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This book addresses the mapping of soil-landscape parameters in the
geospatial domain. It begins by discussing the fundamental
concepts, and then explains how machine learning and geomatics can
be applied for more efficient mapping and to improve our
understanding and management of 'soil'. The judicious utilization
of a piece of land is one of the biggest and most important current
challenges, especially in light of the rapid global urbanization,
which requires continuous monitoring of resource consumption. The
book provides a clear overview of how machine learning can be used
to analyze remote sensing data to monitor the key parameters,
below, at, and above the surface. It not only offers insights into
the approaches, but also allows readers to learn about the
challenges and issues associated with the digital mapping of these
parameters and to gain a better understanding of the selection of
data to represent soil-landscape relationships as well as the
complex and interconnected links between soil-landscape parameters
under a range of soil and climatic conditions. Lastly, the book
sheds light on using the network of satellite-based Earth
observations to provide solutions toward smart farming and smart
land management.
This book addresses the mapping of soil-landscape parameters in the
geospatial domain. It begins by discussing the fundamental
concepts, and then explains how machine learning and geomatics can
be applied for more efficient mapping and to improve our
understanding and management of 'soil'. The judicious utilization
of a piece of land is one of the biggest and most important current
challenges, especially in light of the rapid global urbanization,
which requires continuous monitoring of resource consumption. The
book provides a clear overview of how machine learning can be used
to analyze remote sensing data to monitor the key parameters,
below, at, and above the surface. It not only offers insights into
the approaches, but also allows readers to learn about the
challenges and issues associated with the digital mapping of these
parameters and to gain a better understanding of the selection of
data to represent soil-landscape relationships as well as the
complex and interconnected links between soil-landscape parameters
under a range of soil and climatic conditions. Lastly, the book
sheds light on using the network of satellite-based Earth
observations to provide solutions toward smart farming and smart
land management.
The present book is the outcome of the research work carried out by
the main author in the form of PhD work under the supervision of
the co-author. The book consists of seven chapters followed by a
bibliography. Sufficient review of the concerned literature has
been done. A generalized gamma type model has been proposed and its
statistical analysis has been carried out with its various
characteristics. The proposed model is useful for the analysis of
life time data related to engineering, medical and bio-medical
sciences. Several applications of the proposed model have been
outlined. The book includes Bayes estimation of the parameters of
the proposed model, reliability and hazard rate functions and some
tests of significance regarding the parameters. A mixture model has
also been developed from the proposed model and some of its
characteristics have been investigated. The present book may be
useful for the researchers working in life testing.
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