Skip to main content

Isarithmic Mapping

 

Map 1: Annual Precipitation, Washington State

Map 1 is an Isarithmic map that follows the continuous phenomenon of rainfall in Washington state over a 30 year period. The data was created by the PRISM group at the Oregon State University in 2006, and then downloaded and amended by the U.S. Department of Agriculture, Natural Resources Conservation Service, National Geospatial Management Center in 2012. Eden Santiago Gomez, analyzed the data on 5/2/2021, to create the map above. Santiago Gomez created continuous tones for the data, also adding a hillshade effect. She then converted the floating raster data into Integer data via the geoprocessing tool Int (Spatial Analyst Tool) to bring out hypsometric tinting. Lastly, she added contours of the data via the Contour List tool.  

How the precipitation data was derived and interpolated?

The PRISM system has been continually developed over the past couple decades, utilizing physiographical maps and climate fingerprints as its method of interpolation. Climate fingerprints uses the assumption that “that patterns in climate caused by the earth’s physiography tend to be repeatable over time,” which then can be used to create a regression model in PRISM for interpolation. (Daly, Bryant 2013) Allowing us to create maps of the past and present where there might be gaps in the data or possibly incorrect data. PRISM uses a climate-elevation regression, by incorporating elevation into the surface of the map through a digital elevation model (DEM). (Module 6 Lab Instructions)

a)     What does continuous tone symbology mean and how was it implemented in the map?

Continuous tone symbology represents continuous data. This is usually raster data with not just x and y location, but also z (ex: elevation) that represents the magnitude of x,y. Continuous data is also non discrete as it is surface data. On a map, this data uses continuous tone symbology to represent it. This is done by contour lines and sometimes hillshade shading. A contour line, is a line through all the contiguous points of y. Hillshade shading is the 3D representation of the surface of the relative data. This can be incorporated through DEM. 



Labels:

Comments

Post a Comment

Popular posts from this blog

Bivariate Choropleth and Proportional Symbols

In the first part of this lab, we used proportional symbols to represent positive and negative values in job increases/decreases in the USA.  Because there were negative values in this data set, I created a new map to "fix" the data. In this new map, I created a new field and copied the negative job loss data. I then used the Calculate field data and multiplied it by one to make it positive. Lastly, I overlaid both maps on the data and was able to accurately represent the increase and decrease of jobs in the USA by state.   In the second part of this lab, we delved into how to prepare data for a bivariate choropleth map, choose colors for the legend, and create a good layout.  I created three separate fields to analyze the data: Class Obese, Class Inactivity, and Class Final. I used the symbology tool to create 3 Quantile for the Obese and Inactivity classes and used each quantile to set the three classifications in the fields I created using the Select by Attributes...
Post a Comment
Read more

Positional Accuracy: NSSDA

 In this analysis, I compared the street and road intersect data collected for Alburquerque, NM by the City of Alburquerque and the application StreetMaps. I used an orthophoto base layer as the reference for this analysis, to compare and determine the accuracy of both the City and Streetmap layers using NSSDA procedures. The most difficult part of this analysis for me was how to determine what 20% per quadrant looks like. Because the reference map was divided into 208 quadrants, I had to determine how to subdivide all the quadrant's equality into 20%. After multiple trials and error, I decided to subdivide the entire area (208 sub-quadrants) into 4 equal-area subsections. In this way, I could do 5 random right intersection points per subsection or 20% per subsection.  Map 1: City of Albuquerque city map data.  Map 2: City of Alburquerque SteetMap data When selecting a random intersection to place the points within each quadrant, I choose a location that had data f...
Post a Comment
Read more

Infographic's

 This week was a fun and challenging week as we learned about and created infographics. It was fun to create the infographics themselves, but challenging to figure out the best methods and practices in analyzing raw data.  We used 2018 County Health Rankings National Data from countyhealthrankings.org. I chose to move forward with the two values: Unhealthy Mental Days and Premature Dealth.  I   choose these two variables because those that struggle with mental health die before their time due to depression, anxiety, and/or a combination of similar issues. Both variables are normalized by relating their value to all counties within each state in the USA. For example, the poor mental health days is normalized as the average number of reported mentally unhealthy days per month per ctizen. The normalized premature rate is the “age-adjusted years of potential life lost rate per 100,000.”  Below, I created a scatterplot of the normalized data.  I choose to k...
Post a Comment
Read more