Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles
Abstract
:1. Introduction
1.1. Overview
1.2. Archaeological Background
1.2.1. Camp Hill
1.2.2. Shelford Priory
1.3. Background Theory
Aerial Photography in Archaeology
2. Materials and Methods
2.1. UAV Platform and Sensors
2.1.1. Flight Parameters
2.1.2. Ground Control Targets
2.2. Camp Hill
2.3. Shelford Priory
2.4. Post-Flight Image Processing
2.4.1. Camp Hill
2.4.2. Shelford Priory
2.5. Analytical Processing
2.5.1. Local Pre-Processing
2.5.2. Advanced Processing
3. Results and Discussion
3.1. Multisensor Ground Control
3.2. Camp Hill
3.3. Shelford Priory
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Survey | Products | Area (ha) | GSD (m) | GCP No. | RMSE X (m) | RMSE Y (m) | RMSE Z (m) | RMSE XYZ (m) |
---|---|---|---|---|---|---|---|---|
Camp Hill June 2018 | ||||||||
SODA | RGB*; DSM | 22.7 | 0.017 | n.a. | n.d. | n.d. | n.d. | n.d. |
Sequoia | G R RE NIR*; NDVI | 25.0 | 0.084 | n.a. | n.d. | n.d. | n.d. | n.d. |
TM | Thermal IR*; T (°C) | 24.3 | 0.144 | n.a. | n.d. | n.d. | n.d. | n.d. |
Camp Hill October 2018 | ||||||||
SODA | RGB*; DSM | 25.6 | 0.018 | 4 | 0.017 | 0.007 | 0.005 | 0.01 |
Sequoia | G R RE NIR*; NDVI | 29.1 | 0.081 | 4 | 0.012 | 0.004 | 0.011 | 0.008 |
TM | Thermal IR*; T (°C) | 21.9 | 0.136 | 4 | n.d. | n.d. | n.d. | n.d. |
Shelford Priory July 2018 | ||||||||
SODA | RGB*; DSM | 7.9 | 0.017 | 6 | 0.018 | 0.017 | 0.016 | 0.017 |
Shelford Priory May 2019 | ||||||||
SODA | RGB*; DSM | 7.1 | 0.017 | 6 | 0.013 | 0.015 | 0.012 | 0.014 |
Canon | G R RE NIR*; NDVI | 8.1 | 0.026 | 6 | 0.015 | 0.024 | 0.013 | 0.017 |
Sequoia | G R RE NIR*; NDVI | 9.0 | 0.083 | 6 | 0.008 | 0.012 | 0.008 | 0.009 |
TM | Thermal IR*; T (°C) | 11.1 | 0.144 | 4 | 0.047 | 0.116 | 0.117 | 0.087 |
Feature | Mean Temperature (°C) | Standard Deviation |
---|---|---|
Background field (grass) | 26.9 | 0.69 |
Black material | 30.1 | 0.63 |
Foil | 17.8 | 1.78 |
Survey | Coefficient Estimates | Standard Error | t-Statistic | p-Value |
---|---|---|---|---|
Camp Hill June 2018 | ||||
α (intercept) | 22.281 | 0.121 | 184.05 | 0 |
β (slope) | 0.020 | 0.002 | 9.438 | 7.331e−20 |
Camp Hill October 2018 | ||||
α (intercept) | 17.331 | 0.090 | 191.89 | 0 |
β (slope) | 0.027 | 0.002 | 16.636 | 2.16e−50 |
Feature | Red | s.d. | Green | s.d. | Blue | s.d. |
---|---|---|---|---|---|---|
Background field | 160.89 | 13.85 | 155.61 | 10.71 | 110.44 | 12.28 |
Priory wall | 213.03 | 12.24 | 178.09 | 10.38 | 140.47 | 11.84 |
Circular feature | 210.06 | 9.25 | 175.50 | 8.30 | 146.12 | 8.62 |
West range | 211.22 | 10.51 | 182.49 | 10.29 | 155.82 | 10.91 |
Building to south | 209.36 | 16.21 | 185.00 | 15.66 | 151.47 | 18.12 |
Feature | Mean Temperature (°C) | Standard Deviation |
---|---|---|
Background field | 26.45 | 0.33 |
Priory wall | 28.10 | 0.37 |
Circular feature | 30.92 | 0.46 |
West range | 31.14 | 0.78 |
Building to south | 26.80 | 0.25 |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Brooke, C.; Clutterbuck, B. Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles. Remote Sens. 2020, 12, 41. https://doi.org/10.3390/rs12010041
Brooke C, Clutterbuck B. Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles. Remote Sensing. 2020; 12(1):41. https://doi.org/10.3390/rs12010041
Chicago/Turabian StyleBrooke, Christopher, and Ben Clutterbuck. 2020. "Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles" Remote Sensing 12, no. 1: 41. https://doi.org/10.3390/rs12010041
APA StyleBrooke, C., & Clutterbuck, B. (2020). Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles. Remote Sensing, 12(1), 41. https://doi.org/10.3390/rs12010041