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024 7 $a10.1007/978-3-319-69539-6
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035   $a(DE-He213)978-3-319-69539-6
035   $a(MiAaPQ)EBC5576616
035   $a(Au-PeEL)EBL5576616
035   $a(OCoLC)1066181330
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/44149
035   $a(PPN)226698351
035   $a(EXLCZ)994100000003359206
100   $a20180405d2018      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 10$aCosmic Ray Neutron Sensing:  Estimation of Agricultural Crop Biomass Water Equivalent$b[electronic resource] /$fby Ammar Wahbi, Lee Heng, Gerd Dercon
205   $a1st ed. 2018.
210   $cSpringer Nature$d2018
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (X, 33 p. 18 illus., 14 illus. in color.) 
311   $a3-319-69538-X 
327   $aForeword -- Summary -- 2. In-Situ Destructive Sampling -- 2.1 The Concept of Representivity -- 2.2 Plant Sampling Pattern and Design -- 2.3 Biomass Water Equivalent -- 2.4 Conclusions -- 3. Remote Sensing via Satellite Imagery Analysis -- 3.1 Photo-Reflective Properties of Plants -- 3.2 Satellite Image Analysis -- 3.3 Conclusions -- 4. Estimate of Biomass Water Equivalent via the Cosmic Ray Neutron Sensor -- 4.1 The role of Biomass in the CRNS Calibration -- 4.2 Relationship between Neutrons and Crop Biomass -- 4.3 Dire4ct Relationship between Neutrons and Biomass -- 4.4 Conclusions.
330   $aThis book is published open access under a CC BY 3.0 IGO license. This open access book provides methods for the estimation of Biomass Water Equivalent (BEW), an essential step for improving the accuracy of area-wide soil moisture by cosmic-ray neutron sensors (CRNS). Three techniques are explained in detail: (i) traditional in-situ destructive sampling, (ii) satellite based remote sensing of plant surfaces, and (iii) biomass estimation via the use of the CRNS itself. The advantages and disadvantages of each method are discussed along with step by step instructions on proper procedures and implementation. .
606   $aAgriculture
606   $aHydrology
606   $aEnvironmental sciences
606   $aAgriculture$3https://scigraph.springernature.com/ontologies/product-market-codes/L11006
606   $aHydrology/Water Resources$3https://scigraph.springernature.com/ontologies/product-market-codes/211000
606   $aEnvironmental Science and Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/G37000
610   $aEarth Science
610   $aNuclear
610   $aBiomass Water Equivalent
610   $aSatellite Imagery
610   $aRemote Sensing
610   $aCRNS
610   $aWater Management
610   $aCrop Nutrition
610   $aSoil Management
615  0$aAgriculture.
615  0$aHydrology.
615  0$aEnvironmental sciences.
615 14$aAgriculture.
615 24$aHydrology/Water Resources.
615 24$aEnvironmental Science and Engineering.
676   $a630
700   $aWahbi$b Ammar$4aut$4http://id.loc.gov/vocabulary/relators/aut$0989233
702   $aHeng$b Lee$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aDercon$b Gerd$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
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906   $aBOOK
912   $a9910293140603321
996   $aCosmic Ray Neutron Sensing: Estimation of Agricultural Crop Biomass Water Equivalent$92262364
997   $aUNINA