This book is a printed edition of the Special Issue "Applications of Remote Sensing/GIS in Water Resources and Flooding Risk Managements" that was published in Water

The wide range of challenges in studying Earth system dynamics due to uncertainties in climate change and complex interference from human activities is creating difficulties in managing land and water resources and ensuring their sustainable use. Mapping, Monitoring, and Modeling Land and Water Resources brings together real-world case studies accurately surveyed and assessed through spatial modeling. The book focuses on the effectiveness of combining remote sensing, geographic information systems, and R. The use of open source software for different spatial modeling cases in various fields, along with the use of remote sensing and geographic information systems, will aid researchers, students, and practitioners to understand better the phenomena and the predictions by future analyses for problem-solving and decision-making.

This book is a collection of overview articles showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. Two main issues are highlighted: (1) the use in combination of space observations for monitoring water storage changes in river basins worldwide, and (2) the use of space data in hydrological modeling either through data assimilation or as external constraints. The water resources aspect is also addressed, as well as the impacts of direct anthropogenic forcing on land hydrology (e.g. ground water depletion, dam building on rivers, crop irrigation, changes in land use and agricultural practices, etc.). Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives.Over the past 15 years, remote sensing techniques have increasingly demonstrated their capability to monitor components of the water balance of large river basins on time scales ranging from months to decades: satellite altimetry routinely monitors water level changes in large rivers, lakes and floodplains. When combined with satellite imagery, this technique can also measure surface water volume variations. Passive and active microwave sensors offer important information on soil moisture (e.g. the SMOS mission) as well as wetlands and snowpack. The GRACE space gravity mission offers, for the first time, the possibility of directly measuring spatio-temporal variations in the total vertically integrated terrestrial water storage. When combined with other space observations (e.g. from satellite altimetry and SMOS) or model estimates of surface waters and soil moisture, space gravity data can effectively measure groundwater storage variations. New satellite missions, planned for the coming years, will complement the constellation of satellites monitoring waters on land. This is particularly the case for the SWOT mission, which is expected to revolutionize land surface hydrology. Previously published in Surveys in Geophysics, Volume 37, No. 2, 2016

Case Studies in Geospatial Applications to Groundwater Resources provides thorough the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, through detailed case studies that prove real-world applications of remote sensing applications to this subject. Groundwater is the primary source of fresh water in many parts of the world, while come regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. India is the largest user of groundwater in the world followed by China and the USA, with developing countries using groundwater at an unsustainable rate. Systematic planning of groundwater usage using modern techniques is essential for the proper utilization, management and modeling of this precious but shrinking natural resource. With the advent of powerful and highspeed personal computers, efficient techniques for water management have evolved, of which remote sensing, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Geostatistical techniques are of great significance. This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. Case Studies in Geospatial Applications to Groundwater Resources is a valuable reference for researchers and postgraduate students in Earth and Environmental Sciences, especially GIS, agriculture, hydrology, natural resources, and soil science, who need to be able to apply the latest technologies in groundwater research in a practical manner. Provides detailed case studies on groundwater resources around the world, including regions with highest groundwater resource use Covers modern remote sensing and geostatistical technique-based groundwater resource mapping, monitoring, and modelling Describes novel region-specific management strategies and techniques for sustainability with case studies to illustrate effectiveness Includes practical coverage of the use of geospatial analysis techniques in groundwater resources

This book contains both practical and theoretical aspects of groundwater resources relating to geochemistry. Focusing on recent research in groundwater resources, this book helps readers to understand the hydrogeochemistry of groundwater resources. Dealing primarily with the sources of ions in groundwater, the book describes geogenic and anthropogenic input of ions into water. Different organic, inorganic and emerging contamination and salinity problems are described, along with pollution-related issues affecting groundwater. New trends in groundwater contamination remediation measures are included, which will be particularly useful to researchers working in the field of water conservation. The book also contains diverse groundwater modelling examples, enabling a better understanding of water-related issues and their management. Groundwater Geochemistry: Pollution and Remediation offers the reader: An understanding of the quantitative and qualitative challenges of groundwater resources An introduction to the environmental geochemistry of groundwater resources A survey of groundwater pollution-related issues Recent trends in groundwater conservation and remediation Mathematical and statistical modeling related to groundwater resources Students, lecturers and researchers working in the fields of hydrogeochemistry, water pollution and groundwater will find Groundwater Geochemistry an essential companion.

Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. - Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography - Provides an overview, methods and case studies for each application - Expresses concepts and methods at an appropriate level for both students and new users to learn by example

The last few years have witnessed an enormous interest in application of GIS in hydrology and water resources. This is partly evidenced by organization of sev eral national and international symposia or conferences under the sponsorship of various professional organizations. This increased interest is, in a large measure, in response to growing public sensitivity to environmental quality and management. The GIS technology has the ability to capture, store, manipulate, analyze, and visualize the diverse sets of geo-referenced data. On the other hand, hydrology is inherently spatial and distributed hydrologic models have large data requirements. The integration of hydrology and GIS is therefore quite natural. The integration involves three major components: (1) spatial data construction, (2) integration of spatial model layers, and (3) GIS and model interface. GIS can assist in design, calibration, modification and comparison of models. This integration is spreading worldwide and is expected to accelerate in the foreseeable future. Substantial op portunities exist in integration of GIS and hydrology. We believe there are enough challenges in use of GIS for conceptualizing and modeling complex hydrologic processes and for globalization of hydrology. The motivation for this book grew out of the desire to provide under one cover a range of applications of GIS tech nology in hydrology. It is hoped that the book will stimulate others to write more comprehensive texts on this subject of growing importance.

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.This book invites readers to explore the many benefits in data mining that decision trees offer: