Geospatial Visualization

Geospatial
Visualization

School of Architecture

Dr. Timothy Norris : tnorris@miami.edu
Christopher Mader : cmader@med.miami.edu

Rethinking Image/Raster Data

Colors and values : types of data
Raster Bands : like channels in an image
> NDVI
Attribute tables : look up tables for integer rasters
Resampling : resolution and cell size
Raster math : combining multiple raster overlays
> algebra
> logic
Extraction : review
Datum transformations : review
some exercises

Colors and Values

Raster cells can contain

Integers of varying sizes (8 bit to 32 bit)
Floating point decimals (16 bit decimals)
Double floating poiunt decimals (32 bit decimals)
Remember
- 8 bits to a byte
- 1000 bytes to a kilobyte (kb)
- 1000 kb to a megabyte (MB)
- 1000 MB to a gigabyte (GB)
- 1000 GB to a terrabyte (TB)

Color is entirely a creation of the mind - visible color

Red Green Blue - RGB

Additive color model based on ‘primary’ colors
- Used on all electronic display devices
- Primary colors are closely matched to three receptors in eye
The modern computer uses numbers from 0-255 to represent each primary color
- 8 bits for each color, three colors, 24-bit true color
- Approximately 16,777,216 colors – more than we can see

Cyan Magenta Yellow Black - CMYK

Subtractive color model based on printer colors
- Also known as "process" or "four-color" system
- All printing devices use this model
- More ink 'subtracts' lightness from the white paper
- 'K' is for 'key' as the black plate in an offset press is the 'key' plate
8-bit or 16-bit information in each color 'channel'
- CMYK image files are noticeably larger than RGB image files
- way more colors than we can see ...

Hexadecimal for the Internet

The hex color system is based on the RGB model
- Used in HTML for the internet
- Is the preferred representation for color by programmers
Hexadecimal is the name for counting in base 16
- Good for computers: 2⁴ = 16
- 16 x 16 = 256 = 2⁸ ~ byte of information
- Counted from 0-15 like this:
  
  0 1 2 3 4 5 6 7 8 9 A B C D E F
A hex color might look like this: #FF00FF

rgb(255,0,255)

Red: FF = 15*1 + 15*16 = 255

Green: 00 = 0*1 + 0*16 = 0

Blue: FF = 15*1 + 15*16 = 255

Photoshop's color picker

Approximate screen color

HEX

RGB

CMYK

Color Brewer

https://colorbrewer2.org

The original ColorBrewer (v1.0) was funded by the NSF Digital Government program during 2001-02, and was designed at the GeoVISTA Center at Penn State (National Science Foundation Grant No. 9983451, 9983459, 9983461).

Attribute Tables for Raster Data
(Not Really)

Only in ArcGIS Pro and other ESRI products
Only work on Integer rasters
Actually look up tables for unique values

Resampling

Each cell or pixel in a raster dataset has an associate width and height in the coordinate system.

For projected coordinate systems this means we can calculate area based on width and height of a cell.

Resampling

Resample is similar to changing image resolution in Photoshop; the actual dimensions of the image do not change.

But when we resample the raster dataset, the dimensions of the cells change and the actual values in each cell are re-calculated (several different methods).

image from: https://gisgeography.com/raster-resampling/

Resampling Methods

nearest neighbor
categorical data; fastest method
bi-linear interpolation
continuous data; elevation, temperature
cubic convolution
continuous noisy data; radar, surface models
majority interpolation
categorical data; land cover, districts
there are more ...

see https://gisgeography.com/raster-resampling/

image credit: Cell size of raster data. ArcMap 10.8 Documentation. https://desktop.arcgis.com/en/arcmap/latest/manage-data/raster-and-images/cell-size-of-raster-data.htm

Resampling Methods

You will see these methods as options when you:

perform raster operations between two layers of different resolutions
save a raster in a different format
perform a coordinate system transformation
clip a raster image (crop)
purposefully resample to save disk or memory space

Rasterize Vector Layer and Resolution

You will also make resolution decisions when you rasterize a vector layer:

image credit: Cell size of raster data. ArcMap 10.8 Documentation. https://desktop.arcgis.com/en/arcmap/latest/manage-data/raster-and-images/cell-size-of-raster-data.htm

Raster Math and Raster Calculators

We can combine two or more raster data sets using basic math operations on coincidental cells or pixels.

image from: https://gisgeography.com/raster-resampling/

Raster Algebra Examples

Temp year 1 - Temp Year 2 = Change in Temperature
NDVI Year 1 - NDVI Year 2 = Change in Green Cover
( Temp year 1 + Temp Year 2 ) / 2 = Average Temperature
( NDVI Year 1 + NDVI Year 2 ) / 2 = Average Green Cover
Only limited by your imagination (and available data)

Relational or Logical Raster Algebra

Truth tests on raster cells
- TRUE = 1
- FALSE = 0
Examples
- Elevation (DEM) < 5ft
- Temperature > 80 Fahrenheit

image from: https://gisgeography.com/raster-resampling/

Raster Zonal Statistics

Calculate statistics for cells in defined zones of a raster (count, sum, mean, min, max, etc).

NOTE: area can be calculated with cell dimensions and a count of cells.

images from (left to right): Wei Ying (2017). How to extract raster values at point locations? ArcGIS Blog. extraction from: https://www.esri.com/arcgis-blog/products/analytics/analytics/how-to-extract-raster-values-at-point-locations/ and GIS Geography (2022). How To Use Zonal Statistics [blog]. https://gisgeography.com/zonal-statistics/ and

Raster Zonal Statistics - Examples

Calculate area of inundation scenario in a census tract - with an elevation layer count the number of pixels with an elevation of less than 5ft within each census tract.
Summarizing Rain in a Watershed – By using a precipitation raster as your value field, you can set your zone as the watersheds with a sum function.
Highest Elevation in Country – If you have an elevation raster dataset, you can run Zonal Statistics to find out its highest peak by using the maximum function.
Adding Tree Cover in an Ecozone – To find the tree cover area in an ecozone, you can run Zonal Statistics to sum up a raster land cover dataset.

Examples from: GIS Geography (2022). How To Use Zonal Statistics [blog]. https://gisgeography.com/zonal-statistics/

Extraction of Values from Raster (review)

You can extract values from raster at defined points.

For example: elevation from a DEM based on a point layer.

image from: Wei Ying (2017). How to extract raster values at point locations? ArcGIS Blog. ESRI.

Extraction of Values from Raster (review)

Sometimes more efficient to extract values from multiple rasters in one operation.

For example: elevation from a DEM, temperature, rainfall, etc; all based on one point layer.

image from: Wei Ying (2017). How to extract raster values at point locations? ArcGIS Blog. ESRI.

Datum Shift Review

image used under fair use from: https://en.wikiversity.org/wiki/File:Texas_Capitaol_Dome_Position_Shifts.gif

Datum Shift Review
NAD83 and WGS84

image from: NEI GPS - an authorized Trimble dealer.

Flood Modeling in Little River Miami GIS Data & Tutorial
Raster Operations

From UM Libraries GIS workshops
https://miami.box.com/s/4ef3q2947cku6vrwameflxz4ohbnm326
Download and unzip to a good location
- Open project with ArcGIS Pro
- Open word doc and follow instructions

Parrish (2021). Flood Modeling in the Little River Neighborhood of Miami [workshop]. University of Miami Libraries GIS Resources. https://miami.box.com/s/4ef3q2947cku6vrwameflxz4ohbnm326.

An exercise - UM Gables Campus 5ft Sealevel Rise Scenario

Start new project in GIS of your choice
Get data (from box folder)
- UM_DEM_2021_5FT.tif
- 2021_MD_CensusTracts.zip
Create a data folder inside the project and unzip all data from above

5 ft scenario

Open the DEM in your GIS project
- note projection information, size of cells, other important metadata
- make sure to understand that each cell is 5ft x 5ft or 25 sq/ft
- visualize using manual breaks: <0 | 0-5 | 5-10 | > 10
- choose a good color scheme
- explore a little
Find raster calculator (in toolbox)
- create the expression: ("UM_DEM_2021_5FT.tif" > 0) & ("UM_DEM_2021_5FT.tif" < 5)
- give the output a good file name and run tool
- visualize based on 0 and 1
- make sure to understand that 0 is either elevation < 0 or elevation > 5
- make sure to understand that 1 is either elevation > 0 or elevation < 5

Calculate Zonal Statistics

Open the Census Tracts in your project
- Remove fill color in symbology
Look for "Zonal Statistics as Table" in toolbox
- Zonal layer be census tracts using GEOID20 as the field
- Second layer will be the raster with 0 < cell < 5 showing as 1
- Select all statistics, give the output a good name, and run the tool
- open the resulting table
Calculate percentage flooded using field calculator (review)
- Open the field calculator and create a new column "percentFlooded"
- Create the expression: !SUM! / !COUNT! and run the tool
- Make sure to understand that you are calculating a percent area

Visualize Percentage Flooded

Join statistics table back to census tracts using GEOID as the join field
Visualize the percentage flooded on census tracts
Using the info tool, click on the UM Census Tract and inspect results (find percentage flooded)

Band Number	Description	Wavelength	Resolution
Band 1	Coastal / Aerosol	0.433 to 0.453 µm	30 meter
Band 2	Visible blue	0.450 to 0.515 µm	30 meter
Band 3	Visible green	0.525 to 0.600 µm	30 meter
Band 4	Visible red	0.630 to 0.680 µm	30 meter
Band 5	Near-infrared	0.845 to 0.885 µm	30 meter
Band 6	Short wavelength infrared	1.56 to 1.66 µm	30 meter
Band 7	Short wavelength infrared	2.10 to 2.30 µm	60 meter
Band 8	Panchromatic	0.50 to 0.68 µm	15 meter
Band 9	Cirrus	1.36 to 1.39 µm	30 meter
Band 10	Long wavelength infrared	10.3 to 11.3 µm	100 meter
Band 11	Long wavelength infrared	11.5 to 12.5 µm	100 meter