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This book advances the scientific understanding, development, and
application of geospatial technologies related to water resource
management. It presents recent developments and applications
specifically by utilizing new earth observation datasets such as
TRMM/GPM, AMSR E/2, SMOS, SMAP and GCOM in combination with GIS,
artificial intelligence, and hybrid techniques. By linking
geospatial techniques with new satellite missions for earth and
environmental science, the book promotes the synergistic and
multidisciplinary activities of scientists and users working in the
field of hydrological sciences.
Remote Sensing in Precision Agriculture: Transforming Scientific
Advancement into Innovation compiles the latest applications of
remote sensing in agriculture using spaceborne, airborne and
drones’ geospatial data. The book presents case studies, new
algorithms and the latest methods surrounding crop sown area
estimation, determining crop health status, assessment of
vegetation dynamics, crop diseases identification, crop yield
estimation, soil properties, drone image analysis for crop damage
assessment, and other issues in precision agriculture. This book is
ideal for those seeking to explore and implement remote sensing in
an effective and efficient manner with its compendium of
scientifically and technologically sound information.
GPS and GNSS Technology in Geosciences offers an interdisciplinary
approach to applying advances in GPS/GNSS technology for geoscience
research and practice. As GPS/GNSS signals can be used to provide
useful information about the Earth's surface characteristics and
land surface composition, GPS equipment and services for commercial
purposes continues to grow, thus resulting in new expectations and
demands. This book provides case studies for a deeper understanding
of the operation and principles of widely applied approaches and
the benefits of the technology in everyday research and activities.
Computational intelligence techniques have enjoyed growing interest
in recent decades among the earth and environmental science
research communities for their powerful ability to solve and
understand various complex problems and develop novel approaches
toward a sustainable earth. This book compiles a collection of
recent developments and rigorous applications of computational
intelligence in these disciplines. Techniques covered include
artificial neural networks, support vector machines, fuzzy logic,
decision-making algorithms, supervised and unsupervised
classification algorithms, probabilistic computing, hybrid methods
and morphic computing. Further topics given treatment in this
volume include remote sensing, meteorology, atmospheric and oceanic
modeling, climate change, environmental engineering and management,
catastrophic natural hazards, air and environmental pollution and
water quality. By linking computational intelligence techniques
with earth and environmental science oriented problems, this book
promotes synergistic activities among scientists and technicians
working in areas such as data mining and machine learning. We
believe that a diverse group of academics, scientists,
environmentalists, meteorologists and computing experts with a
common interest in computational intelligence techniques within the
earth and environmental sciences will find this book to be of great
value.
Remote Sensing Applications in Environmental Research is the basis
for advanced Earth Observation (EO) datasets used in environmental
monitoring and research. Now that there are a number of satellites
in orbit, EO has become imperative in today's sciences, weather and
natural disaster prediction. This highly interdisciplinary
reference work brings together diverse studies on remote sensing
and GIS, from a theoretical background to its applications,
represented through various case studies and the findings of new
models. The book offers a comprehensive range of contributions by
well-known scientists from around the world and opens a new window
for students in presenting interdisciplinary and methodological
resources on the latest research. It explores various key aspects
and offers state-of-the-art research in a simplified form,
describing remote sensing and GIS studies for those who are new to
the field, as well as for established researchers.
"Remote Sensing Applications in Environmental Research "is the
basis for advanced Earth Observation (EO) datasets used in
environmental monitoring and research. Now that there are a number
of satellites in orbit, EO has become imperative in today s
sciences, weather and natural disaster prediction. This highly
interdisciplinary reference work brings together diverse studies on
remote sensing and GIS, from a theoretical background to its
applications, represented through various case studies and the
findings of new models. The book offers a comprehensive range of
contributions by well-known scientists from around the world and
opens a new window for students in presenting interdisciplinary and
methodological resources on the latest research. It explores
various key aspects and offers state-of-the-art research in a
simplified form, describing remote sensing and GIS studies for
those who are new to the field, as well as for established
researchers."
Computational intelligence techniques have enjoyed growing interest
in recent decades among the earth and environmental science
research communities for their powerful ability to solve and
understand various complex problems and develop novel approaches
toward a sustainable earth. This book compiles a collection of
recent developments and rigorous applications of computational
intelligence in these disciplines. Techniques covered include
artificial neural networks, support vector machines, fuzzy logic,
decision-making algorithms, supervised and unsupervised
classification algorithms, probabilistic computing, hybrid methods
and morphic computing. Further topics given treatment in this
volume include remote sensing, meteorology, atmospheric and oceanic
modeling, climate change, environmental engineering and management,
catastrophic natural hazards, air and environmental pollution and
water quality. By linking computational intelligence techniques
with earth and environmental science oriented problems, this book
promotes synergistic activities among scientists and technicians
working in areas such as data mining and machine learning. We
believe that a diverse group of academics, scientists,
environmentalists, meteorologists and computing experts with a
common interest in computational intelligence techniques within the
earth and environmental sciences will find this book to be of great
value.
Earth Observation in Urban Monitoring: Techniques and Challenges
presents the latest techniques of remote sensing in urban
monitoring, along with methods for quantitative and qualitative
assessment using state-of-the-art Earth observation technologies.
The book details the advances of remote sensing technologies in
urban environmental monitoring for a range of practical and
research applications, Earth observation datasets, remote sensing
of environmental considerations, geostatistical techniques and
resilience perspectives. Chapters cover sensor applications, urban
growth modelling, SAR applications, surveying techniques, satellite
time series analysis and a variety of other remote sensing
technologies for urban monitoring. Each chapter includes detailed
case studies at a variety of scales and from a variety of
geographies, offering up-to-date, global, urban monitoring
methodologies for researchers, scientists and academics in remote
sensing, geospatial research, environmental science and
sustainability.
Hyperspectral Remote Sensing: Theory and Applications offers the
latest information on the techniques, advances and wide-ranging
applications of hyperspectral remote sensing, such as forestry,
agriculture, water resources, soil and geology, among others. The
book also presents hyperspectral data integration with other
sources, such as LiDAR, Multi-spectral data, and other remote
sensing techniques. Researchers who use this resource will be able
to understand and implement the technology and data in their
respective fields. As such, it is a valuable reference for
researchers and data analysts in remote sensing and Earth
Observation fields and those in ecology, agriculture, hydrology and
geology.
Satellite Soil Moisture Retrieval: Techniques and Applications
offers readers a better understanding of the scientific
underpinnings, development, and application of soil moisture
retrieval techniques and their applications for environmental
modeling and management, bringing together a collection of recent
developments and rigorous applications of soil moisture retrieval
techniques from optical and infrared datasets, such as the
universal triangle method, vegetation indices based approaches,
empirical models, and microwave techniques, particularly by
utilizing earth observation datasets such as IRS III, MODIS,
Landsat7, Landsat8, SMOS, AMSR-e, AMSR2 and the upcoming SMAP.
Through its coverage of a wide variety of soil moisture retrieval
applications, including drought, flood, irrigation scheduling,
weather forecasting, climate change, precipitation forecasting, and
several others, this is the first book to promote synergistic and
multidisciplinary activities among scientists and users working in
the hydrometeorological sciences.
Sensitivity Analysis in Earth Observation Modeling highlights the
state-of-the-art in ongoing research investigations and new
applications of sensitivity analysis in earth observation modeling.
In this framework, original works concerned with the development or
exploitation of diverse methods applied to different types of earth
observation data or earth observation-based modeling approaches are
included. An overview of sensitivity analysis methods and
principles is provided first, followed by examples of applications
and case studies of different sensitivity/uncertainty analysis
implementation methods, covering the full spectrum of sensitivity
analysis techniques, including operational products. Finally, the
book outlines challenges and future prospects for implementation in
earth observation modeling. Information provided in this book is of
practical value to readers looking to understand the principles of
sensitivity analysis in earth observation modeling, the level of
scientific maturity in the field, and where the main limitations or
challenges are in terms of improving our ability to implement such
approaches in a wide range of applications. Readers will also be
informed on the implementation of sensitivity/uncertainty analysis
on operational products available at present, on global and
continental scales. All of this information is vital in the
selection process of the most appropriate sensitivity analysis
method to implement.
This book advances the scientific understanding, development, and
application of geospatial technologies related to water resource
management. It presents recent developments and applications
specifically by utilizing new earth observation datasets such as
TRMM/GPM, AMSR E/2, SMOS, SMAP and GCOM in combination with GIS,
artificial intelligence, and hybrid techniques. By linking
geospatial techniques with new satellite missions for earth and
environmental science, the book promotes the synergistic and
multidisciplinary activities of scientists and users working in the
field of hydrological sciences.
Agricultural Water Management: Theories and Practices advances the
scientific understanding, development and application of
agricultural water management through an integrated approach. This
book presents a collection of recent developments and applications
of agricultural water management from advanced sources, such as
satellite, mesoscale and climate models that are integrated with
conceptual modeling systems. Users will find sections on drought,
irrigation scheduling, weather forecasting, climate change,
precipitation forecasting, and more. By linking these systems, this
book provides the first resource to promote the synergistic and
multidisciplinary activities of scientists in hydro-meteorological
and agricultural sciences. As agricultural water management has
gained considerable momentum in recent decades among the earth and
environmental science communities as they seek solutions and an
understanding of the concepts integral to agricultural water
management, this book is an ideal resource for study and reference.
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