001444572 000__ 05271cam\a2200577Ii\4500
001444572 001__ 1444572
001444572 003__ OCoLC
001444572 005__ 20230310003717.0
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001444572 008__ 220220s2022\\\\sz\a\\\\ob\\\\001\0\eng\d
001444572 019__ $$a1298559182$$a1299385782
001444572 020__ $$a9783030915360$$q(electronic bk.)
001444572 020__ $$a3030915360$$q(electronic bk.)
001444572 020__ $$z9783030915353
001444572 020__ $$z3030915352
001444572 0247_ $$a10.1007/978-3-030-91536-0$$2doi
001444572 035__ $$aSP(OCoLC)1298513718
001444572 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dEBLCP$$dGW5XE$$dOCLCO$$dOCLCF$$dUKAHL$$dOCLCQ$$dWAU
001444572 049__ $$aISEA
001444572 050_4 $$aS627.R45$$bS86 2022
001444572 08204 $$a631.4/5$$223
001444572 1001_ $$aSvoray, Tal,$$eauthor.
001444572 24512 $$aA geoinformatics approach to water erosion :$$bsoil loss and beyond /$$cTal Svoray.
001444572 264_1 $$aCham :$$bSpringer,$$c[2022]
001444572 264_4 $$c©2022
001444572 300__ $$a1 online resource (xxii, 349 pages) :$$billustrations (some color)
001444572 336__ $$atext$$btxt$$2rdacontent
001444572 337__ $$acomputer$$bc$$2rdamedia
001444572 338__ $$aonline resource$$bcr$$2rdacarrier
001444572 504__ $$aIncludes bibliographical references and index.
001444572 5050_ $$aDedication -- Preface -- Acknowledgement -- 1. Soil erosion: The general problem -- 1.1 The soil, and its erosion -- 1.2 Scope of soil erosion -- 1.3 A brief history of soil loss -- 1.4 Soil as a finite resource -- 1.5 Summary -- 2 The case of agricultural catchments -- 2.1 Erosion factors in a distinct landform -- 2.2 On-site and off-site consequences -- 2.3 The human agent -- 2.4 Summary -- 3 The physical process -- 3.1 The basics of hillslope erosion -- 3.2 Water Erosion Prediction Project (WEPP) -- 3.3 CAESAR-Lisflood a landscape evolution model -- 3.4 Morgan-Morgan-Finney (MMF) -- 3.5 Summary -- 4 Spatial variation in the catchment -- 4.1 Discrete spatial units -- 4.2 A suite of continuous variables -- 4.3 Summary -- 5 Earth-based observations -- 5.1 Spectral indices: spectral signatures and mathematical expressions -- 5.2 Classification -- 5.3 Synergy of RS data in catchment models -- 5.4 Close range analysis -- 5.5 Summary -- 6 Predicting erosion risk: from expert knowledge to data mining -- 6.1 The Topographic Threshold -- 6.2 Expert-based systems -- 6.3 The data-mining approach -- 6.4 Fuzzy logic -- 6.5 Summary -- 7 Health of the remaining soil -- 7.1 The soil health index -- 7.2 Statistical analysis and pre-processing -- 7.3 Mapping soil health -- 7.4 Summary -- 8 Decision-making -- 8.1 Decision-making in soil conservation -- 8.2 The simple expert system -- 8.3 GISCAME -- 8.4 Summary -- References -- Index -- Nomenclature.
001444572 506__ $$aAccess limited to authorized users.
001444572 520__ $$aDegradation of agricultural catchments due to water erosion is a major environmental threat at the global scale, with long-lasting destructive consequences valued at tens of billions of dollars per annum. Eroded soils lead to reduced crop yields and deprived agroecosystems functioning through, for example, decreased water holding capacity, poor aeration, scarce microbial activity, and loose soil structure. This can result in reduced carbon sequestration, limited nutrient cycling, contamination of water bodies due to eutrophication, low protection from floods and poor attention restorationconsequences that go far beyond the commonly modelled soil loss and deposition budgets. This book demonstrates, using data from the Harod catchment in northern Israel, how cutting-edge geoinformatics, data science methodologies and soil health indicators can be used to measure, predict, and regulate these major environmental hazards. It shows how these approaches are used to quantifyin time and spacethe effect of water erosion not only on the soil layer, soil minerals, and soil loss, but also on the wide-range of services that agricultural ecosystems might supply for the benefit and well-being of humans. The algorithms described in this book play a major role in this paradigm shift and they include, for example, extraction of photogrammetric DEMs from drone's data, advanced drainage structure calculations, fuzzy process-based modelling and spatial topographic threshold computations, multicriteria analyses and expert-based systems development using analytic hierarchal processes, innovative data-mining and machine learning tools, autocorrelation and interpolation of soil health, physically-based soil evolution models, spatial decision support systems and many more.
001444572 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 1, 2022).
001444572 650_0 $$aSoil erosion$$xRemote sensing.
001444572 650_0 $$aSoil erosion prediction.
001444572 650_0 $$aSoil conservation.
001444572 650_0 $$aGeographic information systems.
001444572 650_6 $$aSols$$xÉrosion$$xTélédétection.
001444572 650_6 $$aSols$$xÉrosion$$xPrévision.
001444572 650_6 $$aSols$$xConservation.
001444572 650_6 $$aSystèmes d'information géographique.
001444572 655_0 $$aElectronic books.
001444572 77608 $$iPrint version: $$z3030915352$$z9783030915353$$w(OCoLC)1280277927
001444572 852__ $$bebk
001444572 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-91536-0$$zOnline Access$$91397441.1
001444572 909CO $$ooai:library.usi.edu:1444572$$pGLOBAL_SET
001444572 980__ $$aBIB
001444572 980__ $$aEBOOK
001444572 982__ $$aEbook
001444572 983__ $$aOnline
001444572 994__ $$a92$$bISE