舉報

會員
Hands-On Geospatial Analysis with R and QGIS
Managingspatialdatahasalwaysbeenchallengingandit'sgettingmorecomplexasthesizeofdataincreases.Spatialdataisactuallybigdataandyouneeddifferenttoolsandtechniquestoworkyourwayaroundtomodelandcreatedifferentworkflows.RandQGIShavepowerfulfeaturesthatcanmakethisjobeasier.ThisbookisyourcompanionforapplyingmachinelearningalgorithmsonGISandremotesensingdata.You’llstartbygaininganunderstandingofthenatureofspatialdataandinstallingRandQGIS.Then,you’lllearnhowtousedifferentRpackagestoimport,export,andvisualizedata,beforedoingthesameinQGIS.Screenshotsareincludedtoeaseyourunderstanding.Movingon,you’lllearnaboutdifferentaspectsofmanagingandanalyzingspatialdata,beforedivingintoadvancedtopics.You’llcreatepowerfuldatavisualizationsusingggplot2,ggmap,raster,andotherpackagesofR.You’lllearnhowtouseQGIS3.2.2tovisualizeandmanage(create,edit,andformat)spatialdata.DifferenttypesofspatialanalysisarealsocoveredusingR.Finally,you’llworkwithlandslidedatafromBangladeshtocreatealandslidesusceptibilitymapusingdifferentmachinelearningalgorithms.Byreadingthisbook,you’lltransitionfrombeingabeginnertoanintermediateuserofGISandremotesensingdatainnotime.
目錄(188章)
倒序
- coverpage
- Title Page
- Packt Upsell
- Why subscribe?
- Packt.com
- Contributors
- About the author
- About the reviewers
- Packt is searching for authors like you
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Download the example code files
- Download the color images
- Conventions used
- Get in touch
- Reviews
- Setting Up R and QGIS Environments for Geospatial Tasks
- Installing R
- Basic data types and data structures in R
- Basic data types in R
- Variable
- Data structures in R
- Vectors
- Basic operations with vector
- Matrix
- Array
- Data frames
- Lists
- Factor
- Looping functions and apply family in R
- Looping in R
- Functions in R
- Apply family – lapply sapply apply tapply
- apply
- lapply
- sapply
- tapply
- Plotting in R
- Installing QGIS
- Getting to know the QGIS environment
- Summary
- Questions
- Further reading
- Fundamentals of GIS Using R and QGIS
- GIS in R
- Data types in GIS
- Vector data
- Raster data
- Plotting point data
- Importing point data from Excel
- Plotting lines and polygons data in R
- Adding point data on polygon data
- Changing projection system
- Plotting quantitative and qualitative data on a map
- Using tmap for easier plotting
- Vector data in QGIS
- Adding Excel data in QGIS using joins
- Adding CSV layers in QGIS
- Showing multiple labels using text chart diagrams
- Adding a background map
- Summary
- Questions
- Further reading
- Creating Geospatial Data
- Getting data from the web
- Downloading data from Natural Earth
- Downloading data from DIVA-GIS
- Downloading data from EarthExplorer
- Creating vector data
- Creating point data
- Creating polygon data
- Adding features to vector data
- Digitizing a map
- Working with databases
- Creating a SpatiaLite database
- Adding a shapefile to a database
- Summary
- Questions
- Further reading
- Working with Geospatial Data
- Working with vector data in R
- Combining shapefiles in R
- Clipping in R
- Difference in R
- Area calculation in R
- Working with vector data in QGIS
- Combining shapefiles
- Converting vector data types
- Polygons into lines
- Lines into polygons
- Clipping
- Difference
- Buffer
- Intersection
- Statistical summary of vector layers
- Using field calculators for advanced field calculations
- Summary
- Remote Sensing Using R and QGIS
- Basics of remote sensing
- Basic terminologies
- Remote sensing image characteristics
- Atmospheric correction
- Working with raster data in R
- Reading raster data
- Stacking raster data
- Changing the projection system of a raster file
- False color composite
- Slope aspect and hillshade
- Slope
- Aspect
- Hillshade
- Normalized Difference Vegetation Index (NDVI)
- Classifying the NDVI
- Working with raster data in QGIS
- False color composite
- Raster mosaic
- Clip raster by mask layer
- Projection system
- Changing projection systems
- Sampling raster data using points
- Reclassifying rasters
- Slope aspect and hillshade in QGIS
- Slope
- Summary
- Questions
- Point Pattern Analysis
- Introduction to point pattern analysis
- The ppp object
- Creating a ppp object from a CSV file
- Marked point patterns
- Analysis of point patterns
- Quadrat test
- G-function
- K-function
- L-function
- Spatial segregation for a bivariate marked point pattern
- Summary
- Spatial Analysis
- Testing autocorrelation
- Preparing data
- Moran's I index for autocorrelation
- Modeling autocorrelation
- Spatial autoregression
- Generalized linear model
- Modeling count data using Poisson GLM
- Spatial interpolation
- Nearest-neighbor interpolation
- Inverse distance weighting
- Geostatistics
- Some important concepts
- Variograms
- Kriging
- Checking residuals
- Summary
- GRASS Graphical Modelers and Web Mapping
- GRASS GIS
- Basics of GRASS GIS
- Database
- Location
- Mapset
- Creating a mapset
- Importing vector data in GRASS
- Importing raster data in GRASS
- False color composite in GRASS
- Graphical modeler
- Web mapping
- Web mapping in QGIS
- Summary
- Classification of Remote Sensing Images
- Classification of raster data
- Supervised classification
- Supervised classification in QGIS
- Creating a validation shapefile
- Unsupervised classification
- Summary
- Landslide Susceptibility Mapping
- Landslides in Bangladesh
- Landslide susceptibility modeling
- Data preprocessing
- Model building
- Logistic regression
- CART
- Random forest
- Summary
- Other Books You May Enjoy
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