Project 6 GIS

.docx

School

Nichols College *

*We aren’t endorsed by this school

Course

ORGANIZATI

Subject

Computer Science

Date

Dec 6, 2023

Type

docx

Pages

8

Uploaded by AgentMonkey15760

Report
Diagnosing the Data: Project 6 Alternate: Graduated Colors and Raster Maps Steven McHugh School of Graduate, Online and Continuing Education, Fitchburg State University SP23_GIS and Decision Making-52 Dr. Davis February 27, 2023
Project Summary Throughout the progression of this course, we’ve learned about the significance of GIS and the data they could provide. As such, we have been how to extrapolate data and present it in a comprehensive and interactive manner. This week’s project presents another data analysis tool, raster analysis, of which we can utilize with the other topic at hand, imagery layers. To gain insight into this project, we must first define the concept of raster analysis. Raster “is a data format that consists of a matrix of cells (or pixels) organized into rows and columns (or a grid), in which each cells contains a value representing information. Raster data is advantageous because it consists of simple data structures, easy simulation due to the cells being the same size, and simple overlay and combination of maps and remote sensed images. Most importantly, it is cheap to perform (Sain, 2018). The main drawback to raster data analysis is its aesthetics as it may appear crude and its use of large cells may distort data causing a serious loss of information (Sain, 2018). In the context of ArcGIS, imagery “refers to any raster or cell-based data” (Fu, 2022, p.325) and “is often used as a basemap for reference” (Fu, 2022, p.326) and for different forms of spatial analysis. Imagery can then be implemented and published as imagery layers, the second major topic of this week’s reading. An imagery layer “provides access to raster data through a web service” (Fu, 2022, p.330). The use of web services is nothing new as we’ve been utilizing them all throughout this course for data interpretation and presentation. However, this week’s project had us not only present the provided data in a visually, interactive manner but it also gave us the chance to analyze it through a new means, that is raster analysis. My intent was to complete the primary project but for some reason, I was not able to access the option to create an imagery layer. Therefore, I focused on the alternate project which
focused on geocoded data and graduated symbols. This project’s feature layer pertained to COVID-19 cases in the United States. The purpose of Project 6 was to manipulate the map to change the symbology to reflect confirmed cases by incident rate as well as deaths. By doing so, each attribute is highlighted, and the data is easily presented. Proposed Map https://smfsu.maps.arcgis.com/home/item.html?id=54d48bf206ec473c9765fdd719a5ea22 https://smfsu.maps.arcgis.com/home/item.html?id=a176a1311e6f443db3d92f825accb656 The purpose of this map was to provide raster data pertaining to COVID-19 cases in the United States. As with previous projects, the basemap did not have to illustrate anything in particular and therefore, I went with the default topographic basemap. Next, I added the two predetermined layers for this map, USA States Generalized Boundaries and the main focus of this map, COVID-19 US Cases. I was able to acquire both of these layers through the ArcGIS Online database. Map 1.1 COVID-19 Cases in the US Figure 1.1 COVID-19 Cases in the US Legend
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
  • Access to all documents
  • Unlimited textbook solutions
  • 24/7 expert homework help