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A geoinformatics approach to water erosionsoil loss and beyond /

Record Type:	Electronic resources : Monograph/item
Title/Author:	A geoinformatics approach to water erosionby Tal Svoray.
Reminder of title:	soil loss and beyond /
Author:	Svoray, Tal.
Published:	Cham :Springer International Publishing :2022.
Description:	xxii, 349 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Soil erosionRemote sensing.
Online resource:	https://doi.org/10.1007/978-3-030-91536-0
ISBN:	9783030915360$q(electronic bk.)

A geoinformatics approach to water erosionsoil loss and beyond /
Svoray, Tal.

A geoinformatics approach to water erosionsoil loss and beyond /[electronic resource] :by Tal Svoray. - Cham :Springer International Publishing :2022. - xxii, 349 p. :ill. (some col.), digital ;24 cm.

Dedication -- 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.

Degradation 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 agroecosystem's 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 restoration-consequences 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 quantify-in time and space-the 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.

ISBN: 9783030915360$q(electronic bk.)

Standard No.: 10.1007/978-3-030-91536-0doiSubjects--Topical Terms:

924275
Soil erosion
--Remote sensing.

LC Class. No.: S627.R45 / S86 2022

Dewey Class. No.: 631.45

A geoinformatics approach to water erosionsoil loss and beyond /
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505 0 $a Dedication -- 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.
520 $a Degradation 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 agroecosystem's 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 restoration-consequences 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 quantify-in time and space-the 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.
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