LEADER 05365nam 2200673 a 450 001 9911019878803321 005 20200520144314.0 010 $a9786610560776 010 $a9781280560774 010 $a1280560770 010 $a9783527606443 010 $a3527606440 010 $a9783527602094 010 $a3527602097 035 $a(CKB)1000000000019280 035 $a(EBL)481800 035 $a(OCoLC)77640507 035 $a(SSID)ssj0000183822 035 $a(PQKBManifestationID)11939047 035 $a(PQKBTitleCode)TC0000183822 035 $a(PQKBWorkID)10199238 035 $a(PQKB)10745499 035 $a(MiAaPQ)EBC481800 035 $a(PPN)242642381 035 $a(Perlego)2784412 035 $a(EXLCZ)991000000000019280 100 $a20031022d2003 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe iron oxides $estructure, properties, reactions, occurrences, and uses /$fR.M. Cornell, U. Schwertmann 205 $a2nd, completely rev. and extended ed. 210 $aWeinheim $cWiley-VCH$d2003 215 $a1 online resource (706 p.) 300 $aDescription based upon print version of record. 311 08$a9783527302741 311 08$a3527302743 320 $aIncludes bibliographical references (p. 553-646) and index. 327 $aThe Iron Oxides; Contents; Preface to the Second Edition; Preface to the First Edition; Abbreviations; Colour Plates; 1 Introduction to the iron oxides; 2 Crystal structure; 2.1 General; 2.2 Iron oxide structures; 2.2.1 Close packing of anion layers; 2.2.2 Linkages of octahedra or tetrahedra; 2.3 Structures of the individual iron oxides; 2.3.1 The oxide hydroxides; 2.3.1.1 Goethite ?-FeOOH; 2.3.1.2 Lepidocrocite ?-FeO(OH); 2.3.1.3 Akagane?ite ?-FeO(OH) and schwertmannite Fe(16)O(16) (OH)(y)(SO(4))(z) ·n H(2)O; 2.3.1.4 ?-FeOOH and ? ?-FeOOH (feroxyhyte); 2.3.1.5 High pressure FeOOH 327 $a2.3.1.6 Ferrihydrite2.3.2 The Hydroxides; 2.3.2.1 Bernalite Fe(OH)(3) · nH(2)O; 2.3.2.2 Fe(OH)(2); 2.3.2.3 Green rusts; 2.3.3 The Oxides; 2.3.3.1 Hematite ?-Fe(2)O(3); 2.3.3.2 ?-Fe(2)O(3); 2.3.3.3 Magnetite Fe(3)O(4); 2.3.3.4 Maghemite ?-Fe(2)O(3); 2.3.3.5 Wu?stite Fe(1-x)O; 2.4 The Fe-Ti oxide system; Appendix; 3 Cation substitution; 3.1 General; 3.2 Goethite and lepidocrocite; 3.2.1 Al substitution; 3.2.2 Other substituting cations; 3.3 Hematite; 3.3.1 Al substitution; 3.3.2 Other cations; 3.4 Magnetite and maghemite; 3.5 Other Iron oxides; 4 Crystal morphology and size; 4.1 General 327 $a4.1.1 Crystal growth4.1.2 Crystal morphology; 4.1.3 Crystal size; 4.2 The iron oxides; 4.2.1 Goethite; 4.2.1.1 General; 4.2.1.2 Domainic character; 4.2.1.3 Twinning; 4.2.1.4 Effect of additives; 4.2.2 Lepidocrocite; 4.2.3 Akagane?ite and schwertmannite; 4.2.4 Ferrihydrite; 4.2.5 Hematite; 4.2.6 Magnetite; 4.2.7 Maghemite; 4.2.8 Other Iron Oxides; 5 Surface area and porosity; 5.1 Surface Area; 5.2 Porosity; 5.3 Surface Roughness and Fractal Dimensions; 5.4 The iron oxides; 5.4.1 Goethite; 5.4.2 Lepidocrocite; 5.4.3 Akagane?ite and schwertmannite; 5.4.4 ?-FeOOH and feroxyhyte; 5.4.5 Ferrihydrite 327 $a5.4.6 Hematite5.4.7 Magnetite; 5.4.8 Maghemite; 6 Electronic, electrical and magnetic properties and colour; 6.1 Electronic properties; 6.1.1 Free Fe(3+) and Fe(2+) ions; 6.1.2 Bound Fe ions; 6.1.3 Molecular orbital description of bonding in iron oxides; 6.2 Electrical properties; 6.2.1 Semiconductor properties of iron oxides; 6.3 Magnetic properties; 6.3.1 Basic definitions; 6.3.2 Types of magnetism (Fig. 6.5); 6.3.3 Magnetic behaviour of iron oxides; 6.3.4 The different iron oxides; 6.3.4.1 Goethite; 6.3.4.2 Lepidocrocite; 6.3.4.3 Akagane?ite 327 $a6.3.4.4 ?-FeOOH, feroxyhyte and high pressure FeOOH6.3.4.5 Ferrihydrite; 6.3.4.6 Hematite; 6.3.4.7 Magnetite and Maghemite; 6.3.4.8 Other Fe oxides; 6.4 Colour; 6.4.1 General; 6.4.2 Colours; 6.4.3 Pigment properties; 7 Characterization; 7.1 Introduction; 7.2 Infrared spectroscopy; 7.2.1 Goethite; 7.2.2 Lepidocrocite; 7.2.3 Ferrihydrite; 7.2.4 Hematite; 7.2.5 Other iron oxides; 7.3 Raman spectroscopy; 7.4 Ultraviolet-visible spectroscopy; 7.4.1 General; 7.4.2 Spectra of the different Fe oxides; 7.5 Mo?ssbauer spectroscopy; 7.5.1 General; 7.5.2 Spectra of the various Fe oxides 327 $a7.5.2.1 Goethite and Lepidocrocite 330 $aThis book brings together in one, compact volume all aspects of the available information about the iron oxides. It presents a coherent, up to date account of the properties, reactions and mechanisms of formation of these compounds. In addition, there are chapters dealing with iron oxides in rocks and soils, as biominerals and as corrosion products together with methods of synthesis and the numerous application of these compounds. Their role in the environment is also discussed. The authors are experts in the field of iron oxides and have worked on all the topics covered. Much recent data from 606 $aIron oxides 615 0$aIron oxides. 676 $a546/.6212 700 $aCornell$b R. M$01840517 701 $aSchwertmann$b Udo$0439418 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019878803321 996 $aThe iron oxides$94420085 997 $aUNINA LEADER 05610nam 22007334a 450 001 9911020444203321 005 20200520144314.0 010 $a9786610252916 010 $a9781280252914 010 $a128025291X 010 $a9780470348000 010 $a0470348003 010 $a9780471723714 010 $a0471723711 010 $a9780471723721 010 $a047172372X 035 $a(CKB)1000000000018988 035 $a(EBL)226562 035 $a(SSID)ssj0000231226 035 $a(PQKBManifestationID)11204243 035 $a(PQKBTitleCode)TC0000231226 035 $a(PQKBWorkID)10206968 035 $a(PQKB)10629975 035 $a(MiAaPQ)EBC226562 035 $a(OCoLC)85820318 035 $a(Perlego)2773891 035 $a(EXLCZ)991000000000018988 100 $a20021209d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aQuantitative remote sensing of land surfaces /$fShunlin Liang 210 $aHoboken, N.J. $cWiley-Interscience$dc2004 215 $a1 online resource (562 p.) 225 1 $aWiley series in remote sensing 300 $aDescription based upon print version of record. 311 1 $a9780471281665 311 1 $a0471281662 320 $aIncludes bibliographical references and index. 327 $aQUANTITATIVE REMOTE SENSING OF LAND SURFACES; Contents; Preface; Acronyms; CHAPTER 1 Introduction; 1.1 Quantitative Models in Optical Remote Sensing; 1.2 Basic Concepts; 1.2.1 Digital Numbers; 1.2.2 Radiance; 1.2.3 Solid Angle; 1.2.4 lrradiance; 1.2.5 Bidirectional Reflectances and Albedos; 1.2.6 Extraterrestrial Solar lrradiance; 1.3 Remote Sensing Modeling System; 1.3.1 Scene Generation; 1.3.2 Scene Radiation Modeling; 1.3.3 Atmospheric Radiative Transfer Modeling; 1.3.4 Navigation Modeling; 1.3.5 Sensor Modeling; 1.3.5.1 Spectral Response; 1.3.5.2 Spatial Response 327 $a1.3.6 Mapping and Binning1.4 Summary; References; CHAPTER 2 Atmospheric Shortwave Radiative Transfer Modeling; 2.1 Radiative Transfer Equation .; 2.2 Surface Statistical BRDF Models; 2.2.1 Minnaert Function; 2.2.2 Lommel-Seeliger Function; 2.2.3 Walthall Function; 2.2.4 Staylor-Suttles Function; 2.2.5 Rahman Function; 2.2.6 Kernel Functions; 2.3 Atmospheric Optical Properties; 2.3.1 Rayleigh Scattering; 2.3.2 Mie Scattering; 2.3.3 Aerosol Particle Size Distributions; 2.3.4 Gas Absorption; 2.3.5 Aerosol Climatology; 2.4 Solving Radiative Transfer Equations; 2.4.1 Radiation Field Decomposition 327 $a2.4.2 Numerical Solutions2.4.2.1 Method of Successive Orders of Scattering; 2.4.2.2 Method of Discrete Ordinates; 2.4.3 Approximate Solutions: Two-Stream Algorithms; 2.4.4 Representative Radiative Transfer Solvers (Software Packages); 2.5 Approximate Representation for Incorporating Surface BRDF; 2.6 Summary; References; CHAPTER 3 Canopy Reflectance Modeling; 3.1 Canopy Radiative Transfer Formulation; 3.1.1 Canopy Configuration; 3.1.2 One-Dimensional Radiative Transfer Formulation; 3.1.3 Boundary Conditions; 3.1.4 Hotspot Effects; 3.1.5 Formulations for Heterogeneous Canopies 327 $a3.2 Leaf Optical Models3.2.1 "Plate" Models; 3.2.2 Needleleaf Models; 3.2.3 Ray Tracing Models; 3.2.4 Stochastic Models; 3.2.5 Turbid Medium Models; 3.3 Solving Radiative Transfer Equations; 3.3.1 Approximate Solutions; 3.3.1.1 Models Based on KM Theory; 3.3.1.2 Decomposition of the Canopy Radiation Field; 3.3.1.3 Approximation of Multiple Scattering; 3.3.2 Numerical Solutions: Gauss-Seidel Algorithm; 3.4 Geometric Optical Models; 3.5 Computer Simulation Models; 3.5.1 Monte Carlo Ray Tracing Models; 3.5.1.1 Forward and Reverse Ray Tracing; 3.5.1.2 Canopy Scene Generation 327 $a3.5.1.3 A Forest Ray Tracing Algorithm3.5.1.4 Botanical Plant Modeling System Model; 3.5.1.5 SPRINT Model; 3.5.2 Radiosity Models; 3.5.2.1 Generating the 3D Scene; 3.5.2.2 Calculating the Emission for All Surfaces in the Scene; 3.5.2.3 Computing the View Factors; 3.5.2.4 Solving the Radiosity Equation; 3.5.2.5 Rendering the Scene for a Given Viewpoint and Calculating BRF; 3.5.2.6 Applications; 3.6 Summary; References; CHAPTER 4 Soil and Snow Reflectance Modeling; 4.1 Single Scattering Properties of Snow and Soil; 4.1.1 Optical Properties of Snow; 4.1.2 Optical Properties of Soils 327 $a4.2 Multiple Scattering Solutions for Angular Reflectance from Snow and Soil 330 $aProcessing the vast amounts of data on the Earth's land surface environment generated by NASA's and other international satellite programs is a significant challenge. Filling a gap between the theoretical, physically-based modelling and specific applications, this in-depth study presents practical quantitative algorithms for estimating various land surface variables from remotely sensed observations.A concise review of the basic principles of optical remote sensing as well as practical algorithms for estimating land surface variables quantitatively from remotely sensed observations.Emp 410 0$aWiley series in remote sensing. 606 $aEarth sciences$xRemote sensing 606 $aEnvironmental sciences$xRemote sensing 606 $aRemote sensing 615 0$aEarth sciences$xRemote sensing. 615 0$aEnvironmental sciences$xRemote sensing. 615 0$aRemote sensing. 676 $a550/.28/7 700 $aLiang$b Shunlin$0311491 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911020444203321 996 $aQuantitative remote sensing of land surfaces$9810627 997 $aUNINA LEADER 04338nam 22007095 450 001 9910623995303321 005 20251009073519.0 010 $a9789811955549 010 $a9811955549 024 7 $a10.1007/978-981-19-5554-9 035 $a(CKB)5580000000418717 035 $a(DE-He213)978-981-19-5554-9 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/93926 035 $a(MiAaPQ)EBC7127673 035 $a(Au-PeEL)EBL7127673 035 $a(OCoLC)1351751945 035 $a(ODN)ODN0010067820 035 $a(oapen)doab97667 035 $a(EXLCZ)995580000000418717 100 $a20221029d2023 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData for Social Good $eNon-Profit Sector Data Projects /$fby Jane Farmer, Anthony McCosker, Kath Albury, Amir Aryani 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Palgrave Macmillan,$d2023. 215 $a1 online resource (XV, 127 p. 7 illus.) 311 08$a9789811955532 311 08$a9811955530 327 $aChapter 1 Introduction -- Chapter 2 Case Studies of Data Projects -- Chapter 3 Data Capability Through Collaborative Data Action -- Chapter 4 Activating for a Data-Capable Future. . 330 $a"Data collaboration is critical to closing societal gaps in data access and capabilities. Ironically, there is little evidence available about impactful data collaboratives, especially involving non-profits, making their data use challenging. This book fills a void by providing a unique understanding of the variables that matter. Anyone interested in using data for social good should read this book." ?Stefaan Verhulst, Co-Founder of The Govlab, New York University and Editor-in-Chief of Data & Policy ?The non-profit needs to build data capability so it continues to develop innovative services and report on high impact outcomes. Through practical examples and advice from data projects, this open access book will help make this happen.? ?Dr Catherine Brown OAM, CEO, Lord Mayors Charitable Foundation, Melbourne, Australia This open access book provides practical guidance for non-profits and community sector organisations about how to get started with data analytics projects using their own organisations? datasets and open public data. The book shares best practices on collaborative social data projects and methodology. For researchers, the work offers a playbook for partnering with community organisations in data projects for public good and gives worked examples of projects of various sizes and complexity. Jane Farmer is Director of the Social Innovation Research Institute at Swinburne University of Technology, Melbourne. Anthony McCosker is Deputy Director of the Social Innovation Research Institute at Swinburne University of Technology, Melbourne. Kath Albury is co-Leader of the Digital Inclusion Program at Swinburne University of Technology Social Innovation Research Institute. Amir Aryani leads the Social Data Analytics Lab at Swinburne University of Technology, Melbourne. 606 $aSocial policy 606 $aScience$xSocial aspects 606 $aPolitical planning 606 $aCommunication 606 $aSocial Policy 606 $aScience and Technology Studies 606 $aPublic Policy 606 $aMedia and Communication 615 0$aSocial policy. 615 0$aScience$xSocial aspects. 615 0$aPolitical planning. 615 0$aCommunication. 615 14$aSocial Policy. 615 24$aScience and Technology Studies. 615 24$aPublic Policy. 615 24$aMedia and Communication. 676 $a361.61 686 $aPOL028000$aPOL029000$aSOC025000$aSOC026000$2bisacsh 700 $aFarmer$b Jane$4aut$4http://id.loc.gov/vocabulary/relators/aut$01271810 702 $aMcCosker$b Anthony$f1974-$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aAlbury$b Kath$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aAryani$b Amir$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910623995303321 996 $aData for Social Good$92995992 997 $aUNINA