A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA
The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/5/2/25 |
| _version_ | 1827695127321116672 |
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| author | Brandon Crawford Erika Swanson Emily Schultz-Fellenz Adam Collins Julian Dann Emma Lathrop Damien Milazzo |
| author_facet | Brandon Crawford Erika Swanson Emily Schultz-Fellenz Adam Collins Julian Dann Emma Lathrop Damien Milazzo |
| author_sort | Brandon Crawford |
| collection | DOAJ |
| description | The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions. |
| first_indexed | 2024-03-10T12:20:09Z |
| format | Article |
| id | doaj.art-481092051f1f423c8d7635cb085bf366 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-10T12:20:09Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-481092051f1f423c8d7635cb085bf3662023-11-21T15:31:34ZengMDPI AGDrones2504-446X2021-04-01522510.3390/drones5020025A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USABrandon Crawford0Erika Swanson1Emily Schultz-Fellenz2Adam Collins3Julian Dann4Emma Lathrop5Damien Milazzo6Earth Systems Observations Group (EES-14), Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM 87544, USAEarth Systems Observations Group (EES-14), Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM 87544, USAEarth Systems Observations Group (EES-14), Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM 87544, USAEarth Systems Observations Group (EES-14), Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM 87544, USAEarth Systems Observations Group (EES-14), Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM 87544, USAEarth Systems Observations Group (EES-14), Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM 87544, USAEarth Systems Observations Group (EES-14), Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM 87544, USAThe use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.https://www.mdpi.com/2504-446X/5/2/25structure from motion (SFM)global securitychange detectionUASunderground explosions |
| spellingShingle | Brandon Crawford Erika Swanson Emily Schultz-Fellenz Adam Collins Julian Dann Emma Lathrop Damien Milazzo A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA Drones structure from motion (SFM) global security change detection UAS underground explosions |
| title | A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA |
| title_full | A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA |
| title_fullStr | A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA |
| title_full_unstemmed | A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA |
| title_short | A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA |
| title_sort | new method for high resolution surface change detection data collection and validation of measurements from uas at the nevada national security site nevada usa |
| topic | structure from motion (SFM) global security change detection UAS underground explosions |
| url | https://www.mdpi.com/2504-446X/5/2/25 |
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