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This is a book about how ecologists can integrate remote sensing
and GIS in their research. It will allow readers to get started
with the application of remote sensing and to understand its
potential and limitations. Using practical examples, the book
covers all necessary steps from planning field campaigns to
deriving ecologically relevant information through remote sensing
and modelling of species distributions. An Introduction to Spatial
Data Analysis introduces spatial data handling using the open
source software Quantum GIS (QGIS). In addition, readers will be
guided through their first steps in the R programming language. The
authors explain the fundamentals of spatial data handling and
analysis, empowering the reader to turn data acquired in the field
into actual spatial data. Readers will learn to process and analyse
spatial data of different types and interpret the data and results.
After finishing this book, readers will be able to address
questions such as "What is the distance to the border of the
protected area?", "Which points are located close to a road?",
"Which fraction of land cover types exist in my study area?" using
different software and techniques. This book is for novice spatial
data users and does not assume any prior knowledge of spatial data
itself or practical experience working with such data sets. Readers
will likely include student and professional ecologists,
geographers and any environmental scientists or practitioners who
need to collect, visualize and analyse spatial data. The software
used is the widely applied open source scientific programs QGIS and
R. All scripts and data sets used in the book will be provided
online at book.ecosens.org. This book covers specific methods
including: what to consider before collecting in situ data how to
work with spatial data collected in situ the difference between
raster and vector data how to acquire further vector and raster
data how to create relevant environmental information how to
combine and analyse in situ and remote sensing data how to create
useful maps for field work and presentations how to use QGIS and R
for spatial analysis how to develop analysis scripts
This is a book about how ecologists can integrate remote sensing
and GIS in their daily work. It will allow ecologists to get
started with the application of remote sensing and to understand
its potential and limitations. Using practical examples, the book
covers all necessary steps from planning field campaigns to
deriving ecologically relevant information through remote sensing
and modelling of species distributions. All practical examples in
this book rely on OpenSource software and freely available data
sets. Quantum GIS (QGIS) is introduced for basic GIS data handling,
and in-depth spatial analytics and statistics are conducted with
the software packages R and GRASS. Readers will learn how to apply
remote sensing within ecological research projects, how to approach
spatial data sampling and how to interpret remote sensing derived
products. The authors discuss a wide range of statistical analyses
with regard to satellite data as well as specialised topics such as
time-series analysis. Extended scripts on how to create
professional looking maps and graphics are also provided. This book
is a valuable resource for students and scientists in the fields of
conservation and ecology interested in learning how to get started
in applying remote sensing in ecological research and conservation
planning.
This is a book about how ecologists can integrate remote sensing
and GIS in their research. It will allow readers to get started
with the application of remote sensing and to understand its
potential and limitations. Using practical examples, the book
covers all necessary steps from planning field campaigns to
deriving ecologically relevant information through remote sensing
and modelling of species distributions. An Introduction to Spatial
Data Analysis introduces spatial data handling using the open
source software Quantum GIS (QGIS). In addition, readers will be
guided through their first steps in the R programming language. The
authors explain the fundamentals of spatial data handling and
analysis, empowering the reader to turn data acquired in the field
into actual spatial data. Readers will learn to process and analyse
spatial data of different types and interpret the data and results.
After finishing this book, readers will be able to address
questions such as "What is the distance to the border of the
protected area?", "Which points are located close to a road?",
"Which fraction of land cover types exist in my study area?" using
different software and techniques. This book is for novice spatial
data users and does not assume any prior knowledge of spatial data
itself or practical experience working with such data sets. Readers
will likely include student and professional ecologists,
geographers and any environmental scientists or practitioners who
need to collect, visualize and analyse spatial data. The software
used is the widely applied open source scientific programs QGIS and
R. All scripts and data sets used in the book will be provided
online at book.ecosens.org. This book covers specific methods
including: what to consider before collecting in situ data how to
work with spatial data collected in situ the difference between
raster and vector data how to acquire further vector and raster
data how to create relevant environmental information how to
combine and analyse in situ and remote sensing data how to create
useful maps for field work and presentations how to use QGIS and R
for spatial analysis how to develop analysis scripts
This is a book about how ecologists can integrate remote sensing
and GIS in their daily work. It will allow ecologists to get
started with the application of remote sensing and to understand
its potential and limitations. Using practical examples, the book
covers all necessary steps from planning field campaigns to
deriving ecologically relevant information through remote sensing
and modelling of species distributions. All practical examples in
this book rely on OpenSource software and freely available data
sets. Quantum GIS (QGIS) is introduced for basic GIS data handling,
and in-depth spatial analytics and statistics are conducted with
the software packages R and GRASS. Readers will learn how to apply
remote sensing within ecological research projects, how to approach
spatial data sampling and how to interpret remote sensing derived
products. The authors discuss a wide range of statistical analyses
with regard to satellite data as well as specialised topics such as
time-series analysis. Extended scripts on how to create
professional looking maps and graphics are also provided. This book
is a valuable resource for students and scientists in the fields of
conservation and ecology interested in learning how to get started
in applying remote sensing in ecological research and conservation
planning.
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