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Week 12 wolf pave

1. Introduction

How you present UAS data matters almost as much as the data itself. A drone can capture high-quality imagery and create raster products like an orthomosaic and DSM, but those products are not automatically useful unless they are turned into clear, readable maps. One of the most desired skills in the UAS world is the ability to take UAS data and put it into the context of a Geographic Information System (GIS) software package for further analysis and use. This lab built on previous geospatial concepts by focusing on cartographic fundamentals and learning how to create functional maps using ArcGIS Pro.

Another major idea in this lab is that there is a difference between a picture taken from the air and a proper map. A map needs elements that communicate scale, orientation, location, and data source information. Without those pieces, it becomes hard for someone else to understand what they are looking at or trust the data. For this lab, the goal was to work with the Wolf Paving dataset, explore raster visualization and analysis tools in ArcGIS Pro, and then create multiple map layouts using the required cartographic criteria.

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2. Objectives

The objectives of this lab were to:

Apply cartographic fundamentals to UAS-derived data products

Organize and manage UAS project files correctly

Use ArcGIS Pro tools to load, visualize, and analyze raster layers (DSM + orthomosaic)

Build pyramids and calculate statistics for raster datasets

Generate hillshades and improve DSM readability using symbology and transparency

Create export-ready map layouts that include all required map elements:

North arrow

Scale bar

Locator map (when required)

Legend (especially for GCP points)

Watermark

Data sources and metadata (sensor, altitude, platform, pilot)

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3. Background: Map Fundamentals + Metadata

This lab emphasized that every map should include core elements that help the reader interpret the information correctly. Required map elements included:

North Arrow: shows orientation so the viewer knows direction

Scale Bar: allows the viewer to understand real-world distance

Locator Map: shows where the site is in a larger context (state/region)

Watermark: shows authorship (who created it)

Data sources + metadata: documents how and when the data was collected and what tools were used

Metadata was also emphasized as “not exciting but crucial.” In UAS mapping, metadata is what keeps your data usable later. A good habit is keeping a metadata text file inside the same folder as the dataset so it stays attached to the project and doesn’t get lost.

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4. Software and Data

Software Used

ArcGIS Pro

Data Used

Wolfpaving_X5_processed dataset from the class server folder (AT309ClassData)

Raster products used in this lab included:

Orthomosaic

DSM

Hillshade layers (generated in lab)

Ground control / GCP points (used in map layouts)

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5. Methods / Procedure (Workflow)

5.1 Data Copy and Folder Setup

Created a folder in C:\temp named: username_UASmapdata

Navigated to the server: AT309ClassData → Wolfpaving_X5_processed

Copied the full Wolfpaving_X5_processed folder into the created local folder.

After finishing the lab, copied this folder into the student folder because the temp folder can be wiped.

Reason for this step: UAS raster data is large, and projects break easily if data is moved later. Keeping the project + data in one organized location prevents broken paths and keeps workflow consistent.

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5.2 Create ArcGIS Pro Project and Connect Data

Opened ArcGIS Pro and created a new project inside the same folder that contained the Wolf Paving data.

Established:

Folder connection (to the lab folder)

Database connection (to access rasters)

Added raster datasets (DSM and orthomosaic) into the map using the Catalog pane / Add Data.

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5.3 Navigating ArcGIS Pro + Raster Visualization

During the lab, several basic navigation and raster visualization skills were practiced:

Turning layers on/off to compare products

Zooming and panning around the site

Zoom-to-layer to quickly find raster extent

Checking layer properties (metadata and coordinate system)

Adjusting raster symbology:

mask settings

color scheme / color ramps

Using the Swipe Tool to compare:

DSM vs orthomosaic

hillshade vs DSM overlay

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5.4 Raster Processing: Pyramids and Statistics

Pyramids and statistics were created for each dataset:

Build Pyramids

Calculate Statistics

This step improves performance and improves how the raster displays with symbology. For DSM work especially, statistics help ArcGIS know the value distribution so the stretching and color ramp display correctly.

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5.5 Hillshade Creation + DSM Overlay

Several hillshades were generated:

Traditional hillshade

Multi-directional hillshade

Then the DSM was:

set to a color ramp of choice

given transparency

layered on top of the hillshade

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This is a standard method to make elevation products easier to interpret because hillshade gives relief detail and DSM color gives height information.

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5.6 Map Layout Creation and Export

Layouts were created and exported as standalone images. Layout tools used included:

choosing portrait vs landscape

adding a mapframe

adding locator maps (when required)

creating detailed insets (for GCP points)

adding a reference grid (for one layout)

inserting:

north arrow

scale bar

legend (for GCP points)

watermark

metadata/data source text

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exporting to image format for submission/e-portfolio

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6. Results and Discussion

This lab produced several major outputs:

Shaded DSM with transparent DSM overlay

Orthomosaic map with GCP points and detailed inset views

Orthomosaic map with a reference grid

Metadata table and DSM descriptive statistics table (included below)

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These outputs demonstrate how the same dataset can be displayed and interpreted in different ways depending on map purpose. The DSM products helped show elevation patterns and surface relief, while the orthomosaic helped confirm real-world features like surfaces, objects, and textures.

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Part 1: Critical Thought Questions (Included)

1) Why are proper cartographic skills essential in working with UAS data?

Good cartography turns raw drone imagery into something useful. Without things like a scale bar, north arrow, and metadata, the viewer can’t properly understand what they’re looking at. Proper map design makes the data more reliable and easier for others to use.

2) What are the fundamentals of turning either a drawing or an aerial image into a map?

To make an image into a real map, it must be georeferenced, have a projection, and include map elements like a scale bar, north arrow, legend, and metadata. If those things aren’t included, it stays just a picture and not a usable map.

3) What can spatial patterns of data tell the reader about UAS data? Provide several examples.

Spatial patterns help show trends and relationships in the data. For example, elevation changes in a DSM show slopes, drainage, or piles of material. Vegetation maps can show crop health patterns or stressed areas. Thermal maps can show heat loss or overheating equipment.

4) How does presentation format and cartographically correct maps relate to future projects and jobs?

In most UAS careers, the map is the final product given to a client or supervisor. If the map looks sloppy or doesn’t follow standards, it makes you look unprofessional. Good map presentation shows attention to detail and makes it easier for others to trust and use your work.

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Part 2: Working With the Data (Included)

1) What key characteristics should go into folder and file naming conventions?

Good folder and file names should include the project name, the date, and what the file actually is (DSM, orthomosaic, raw images, etc.). It helps to use the same format every time so you can find things later. Using underscores instead of spaces is also better so software doesn’t break the file path.

2) Why is file management so key in working with UAS data? How does this relate to the metadata?

UAS projects create tons of files, and if they aren’t organized correctly, you lose track of where everything is. File management makes sure the right metadata stays with the right data. If you lose metadata, you also lose important details like flight altitude, coordinate system, or sensor type, which makes the data less useful.

3) What key forms of metadata should be associated with every UAS mission?

Every UAS dataset should have the drone type and camera used, flight altitude, and date and time. GPS/GNSS accuracy or base station info, coordinate system and projection, pilot name and mission location, and any notes about problems or weather during the flight.

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Metadata Table (Insert Into Report)

Table 5

Table 5

Metadata Item

Example / Notes

Project / Site Name

Wolf Paving / Wolf Creek

Data Products

Orthomosaic, DSM

Platform

[Enter if listed in dataset]

Sensor

[Enter if listed in dataset]

Flight Altitude

[Enter if provided]

Date + Time

[Enter if provided]

GPS/GNSS

[Onboard or base station if provided]

Coordinate System

[From layer properties]

Projection

[From layer properties]

Pilot

[Enter if known]

Notes

Weather, issues, shadows, etc.

There are no rows in this table

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4) What basemap did you use? Why?

I used the Topographic basemap because it matched the orthomosaic visually and made it easier to confirm the map lined up correctly. It also helps provide context around the site.

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Descriptive Statistics (DSM)

5) What is the purpose of pyramids and calculate statistics?

These tools help the raster display and perform better in ArcGIS Pro. Pyramids speed up loading and zooming, and statistics help ArcGIS Pro understand the raster value distribution. That makes DSM symbology more accurate and prevents the DSM from looking washed out or flat.

DSM Statistics Table (Provided)

Table 15

Table 15

Band Name

Minimum

Maximum

Mean

Std. Deviation

Band_1

281.0470886230469

323.0886535644531

296.96691083562587

4.178350237820167

There are no rows in this table

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6) Why might knowing Cell Size, Units, Projection, Highest Elevation, Lowest Elevation be important?

Cell size tells you how detailed the data is. The projection makes sure the map lines up with other layers. The elevation values help catch errors—if the elevations are way too high or low, something is wrong. These things all affect how accurate your measurements and analysis will be.

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7) What is the difference between a DSM and DEM?

A DSM shows the ground and everything on top of it (trees, buildings, etc.). A DEM has those things removed and only shows bare earth. UAS photogrammetry usually produces DSMs unless you filter the data.

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8) What does hillshading do toward visualizing relief and topography?

Hillshading makes the terrain look 3-D by adding fake shadows. It makes it easier to see hills, dips, slopes, piles, and other height changes that are hard to see in regular color ramps.

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9) How does the orthomosaic relate to what you see in the shaded relief of the DSM?

The orthomosaic shows real-world color and texture, while the DSM shows height. When you compare them, you can see what the surface is made of and how tall it is. For example, a pile of gravel looks like a mound in the orthomosaic and also shows up as a raised area in the shaded DSM.

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Part 3: Map Layout Products (Placeholders)

Below are the required exported layouts. Insert your exported images and captions here.

Map 1: Shaded DSM with Transparent DSM Overlay + Locator Map

Figure 1. Shaded DSM with transparent DSM overlay. Locator inset shows Wolf Paving location within Wisconsin.

Map 2: Orthomosaic Map with GCP Points + Detailed Insets

Figure 2. Orthomosaic map showing GCP point locations and detailed inset views for each point.

Map 3: Orthomosaic Layout with Reference Grid

Figure 3. Orthomosaic layout including reference grid for improved spatial referencing.

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Part 4: Final Orthomosaic Product Notes (Not Included in This Submission)

For the final data products assignment, proper maps will be created for each orthomosaic image. These maps will include:

Locator inset

North arrow + scale bar

Watermark

Data sources and metadata

Reference grid optional

No DSM required

No GCP points required

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Conclusion / Summary

This lab reinforced that cartography is not just making maps look “nice,” but making them accurate, understandable, and usable for other people. Using ArcGIS Pro, I learned how to organize UAS data, apply metadata standards, visualize and compare DSM and orthomosaic datasets, generate hillshades, and create multiple export-ready layouts. The DSM and hillshade products helped visualize elevation and relief, while the orthomosaic provided real-world detail that helped interpret what caused height changes in the DSM. Overall, the skills practiced in this lab connect directly to real UAS careers because the map is often the final deliverable a client or supervisor uses to make decisions.

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