS --- geodetic --- TomoSAR --- D-TomoSAR --- PSI --- robust estimation --- covariance matrix --- InSAR --- SAR --- review --- SAR --- SAR interferometry --- atmospheric propagation delay --- persistent scatterer interferometry --- numerical weather prediction --- stratified atmospheric delay --- zenith path delay --- slant path delay --- interferometry --- surface movement monitoring --- ground control points --- radargrammetry --- automated target recognition --- convolutional neural networks (CNN), deep CNN --- support vector machine --- SVM --- synthetic aperture radar --- TerraSAR-X --- SAR interferometry --- land subsidence --- precise orbit determination --- geometric and radiometric calibration --- PSI

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