SUS 9000A: Geospatial Analysis

Michael Tantala

Course Description

Trhis course is designed to explore analysis of spatial information, Geographic Information Systems (GIS) technology, and real-world applications to a broad range of fields: Architecture, Landscape Architecture, Planning, Earth and Atmospheric Sciences, Economics and Business, and Engineering. This course will help students develop a solid, hands-on understanding of the use and application of geographic information systems. The goals are to help students: acquire technical skills in the use of advanced GIS software; acquire qualitative and quantitative skills in data and document gathering, analyzing information, performing spatial calculations, and presenting results; and to investigate the potential and practicality of GIS technologies in several scenario-based settings to real-world applications.

Through lectures, readings, discussion, and Geographic Information Systems (GIS) modeling, we will work extensively with techniques of geospatial analysis in GIS. We will explore data sources, data models, topological overlays, map algebra, spatial statistics, remote sensing and satellite imagery, terrain analysis, and suitability modeling, among others. Visual expression is one of the most compelling methods to describe the physical environment, and students will learn techniques specifically geared towards quantifying environmental, social, and economic dynamics and how they relate to decision-making and design. We will interweave GIS mapping and analysis throughout the course to emphasize the interconnections between the different layers and systems.

CCNY Spitzer School of Architecture

LAAR 61700 / LAAR 61610 / ARCH 51560 - Geospatial Analysis Tantala Fall 2019

ESRI ArcGIS/ArcMap software will be used extensively. This course will cover a range of functionality available in the software and the essential tools for visualizing, creating, managing, and analyzing geographic data. No prior GIS knowledge is required. This course welcomes students new to GIS and also those who have worked with GIS previously with interest in more advanced topics.

Methodology and Course Requirements

This course is principally divided into “lecture” and computer lab components. In computer lab, students will learn the fundamentals of GIS and ultimately propose and execute their own GIS analysis. The lecture component of class will cover the fundamentals of spatial analysis where the topics are sequenced to convey the material and meet the Learning Objectives and develop the skills that are the Educational Goals.

Educational Goals and Learning Objectives

In this course, it is important for you to (1) establish a conceptual framework for critically engaging the practices of mapping and data-visualization, (2) provide a basic understanding of tools and techniques needed to reason, design and communicate with geospatial data, and (3) Develop skills and confidence for visualizing the complex processes, flows, and dependencies unique to a variety of disciplines.

This course will combine traditional lectures with hands-on GIS analysis and class discussion. While much of the subject matter may be new and unfamiliar, students are expected to have thoroughly read required readings and to come prepared to participate in class discussions as they would for a seminar course.

The class projects will have access to premium data and spatial content within the LAAR Geospatial Center (LGC). The student projects will share and create new research content and datasets for the LGC geospatial collection.

References Texts

Most weeks will include specific excerpts that will be provided online to read before class for discussion or to aid with assignments and your project. There are also several reference texts that we will refer to which provide geospatial methods and to provide assistance with ArcGIS analyses. It is recommended that you review specific chapters each week or pull them out when you feel uncertain of the next research/writing/drawing step. You should consider these texts:

  1. (1)  Shellito, Bradley A., Discovering GIS and ArcGIS, Second Edition, W.H. Freeman and Company, 2017.

  2. (2)  Keranen, Kathryn and Malone, Lyn, The ArcGIS Imagery Book, ESRI Academic Press, 2017.

  3. (3)  Keranen, Kathryn and Kolvoord, Robert, Making Spatial Decisions Using ArcGIS PRO, ESRI Academic Press, 2017.

  4. (4)  Law, Michael and Collins, Amy, Getting to Know ArcGIS PRO, ESRO Press, 2016.

CCNY Spitzer School of Architecture

LAAR 61700 / LAAR 61610 / ARCH 51560 - Geospatial Analysis Tantala Fall 2019

Grading and Academic Conduct

1. Grading Breakdown. Grading for the class will be determined according to the following criteria:

• Class Participation, Attendance, and Discussion • Synopsis / Short Assignments
• Geospatial Assignments
• Midterm Project Pinup/Presentation

• Final Project and Presentation

12% (four at 3% each) 40% (four at 10% each) 15%

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2. Incompletes: There will be no Incomplete given for a course except for a documented medical excuse at the discretion of the instructor. You are required to attend all classes and be present in the class during the allocated times. Absences need to be notified in advance of the class.

3. Attendance and timely submission of assignments: More than two unexcused absences in a course will result in a failing grade (two absences is equal to over 13% of total class time). Late assignments will not be reviewed for a grade. Each student must turn in what is completed or receive a failing grade for the particular assignment. Names of individuals should be clearly indicated on all assignments.

4. Grading Standards

Grade Explanation (refers to class performance)

A+ Rare, near perfect achievement A Exceptional
A- Excellent
B+ High caliber

B Satisfactory
B- Below average C+ Not satisfactory C Poor
F Course failure

Quality Points

4.00 4.00 3.70 3.30 3.00 2.70 2.30 2.00 0.00

CCNY Spitzer School of Architecture

LAAR 61700 / LAAR 61610 / ARCH 51560 - Geospatial Analysis Tantala Fall 2019 Course Schedule NB: This schedule is subject to change!

week date 1 8/30

topic and readings (as assigned)

Course Introduction: Mapping and Geographic Information Systems (GIS)

Symbolizing information with maps
Topics: Syllabus, Course requirements, Overview of GIS; Samples of GIS applications; Maps and Exploring

GIS maps: Defining features, layers, and data frames; Exploring map scale; Working with Projections and datums; Understanding the relationship between features and attributes; Exploring a GIS database: Exploring attribute tables; Identifying features; Symbology of features based on their attributes; Labeling features based on their attributes; Finding and Using Data. Examples and Sources of Data; arcgis portal; geospatial clearinghouses.

Spatial Analysis A : Visualizing and Symbolizing Geospatial Data

Making Sense out of Spatial Data: the map query

An introduction to spatial analysis for various kinds of problem solving in a GIS environment. Examples of both raster and vector data-based spatial operations like overlay, buffering, and interpolation will be covered. Understanding vector and raster data; Geodatabases; Shapefiles; Solving spatial problems with query and analysis; Understanding and performing attribute and spatial queries; Fundamental Geoprocessing Operations: Clip, Dissolve, Merge, Intercept, Union. Acquiring and public and premium geospatial data.

Spatial Analysis B : Working with Surfaces
Changes by Location: Topography, Terrain and Profiles

Topics: Working with topography and elevation data. Digital Elevation Models (DEMs). Introduction to Geospatial Tools, Toolboxes and Extensions: Spatial Analyst; 3d Analyst (Profile tools, Surface Analysis; Slope functions); Select ArcToolbox functions. Scenario specific applications. Landscape Analyst tools and content.

Spatial Analysis C : Raster Analysis

Map Algebra and Functional Mapping
Special Topic: Weather and Water Mapping : Hydrologic Models
Topics: Processing Rasters, Masks, Density, Change analysis; Raster Math; using Raster Calculator. Georeferencing. Scenario specific applications.
Application examples and tools in GIS for Hydrology, Climate and Climate Change.

2 9/6

  1. 3  9/13

  2. 4  9/20

5 9/27

Working with ArcGIS Pro

Social Mapping:
Demographic and Cultural Mapping, Georeferencing Historical Data

Working with Arcgis Online premium content and tools; Working with Census and demographic data; Population Models and Impact analysis; Distance and Travel time; Georeferencing historic data

Business and Financial Mapping:
Use of Business Analyst and Geostatistical Models
Working with Business Analyst Tools and datasets. Linear Regression Models.

Remote Sensing A :

Satellite Imagery and Premium Content
The earth from above. Bands and Spectrums. Combinations of Reflected Light. Understanding the basics of remote sensing technology, image data properties, and software tools and procedures for satellite image processing. Remotely Sensing Agricultural data

Midterm Project Pinups / Presentations

Remote Sensing B :

Classifications and Calculations with Remotely-Sensed Data
The changing nature of place. Hands on use of Multispectral software for multi-band combinations, supervised and unsupervised classification on a Landsat satellite image. Land Use Change Analysis: visual and quantitative analysis. Temporal-Spatial Change Sensitivity Analysis

Planning, Design and Decision-making techniques:

Suitability and Site Analysis using Geospatial Analysis
Planning and GIS. Working with spatial information: parcel, zoning and land use data, addresses, transportation networks, and housing. Mapping multiple urban and regional indicators, forecast future community needs.

Environment, Climate and Weather Models in Spatial Methods Hazards and Emergency Response.

3D visualization and calculations

Working with ArcScene and 3D models. Animation and Simulation. Viewshed analysis. Working with CityEngine Data.

  1. 6  10/4

  2. 7  10/11

  3. 8  10/18

  4. 9  10/25

  5. 10  11/1

  6. 11  11/8

CCNY Spitzer School of Architecture

LAAR 61700 / LAAR 61610 / ARCH 51560 - Geospatial Analysis Tantala Fall 2019

  1. 12  11/15

  2. 13  11/22

  3. 14  11/29

  4. 15  12/06

  5. 16  12/13

  6. 17  12/20

Mapping temporal data : the science of where and the timing of when VR and Tangible Landscapes. Data collection and Drones.

Advanced Topics: Model Builder, Codes and Scripts (continued)

Research methods in GIS
Automating Analyses, working with Lidar data. Mapping real-time data.

Class Final Presentations due

Class final paper due