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Volumetrics 1

Introduction

Unmanned Aircraft Systems have become a powerful tool for collecting high-resolution geospatial data. In this lab, I conducted a volumetric analysis of aggregate piles at a fluvial mining site using UAS-derived data within ArcGIS Pro. The objective was to calculate the volume of material using raster-based surface analysis tools while gaining hands-on experience with workflows such as clipping, resampling, and surface volume calculations. This project emphasized both the technical process and the importance of accurate data outputs.

Importance to the UAS Industry

Volumetric analysis is one of the most valuable applications of UAS technology, particularly in industries such as mining, construction, and environmental monitoring. Traditional surveying methods can be time-consuming, labor-intensive, and less efficient when dealing with large or uneven terrain. UAS allows for rapid data collection with high spatial resolution, improving both accuracy and efficiency.

In the UAS industry, being able to quickly and accurately calculate stockpile volumes is critical for inventory management, cost estimation, and operational planning. Additionally, UAS data enables repeatable measurements over time, allowing companies to monitor changes, track material movement, and improve decision-making processes. This capability highlights why geospatial analysis skills are increasingly essential for UAS professionals.

Steps and Process

1. Data Preparation

Transferred the Wolfcreek geodatabase into my temp folder.

Reviewed the dataset in ArcGIS Pro using Arc Catalog to understand available data layers and properties.

2. Tool Familiarization

Studied key geoprocessing tools including:

Extract by Mask (used to clip raster data to a defined area)

Resample (used to adjust raster resolution)

Surface Volume (used to calculate volume based on elevation data)

3. Raster Clipping (Extract by Mask)

Created a polygon feature class outlining each aggregate pile.

Used the Extract by Mask tool to isolate each pile while ensuring no data was excluded or contaminated by nearby features.

4. Volume Calculation (Surface Volume Tool)

Applied the Surface Volume tool to each clipped raster dataset.

Determined elevation values and calculated the volume of each aggregate pile.

Recorded outputs in a table including elevation surface and total volume.

5. Resampling the Data

Resampled the Digital Surface Model (DSM) to a 10 cm resolution.

Compared how resolution changes impacted volume calculations and processing performance.

6. Visualization and Mapping

Created map layouts displaying the clipped piles and results.

Included essential cartographic elements such as scale, legend, and coordinate system information.

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7. Workflow Development

Designed a workflow chart outlining the full process from data preparation to final volume output.

Conclusion and Lessons Learned

This lab demonstrated the effectiveness of UAS data in performing accurate and efficient volumetric analysis. One of the key takeaways is the importance of proper data preparation and clipping, as errors in defining the area of interest can significantly impact volume results. Additionally, resolution plays a major role. Higher resolution data provides more detail but requires greater processing power, while lower resolution data may reduce accuracy.

I also learned that external factors such as vegetation, shadows, or other surface objects can introduce errors into volumetric calculations. This highlights the need for careful data collection and preprocessing. Furthermore, hardware limitations can affect processing time and performance, making cloud-based solutions a valuable alternative for handling large datasets.

Overall, this project reinforced the critical role of UAS in modern geospatial analysis and provided practical experience with tools and workflows that are directly applicable in the industry. The ability to efficiently calculate and analyze volumes using UAS data is a highly relevant skill that will continue to grow in importance across multiple fields.

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