UNBC GIS Lab

  • Home
  • Courses
    • ENPL 303
      • ENPL 303 Lectures
      • ENPL 303 Labs
      • ENPL 303 Tutorials
    • GEOG 204
      • GEOG 204 Lectures
      • GEOG 204 Labs
      • GEOG 204 Tutorials
    • GEOG 205
      • GEOG 205 Lectures
      • GEOG 205 Labs
      • GEOG 205 Tutorials
    • GEOG 250
      • GEOG 250 – Lectures
      • GEOG 250 – Labs
      • GEOG 250 – Projects
    • GEOG 300
      • GEOG 300 Lectures
      • GEOG 300 Labs
      • GEOG 300 Tutorials
    • GEOG 357
      • GEOG 357 Lectures
      • GEOG 357 Labs
      • GEOG 357 Tutorial
    • GEOG 413
      • GEOG 413 Lectures
      • GEOG 413 Labs
      • GEOG 413 Tutorials
    • GEOG 450/650
      • GEOG 450 – Lecture
      • GEOG 450 – Labs
      • GEOG 450 – Tutorial
    • GEOG 457
      • GEOG 457 Lectures
      • GEOG 457 Labs
      • GEOG 457 Tutorials
    • GEOG 499
      • GEOG 499 Lectures
      • GEOG 499 Labs
      • GEOG 499 Tutorials
  • Contacts
  • Support

Anthony Jjumba

Uncategorized

Lab 7/8 PostgreSQL and Leaflet

In todays lab we will be working with Enterprise Database Management Systems (DBMS). First looking at conceptual design, then logical design, and finishing with with SQL or Structured Query Language. While we will not be working with spatial data today, this week’s lab forms an important foundation DBMS in general. Read more…

By Anthony Jjumba, 7 months2024-11-18 ago
Uncategorized

GEOG413/613 – Lab 5

Moran’s I Spatial Autocorrelation The data For this exercise, we will use the Pennsylvania county-level lung cancer counts for 2002. The data are provided by the SpatialEpi package, which we will install for this exercise. The dataset comes a tibble with a the following components: Do you see a degree Read more…

By Anthony Jjumba, 8 months2024-10-29 ago
Uncategorized

GEOG413/613 – Lab 4

In today’s lab, we will be looking at some of the more fundamental exploratory analysis tools. Cluster Analysis (using K-Means), and Quadrat Analysis. K-Means Clustering Clustering algorithms are useful for separating data into groups with similar qualities, clustering is often not the end goal in and of itself, but it Read more…

By Anthony Jjumba, 9 months2024-10-08 ago
Uncategorized

GEOG413/613 – Lab 3

Principal Component Analysis Eigenvectors, Eigenvalues, Identity Matrices It is helpful to have some background in linear algebra. For our purposes, though, we’ll start with a remote sensing example. A visual example To start our exploration of PCA we will first look at the principal components of an image as it Read more…

By Anthony Jjumba, 9 months2024-10-01 ago
Uncategorized

GEOG413/613 – Lab 2

Working with spatial data sf & sp packages The tools for handling spatial data in R were built around the SP package. However, recently, the sf (simple features) package has been developed to conform with formal geospatial standards, which has mostly replaced the sp tools. The sf and sp data Read more…

By Anthony Jjumba, 9 months2024-09-24 ago
Uncategorized

GEOG413/613 – Lab 1

Basic Analytics in R data.frames and tibble When working with tabular data, generally each row represents a record of the phenomena of interest (such as a spatial object, a person…) and each columns represents an attribute of that feature.  In R, data can be in a matrix, but matrices can only Read more…

By Anthony Jjumba, 9 months2024-09-17 ago
Uncategorized

GEOG413/613 Lab 1

R is a programming language that is widely used in areas of scientific activity and quantitative research.  The extensive functionally is through R packages, which are referred to as Libraries when installed. These libraries extend the core R packages.  The Basics You can type commands directly in the R console Read more…

By Anthony Jjumba, 10 months2024-09-10 ago
  • Contacts
  • Courses
  • Home
  • Support
Hestia | Developed by ThemeIsle