[Intermediate] Spatial Data Analysis with R, QGIS & More

In this lecture students will be briefly introduced to the concepts pertaining to spatial data analysis such as coordinate reference systems and the different spatial data that will be used in the course. 

This lecture will show how to configure GRASS to read in our own data. The demonstration data are in folder "Lecture_4-grass_eg1"

This quiz will test the introductory concepts relating to spatial data and the software tools that we will use in this course 

This lecture presents a brief overview of what shapefiles are and their attribute table is. Further I briefly demonstrate how to modify the basic properties of shapefiles to improve their appearance. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this section we will see how shapefiles can be rendered and visualized using qualitative attributes. We will focus on the world map and display the different continents in there as a way of making the world map more intuitive.  The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this section we will see how shapefiles can be rendered and visualized using quantitative attributes. We will focus on the world map and use the country areas in there as a way of making the world map more intuitive. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this lecture the students will be exposed to basic concepts of mapping shapefile data and mapping shapefile attributes in R using spplot function.  The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

This lecture will demonstrate how to build choropleth maps using shapefiles in R. The students will also be introduced to the R package, GISTools for choropleth mapping.  The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this lecture, students will learn how to use Google Earth data and display their own spatial data on Google Earth base layers. The data for this lecture are in folder "Lecture_11-ggplot_GE_R"

In this section I will demonstrate how to add data from a CSV file to a shapefile using a spatial join. Spatial joins work by combining data for common attributes in CSV and the shapefile. The data for this lecture are in folder "Lecture_13-JpnPop_joinR". 

In this lecture we will see how to carry out the spatial joining demonstrated in the previous lecture in QGIS using R. The data for this lecture are in folder "Lecture_13-JpnPop_joinR". 

In this lecture I will demonstrate how to compute basic descriptive statistics from a shapefile using R.  The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this lecture the students will learn how to add a user defined buffer to a polygon or a polyline. The data used in this lecture are present in the folder "Lecture_16-buffer_vector_data". 

In this lecture the students will learn how to add a user defined buffer to a polygon or a polyline. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn". 

This lecture demonstrates how to make an outer buffer/boundary in both R and QGIS. The data for this lecture are in folder "Lecture_18-outer_buffer".

A brief description of the data used for lectures 20--23

In this lecture the students will learn how to carry out the union between 2 shapefiles in QGIS. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn". 

In this lecture the students will learn how to clip a shapefile in QGIS. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn". 

In this lecture the students will learn how to intersect 2 shapefiles in QGIS. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn". 

In this lecture I will show how to carry out intersection between two shapefiles and clip the bigger shapefile using the smaller shapefile as a cookie-cutter in R. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn". 

This quiz is designed to test the ability of the students to carry out analysis of shapefile data

In this lecture I will demonstrate how to make a heat map from point/XY data in QGIS and visually display the distribution and concentration of attributes using QGIS. The data used in this lecture are present in the folder "Lecture_25-Heatmap". 

A brief introduction to the theory behind Kernel Density Estimation (KDE)

In this lecture I will demonstrate how to use geographical point data to map the distribution and clustering of an attribute using Kernel Density Estimates in R. A brief introduction to the package spatstat (used for analyzing point/XY data) has been provided. The data used in this lecture are present in the folder "Lecture_27-uk_plaque". 

In this lecture, the students will learn how to plot heat maps to show the spatial distribution and concentration of point data on Google Earth in R. The data for this lecture are in "Lecture_27-uk_plaque".

In this lecture, the students will learn how to carry out interpolation of point data in QGIS. The data for this lecture are in "Lecture_30-aust_elev".

Students will be able to carry out thin spline interpolation on point data to produce a raster surface. The data for this lecture are in "Lecture_31-interpolation_r".

This lecture demonstrates how to carry out the IDW interpolation of point data in R. Students will be able to carry out thin spline interpolation on point data to produce a raster surface. The data for this lecture are in "Lecture_31-interpolation_r".

This lecture briefly demonstrates how to carry out kriging in R. Students will be able to carry out thin spline interpolation on point data to produce a raster surface. The data for this lecture are in "Lecture_31-interpolation_r".

This lecture demonstrates how to use GRASS to implement some interpolation techniques on point data. The data for this lecture are in "Lecture_32-interpolation_grass1".

This quiz seeks to test the understanding of carrying out point patterns analysis of spatial data

I will demonstrate how to display raster data in QGIS and how to use Properties to enhance the rendering and visualization of these data.  The data for this lecture are in "Lecture_37-digital elevation model_easia".

This lecture will demonstrate how to display raster data in R. A brief introduction the package rasterVis which is used for visualizing raster data in R will be provided. The data for this lecture are in "Lecture_37-digital elevation model_easia".

This lecture will demonstrate how to extract raster statistics for a given set of shapefile polygons. The data for this lecture are in "Lecture_38-zonal_stats".

In this lecture I will demonstrate how to merge and stitch together non-overlapping rasters in QGIS . The data for these lectures are in folder "Lecture_39-raster_merging"

This lecture demonstrates how we can merge adjacent, non-overlapping rasters in R.  The data for these lectures are in folder "Lecture_39-raster_merging"

Briefly demonstrate how to clip a raster to desired boundary using a shapefile as cookie-cutter in R and QGIS. The data for this lecture are in "Lecture_37-digital elevation model_easia".

Briefly demonstrate how to clip a raster to desired boundary using a shapefile as cookie-cutter in GRASS. The data for this lecture are in "Lecture_42-clipRasters_grass".

In this lecture, I will demonstrate how to carry out basic terrain analysis calculations on DEMs using GRASS. The data for this lecture are in "Lecture_37-digital elevation model_easia".

In this lecture I will show you how to geo-reference image data using QGIS. I will show how to add coordinate information both manually and using a Google Earth base layer map. The data for this lecture are in folder "Lecture_44-georeferencing_qgis"

A brief quiz pertaining to processing of raster data

This lecture shows how simple GIS tasks can be automated as a part of a workflow in QGIS. The data for this lecture are in "Lecture_37-digital elevation model_easia".

This lecture will show how to implement the AHP process on raster data in QGIS. The data for this lecture are in "Lecture_49-suitability analysis_MCDM".

This lecture will show how to build a basic interactive webmap in QGIS. The data for this lecture are in "Lecture_50-webmap_qgis".

This lecture shows how the student can build interactive web maps using their own spatial data in R. An introduction to the leaflet package is provided. The data for this lecture are in "Lecture_50-webmap_qgis".