Lab Reports

Chelsea Scheske

Overview of Lab Reports

The Lab Report section contains summaries of the seven labs completed during the Winter 2019 session of the ENVB 530 (Advanced GIS) course at McGill University. To access the Lab Reports, click on the link under each heading, or navigate to the toolbar on the upper left corner of the page.

Lab 1: Applying the Spatial Analyst Extension

Lab 1 demonstrates the use of ArcGIS to find the best location for a school in Stowe, Vermont and identify the least costly access route to the new school site. ArcGIS Model Builder and various Spatial Analyst tools are employed to identify the optimal place for the new school based on various factors including slope, distance from waterways and wetlands, and distance from recreational activities and existing schools.

Lab 2: Rectification in ArcGIS

Lab 2 demonstrates the use of ArcGIS rectification tools to transform a .jpg image of an 1903 Montreal street map into an ArcGIS layer, effectively merging the 1903 map with a vector shape file (.shp) of Montreal street layouts. The result is a digitized version of the 1903 map with the same coordinate system as the vector street data. The resulting map is converted to a KML file for viewing on Google Earth.

Lab 3: Python and Model Builder

Lab 3 explores the intersections between Python and Model Builder, extending our ArcGIS analysis capabilities. An extraction (Times tool) and a reclassification (Slice tool) are performed on seven TIFF files using code exported from Model Builder, and adjusted manually. The result is a code that, when executed in ArcGIS, applies the given treatment (Times or Slice) to the seven input TIFF files rapidly, and saves the raster output along with specified Raster Data in new files.

Lab 4: Regression Analysis

In Lab 4 we perform an analysis of 911 Call Volumes in Portland, OR, to determine factors leading to high call volumes and inform policies to reduce the volumes in the future. This is done using both Ordinary Least Squares Regression (OLS) and Geographically Weighted Regression (GWR) tools in ArcGIS. In addition, geographically specific predictions of future calls is carried out using the GWR tool.

Lab 5: Interpolation with QGIS

In Lab 5 we explore QGIS, the COMPLETELY FREE & OPEN SOURCE sister-program to ArcGIS. Here, using QGIS we interpolate data measurements from a DGPS instrument taken over Lake Arlington, Texas, to create a depth map of the lake.

Lab 6: Introduction to Earth Engine

In Lab 6 we are introduced to the processing power of the Earth Engine API. Using Javascript, we perform some basic data analysis on Image Collections provided by Earth Engine, including image filtering, the use of the .reduce() function, the computation of NDVI,building a greenest-pixel composite, including the application of computation to an image, the application of a spatial reducer, the loading and filtering of an image collection, modification of image bands, reducing image collections, isolating an image, computing NDVI, writing a function, mapping a function over a collection, building a greenest-pixel composite, charting NDVI over time, and exporting an RGB image. The following write up includes discussion and images of the results of these processes.

Created for Advanced GIS for Natural Resource Management, in the McGill University Department of Natural Resource Sciences, Professor Jeffrey Cardille