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This book focuses solely on the issues of agriculture and forest
productivity analysis with advanced modeling approaches to bring
solutions to food-insecure regions of South and Southeast Asia.
Advanced modeling tools and their use in regional planning provide
an outstanding opportunity to contribute toward food production and
environments. In this book, leading-edge research methodologies
related to remote sensing and geospatial variability of soil,
water, and regional agricultural production indicators and their
applications are introduced together-a unique feature of the book
is the domain of regional policy perspectives and allied fields. In
regional policy planning, agriculture and forestry have a key role
in food security and environmental conservation that depends on the
geo-spatial variability of these factors. Over the years, nature
and climate have determined the variability of soil type, soil
quality, geographical deviation for habitat, water quality, water
sources, urban influences, population growth, carbon stock levels,
and water resources with rain-fed or irrigated land use practices.
In addition, human nutritional values and dietary habits have
brought cultural adaptation of either mono- or multi-cropping
patterns in the region. To encompass all these above mentioned
factors and classify regional variability for policy planning,
satellite remote sensing and geographical information systems have
the immense potential to increase agricultural and forest
productivity to ensure the resilience of its sustainability.
Therefore, the 13 chapters presented in this book introduce
modeling techniques using the signatures of vegetation and water
indices, land use and land change dynamics, climatic, and
socioeconomic criteria through spatial, temporal, and statistical
analysis. As well, remote sensing and in-depth GIS analysis are
integrated with machine and deep learning algorithms to address
natural uncertainties such as flash floods, droughts, and cyclones
in agricultural production management.
This book focuses solely on the issues of agriculture and forest
productivity analysis with advanced modeling approaches to bring
solutions to food-insecure regions of South and Southeast Asia.
Advanced modeling tools and their use in regional planning provide
an outstanding opportunity to contribute toward food production and
environments. In this book, leading-edge research methodologies
related to remote sensing and geospatial variability of soil,
water, and regional agricultural production indicators and their
applications are introduced together—a unique feature of the book
is the domain of regional policy perspectives and allied fields. In
regional policy planning, agriculture and forestry have a key
role in food security and environmental conservation that depends
on the geo-spatial variability of these factors. Â Over the
years, nature and climate have determined the variability of soil
type, soil quality, geographical deviation for habitat, water
quality, water sources, urban influences, population growth, carbon
stock levels, and water resources with rain-fed or irrigated land
use practices.  In addition, human nutritional values
and dietary habits have brought cultural adaptation of either mono-
or multi-cropping patterns in the region. To encompass all these
above mentioned factors and classify regional variability for
policy planning, satellite remote sensing and geographical
information systems have the immense potential to increase
agricultural and forest productivity to ensure the resilience of
its sustainability. Therefore, the 13 chapters presented in this
book introduce modeling techniques using the signatures of
vegetation and water indices, land use and land change dynamics,
climatic, and socioeconomic criteria through spatial, temporal, and
statistical analysis. As well, remote sensing and in-depth GIS
analysis are integrated with machine and deep learning algorithms
to address natural uncertainties such as flash floods, droughts,
and cyclones in agricultural production management.
This book has the ambition of presenting sustainability issues in a
simple way to students in the field of agriculture and the
environment. There is much diversity in the viewpoints on the
meaning of sustainability. Sustainability must be made operational
in each specific context and scaled, and appropriate methods must
be designed to achieve long-term goals for the environment,
agriculture, energy and food security. The ultimate goal of the
environment and agriculture is protecting soil and water to ensure
food security for the growing population. This book discusses the
integration of views pertaining to the sustainability of
agriculture, the environment, renewable energy and food security.
Crop production varies spatially and temporally within the field
boundaries depending on soil and environmental conditions. The
major concern of variability for agronomic inputs addresses how
best to intervene in the right place, at the right time and in the
right quantity to improve the potential yield of crops and
feedstock. This book addresses the important question of how large
a role bioproduction and renewable energy can play in achieving
sustainable agricultural practices in the present system of
agricultural production. Agronomy is local, which brings the
challenges to the remote optimisation of agricultural machinery
operations for seeding, fertilising, crop protecting, and
harvesting in the field level to adopt precise agriculture
technologies. Cloud computing and big data analytics bring the
potential about in machine optimisation and agronomy to enable the
site-specific management. Understanding bioproduction engineering
and development can help improve the efficiency of a sustainable
agriculture system. With the aim of understanding this process,
this book focuses on bioproduction and sustainability issues,
covering sensors, agricultural decision-making systems and the
relationship between bioproduction and sustainable practices of
agriculture. The chapters are organised as follows: information
oriented technology that can be implemented to address the
variability of bioproduction systems, sensors and control systems,
precision agricultural technology, decision support systems in
agriculture, renewable energy resources and analytical hierarchy
processes for agricultural management. The crop growth monitoring
parameters like LAI and NDVI points were clarified in the
pre-processing stage of images. The decisions and logistics that
influence the market prices of agricultural products is emphasised
within the revised edition of this book.
This book addresses the important question of how large a role
bioproduction and renewable energy can play in achieving
sustainable agricultural practices in the present system of
agricultural production. Understanding bioproduction engineering
and development can help improve the efficiency of sustainable
agriculture and future renewable energy resources. With the aim of
understanding this question, this book focuses on bioproduction and
sustainability issues, covering sensors, agricultural decision
making systems and the relationship between bioproduction and
sustainable practices of agriculture. Topics discussed include
information oriented technology that can be implemented to address
the variability of bioproduction systems; sensors and control
systems; precision agricultural technology; decision support
systems in agriculture; renewable energy resources; and analytical
hierarchy processes for agricultural management. This material will
appeal to a wide range of readers and is designed as a resource for
graduate and undergraduate students working in any area of
agricultural engineering, crop sciences, or environmental science
disciplines. The book also includes questions and sample model
problems to allow readers to practice implementing the modelling
tools.
This book provides a sound understanding for creating new
knowledge, which takes three main forms: Exploratory research,
which structures and identifies new problems; constructive
research, which develops solutions to a problem; and empirical
research, which tests the feasibility of a solution using empirical
evidence. This book encompasses both qualitative and quantitative
research and analysis. The reader should gain an understanding of
the skills needed to design and undertake a research project,
including legal and ethical requirements in planning research
projects, choosing the best experimental design and analytical
methods, and how to present data for extension to the wider
community and establish the knowledge. Hands-on exercises are
provided to improve reasoning skills, emphasising agricultural
problems and issues to solve and interpret the experimental data to
knowledge. The book covers research methods within these three
forms with basic knowledge of research methodology. Design of
experiments and significant results are interpreted through the
scientific organisation and information in each of the chapters.
The inherent discussion should help interdisciplinary graduate
students and researchers accomplish their scientific experiments
and write research articles. The cognitive writing style to
interpret the observed data from experiments and surveys is
emphasised in this book. The cognitive summary for each of the
chapters is provided in the form of wording and graphics to focus
on the chapter highlights as well as the use of analytical tools in
the research. The utmost care is taken to present a varied range of
research problems along with their solutions in agriculture and its
allied fields, which should be of immense use to the readers
interested in this topic.
This book reviews recent innovations in the smart agriculture space
that use the Internet of Things (IoT) and sensing to deliver
Artificial Intelligence (AI) solutionsto agricultural productivity
in the agricultural production hubs. In this regard, South and
Southeast Asia are one of the major agricultural hubs of the world,
facing challenges of climate change and feeding the fast-growing
population. To address such challenges, a transboundary approach
along with AI and BIG data for bioinformatics are required to
increase yield and minimize pre- and post-harvest losses in
intangible climates to drive the sustainable development goal (SDG)
for feeding a major part of the 9 billion population by 2050
(Society 5.0 SDG 1 & 2). Therefore, this book focuses on the
solution through smart IoT and AI-based agriculture including pest
infestation and minimizing agricultural inputs for in-house and
fields production such as light, water, fertilizer and pesticides
to ensure food security aligns with environmental sustainability.
It provides a sound understanding for creating new knowledge in
line with comprehensive research and education orientation on how
the deployment of tiny sensors, AI/Machine Learning (ML),
controlled UAVs, and IoT setups for sensing, tracking, collection,
processing, and storing information over cloud platforms for
nurturing and driving the pace of smart agriculture in this current
time. The book will appeal to several audiences and the
contents are designed for researchers, graduates, and undergraduate
students working in any area of machine learning, deep learning in
agricultural engineering, smart agriculture, and environmental
science disciplines. Utmost care has been taken to present a varied
range of resource areas along with immense insights into the impact
and scope of IoT, AI and ML in the growth of intelligent digital
farming and smart agriculture which will give comprehensive
information to the targeted readers.Â
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