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Sensors in Agriculture

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ISBN: 9783038974123 / 9783038974130 Year: Pages: 346 DOI: 10.3390/books978-3-03897-413-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Sensors in Agriculture

Author:
ISBN: 9783038977445 / 9783038977452 Year: Pages: 354 DOI: 10.3390/books978-3-03897-745-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Remote Sensing of Precipitation: Volume 1

Author:
ISBN: 9783039212859 / 9783039212866 Year: Pages: 480 DOI: 10.3390/books978-3-03921-286-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-08-28 11:21:27
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Abstract

Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne.

Keywords

GPM --- IMERG --- satellite precipitation adjustment --- numerical weather prediction --- heavy precipitation --- flood-inducing storm --- complex terrain --- precipitation --- geostationary microwave sensors --- polar systems --- synoptic weather types --- drop size distribution (DSD) --- microstructure of rain --- disdrometer --- radar reflectivity–rain rate relationship --- CHIRPS --- CMORPH --- TMPA --- MSWEP --- statistical evaluation --- VIC model --- hydrological simulation --- precipitation --- satellite --- GPM --- TRMM --- CFSR --- PERSIANN --- MSWEP --- streamflow simulation --- lumped models --- Peninsular Spain --- GPM IMERG v5 --- TRMM 3B42 v7 --- precipitation --- evaluation --- Huaihe River basin --- precipitation --- radar --- radiometer --- T-Matrix --- microwave scattering --- quantitative precipitation estimates --- validation --- PERSIANN-CCS --- meteorological radar --- satellite rainfall estimates --- satellite precipitation retrieval --- neural networks --- GPM --- GMI --- remote sensing --- hurricane Harvey --- GPM satellite --- IMERG --- tropical storm rainfall --- gridded radar precipitation --- precipitation --- satellites --- climate models --- regional climate models --- X-band radar --- dual-polarization --- precipitation --- complex terrain --- runoff simulations --- snowfall detection --- snow water path retrieval --- supercooled droplets detection --- GPM Microwave Imager --- Satellite Precipitation Estimates --- GPM --- TRMM --- IMERG --- GSMaP --- TMPA --- CMORPH --- assessment --- Pakistan --- heavy rainfall prediction --- satellite radiance --- data assimilation --- RMAPS --- harmonie model --- radar data assimilation --- pre-processing --- mesoscale precipitation patterns --- GNSS meteorology --- GPS --- Zenith Tropospheric Delay --- precipitable water vapor --- SEID --- single frequency GNSS --- Precise Point Positioning --- low-cost receivers --- goGPS --- GPM --- IMERG --- TRMM --- precipitation --- Cyprus --- satellite precipitation product --- Tianshan Mountains --- GPM --- TRMM --- CMORPH --- heavy precipitation --- rainfall retrieval techniques --- forecast model --- Red–Thai Binh River Basin --- TMPA 3B42V7 --- TMPA 3B42RT --- rainfall --- bias correction --- linear-scaling approach --- climatology --- topography --- precipitation --- remote sensing --- CloudSat --- CMIP --- high latitude --- mineral dust --- wet deposition --- cloud scavenging --- dust washout process --- Saharan dust transportation --- precipitation rate --- precipitating hydrometeor --- hydrometeor classification --- cloud radar --- Ka-band --- thunderstorm --- thundercloud --- vertical air velocity --- terminal velocity --- Milešovka observatory --- rain gauges --- radar --- quality indexes --- satellite rainfall retrievals --- validation --- surface rain intensity --- kriging with external drift --- PEMW --- MSG --- SEVIRI --- downscaling --- tropical cyclone --- rain rate --- precipitation --- remote sensing --- radiometer --- retrieval algorithm --- GPM --- DPR --- validation network --- volume matching --- reflectivity --- rainfall rate --- TRMM-era TMPA --- GPM-era IMERG --- satellite rainfall estimate --- Mainland China --- satellite precipitation --- Global Precipitation Measurement (GPM) --- IMERG --- TRMM-TMPA --- Ensemble Precipitation (EP) algorithm --- topographical and seasonal evaluation --- daily rainfall estimations --- TRMM 3B42 v7 --- rain gauges --- Amazon Basin --- regional rainfall regimes --- regional rainfall sub-regimes --- TRMM 3B42 V7 --- CMORPH_CRT --- PERSIANN_CDR --- GR models --- hydrological simulation --- Red River Basin --- satellite precipitation --- Tibetan Plateau --- GPM --- IMERG --- GSMaP --- precipitation --- weather --- radar --- GPM --- RADOLAN --- QPE --- TRMM --- TMPA --- 3B42 --- validation --- rainfall --- telemetric rain gauge --- Lai Nullah --- Pakistan --- XPOL radar --- GPM/IMERG --- WRF-Hydro --- CHAOS --- hydrometeorology --- flash flood --- Mandra --- typhoon --- IMERG --- GSMaP --- Southern China --- precipitation --- satellite remote sensing --- error analysis --- triple collocation --- precipitation --- TRMM --- GPM --- IMERG --- weather radar --- precipitable water vapor --- precipitation retrieval --- rain rate --- QPE

Remote Sensing of Precipitation: Volume 2

Author:
ISBN: 9783039212873 / 9783039212880 Year: Pages: 318 DOI: 10.3390/books978-3-03921-288-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-08-28 11:21:27
License:

Loading...
Export citation

Choose an application

Abstract

Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne.

Keywords

GPM --- IMERG --- satellite precipitation adjustment --- numerical weather prediction --- heavy precipitation --- flood-inducing storm --- complex terrain --- precipitation --- geostationary microwave sensors --- polar systems --- synoptic weather types --- drop size distribution (DSD) --- microstructure of rain --- disdrometer --- radar reflectivity–rain rate relationship --- CHIRPS --- CMORPH --- TMPA --- MSWEP --- statistical evaluation --- VIC model --- hydrological simulation --- precipitation --- satellite --- GPM --- TRMM --- CFSR --- PERSIANN --- MSWEP --- streamflow simulation --- lumped models --- Peninsular Spain --- GPM IMERG v5 --- TRMM 3B42 v7 --- precipitation --- evaluation --- Huaihe River basin --- precipitation --- radar --- radiometer --- T-Matrix --- microwave scattering --- quantitative precipitation estimates --- validation --- PERSIANN-CCS --- meteorological radar --- satellite rainfall estimates --- satellite precipitation retrieval --- neural networks --- GPM --- GMI --- remote sensing --- hurricane Harvey --- GPM satellite --- IMERG --- tropical storm rainfall --- gridded radar precipitation --- precipitation --- satellites --- climate models --- regional climate models --- X-band radar --- dual-polarization --- precipitation --- complex terrain --- runoff simulations --- snowfall detection --- snow water path retrieval --- supercooled droplets detection --- GPM Microwave Imager --- Satellite Precipitation Estimates --- GPM --- TRMM --- IMERG --- GSMaP --- TMPA --- CMORPH --- assessment --- Pakistan --- heavy rainfall prediction --- satellite radiance --- data assimilation --- RMAPS --- harmonie model --- radar data assimilation --- pre-processing --- mesoscale precipitation patterns --- GNSS meteorology --- GPS --- Zenith Tropospheric Delay --- precipitable water vapor --- SEID --- single frequency GNSS --- Precise Point Positioning --- low-cost receivers --- goGPS --- GPM --- IMERG --- TRMM --- precipitation --- Cyprus --- satellite precipitation product --- Tianshan Mountains --- GPM --- TRMM --- CMORPH --- heavy precipitation --- rainfall retrieval techniques --- forecast model --- Red–Thai Binh River Basin --- TMPA 3B42V7 --- TMPA 3B42RT --- rainfall --- bias correction --- linear-scaling approach --- climatology --- topography --- precipitation --- remote sensing --- CloudSat --- CMIP --- high latitude --- mineral dust --- wet deposition --- cloud scavenging --- dust washout process --- Saharan dust transportation --- precipitation rate --- precipitating hydrometeor --- hydrometeor classification --- cloud radar --- Ka-band --- thunderstorm --- thundercloud --- vertical air velocity --- terminal velocity --- Milešovka observatory --- rain gauges --- radar --- quality indexes --- satellite rainfall retrievals --- validation --- surface rain intensity --- kriging with external drift --- PEMW --- MSG --- SEVIRI --- downscaling --- tropical cyclone --- rain rate --- precipitation --- remote sensing --- radiometer --- retrieval algorithm --- GPM --- DPR --- validation network --- volume matching --- reflectivity --- rainfall rate --- TRMM-era TMPA --- GPM-era IMERG --- satellite rainfall estimate --- Mainland China --- satellite precipitation --- Global Precipitation Measurement (GPM) --- IMERG --- TRMM-TMPA --- Ensemble Precipitation (EP) algorithm --- topographical and seasonal evaluation --- daily rainfall estimations --- TRMM 3B42 v7 --- rain gauges --- Amazon Basin --- regional rainfall regimes --- regional rainfall sub-regimes --- TRMM 3B42 V7 --- CMORPH_CRT --- PERSIANN_CDR --- GR models --- hydrological simulation --- Red River Basin --- satellite precipitation --- Tibetan Plateau --- GPM --- IMERG --- GSMaP --- precipitation --- weather --- radar --- GPM --- RADOLAN --- QPE --- TRMM --- TMPA --- 3B42 --- validation --- rainfall --- telemetric rain gauge --- Lai Nullah --- Pakistan --- XPOL radar --- GPM/IMERG --- WRF-Hydro --- CHAOS --- hydrometeorology --- flash flood --- Mandra --- typhoon --- IMERG --- GSMaP --- Southern China --- precipitation --- satellite remote sensing --- error analysis --- triple collocation --- precipitation --- TRMM --- GPM --- IMERG --- weather radar --- precipitable water vapor --- precipitation retrieval --- rain rate --- QPE

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eng (4)


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2019 (4)