Visualizing hourly traffic crime data for Denver, Colorado using R, dplyr, and ggplot
This tutorial demonstrates how to access and visualize crime data for Denver, Colorado.
Data Intensive Tutorials
Scientific programming can be used to efficiently work with many different types of data. Rather than performing tasks manually, you can write code that opens, cleans and processes your data. However, often figuring out how to perform a specific task in R, Python or another programming language can be tricky. In the tutorials below, you will learn how to use R, Python and Javascript programming languages to perform specific tasks including calculating slope in a digital elevation model or using Leaflet to create an interactive map.
If there is a tutorial you’d like to see covered, reach out to us on Twitter @EarthLabCU.
Tutorials
Tutorials that cover data intensive topics
Calculating the area of polygons in Google Earth Engine
This tutorial demonstrates polygon creation, perimeter and area calculations, and visualization using the JavaScript interface to Google Earth Engine.
Introduction to the Google Earth Engine Python API
This tutorial outlines the process of installing the Google Earth Engine Python API client.
Introduction to the Google Earth Engine code editor
This tutorial introduces the code editor in Google Earth Engine and shows how to use LandSat imagery using the JavaScript API.
Get Modis sinusoidal tile grid positions from latitude and longitude coordinates in Python
This tutorial demonstrates how to convert Modis sinusoidal tile grid positions to latitude and longitude in Python.
Convert lat/lon coordinates to Landsat 8 path/row in Python
This tutorial demonstrates how to convert Landsat 8 path/row coordinates to latitude and longitude in Python.
Using Leaflet and Folium to make interactive maps in Python
This tutorial shows how to make interactive maps in Python with folium.
Visualizing elevation contours from raster digital elevation models in Python
This tutorial shows how to compute and plot contour lines for elevation from a raster DEM (digital elevation model).
Calculating slope and aspect from a digital elevation model in Python
This tutorial shows how to compute the slope and aspect from a digital elevation model in Python.
DEPRECATED: Introduction to spatial regression in Python
This tutorial has been deprecated.
Computing raster statistics around buffered spatial points Python
This tutorial shows how to compute raster statistics like the mean and variance around buffered spatial points in Python.
Acquiring streamflow data from USGS with climata and Python
This tutorial demonstrates how to use climata to acquire streamflow data in and around Boulder, Colorado.
Computing and plotting 2d spatial point density in R
This tutorial demonstrates how to compute 2d spatial density and visualize the result using storm event data from NOAA.
Using R and Python in the same Jupyter notebook
This tutorial shows how to use rpy2 in a Jupyter notebook to run both R and Python.
Acquiring U.S. census data with Python and cenpy - Deprecated lesson
This tutorial has been deprecated.
Create rasters from SMAP data in Python
This tutorial demonstrates how to access SMAP data, and how to generate raster output from this data.