Goal

In this lab, we will exercise a real-world spatial analysis problem and develop a GIS solution using the raster analytical capabilities of ArcGIS. Here is a scenario for you:

You have been hired in your first job as a GIS consultant (Congratulations, Btw!). An executive from an energy supplier has presented you with an interesting problem. The company would like to expand into the solar power market, but it is still determining which global regions to focus its efforts on. The executive asked you to present a ranking of global areas based on their potential for solar power generation.

This work will involve some raster map algebra analysis. You will conduct a focal analysis across several raster layers with ArcGIS’s Raster Calculator tool. This is a very powerful and versatile tool for raster data. Using the outcome of this project, your client has decided that solar power production should be a) close to populated areas, b) in low-elevation areas, c) in relatively sunny areas, and d) near the equator so that solar insolation intensity will be strong enough to produce electricity efficiently.

Skills

The purpose of this lab is to help you practice the following skills that are essential to your success in this course, as well as in professional settings beyond school.

• Raster Calculator for selecting areas that fit the criteria and overlaying multiple raster layers
• Select Layer By Attribute and Select Layer By Location
• Buffer for the proximity analysis
• Data conversion from raster to vector

Lab data introduction

All data for this task will be provided to you (although this is rarely the case in real-world consulting jobs. You are primarily responsible for collecting all the data for the analysis!

• Insolation: Derived from a figure in Geosystems (Robert Christopherson) Units: Watts per square meter
• Population: Population density from NCGIA Units: persons per square kilometer. More information: http://www.ciesin.org/datasets/gpw/globldem.doc.html
• Elevation: Data set GTOPO30, United States Geological Survey, EROS Data Center. This is a global digital elevation model (DEM) with a horizontal grid spacing of 30 arc seconds (approximately 1 kilometer). Units: meter. More information: http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/gtopo30_info
• Cloudless: UNEP-GRID Units: percent cloudless, defined as the bright sunshine hours over the potential number. This means a pixel with many sunny days has a relatively HIGH percentage. More information: http://gcmd.nasa.gov