Quantitative measurement of the environmental disturbance caused by onshore seismic surveys

References

• Aquino, C., E.T.A. Mitchard, I.M. McNicol, H. Carstairs, A. Burt, B.L. Puma Vilca, M.O. Ebanéga, et al. 2022. Reliably mapping low-intensity forest disturbance using satellite radar data. Frontiers in Forests and Global Change 5.
   PubMedGoogle Scholar
• Chen, W., X. Hu, W. Chen, Y. Hong, and M. Yang. 2018. Airborne LiDAR remote sensing for individual tree forest inventory using trunk detection-aided mean shift clustering techniques. Remote Sensing 10, no. 7.
   Web of Science ®Google Scholar
• Coops, N.C., P. Tompalski, T.R.H. Goodbody, M. Queinnec, J.E. Luther, D.K. Bolton, J.C. White, M.A. Wulder, O.R. van Lier, and T. Hermosilla. 2021. Modelling lidar-derived estimates of forest attributes over space and time: A review of approaches and future trends. Remote Sensing of Environment 260.
   PubMed Web of Science ®Google Scholar
• Crook, A., M. Naghizadeh, P. Vermeulen, D. Gagnier, and C. Reine. 2023. The use of miniaturised seismic sources for reduced environmental impact. First Break 41, no. 1: 77–84.
   Google Scholar
• Dawson, S.J., P.J. Adams, K.E. Moseby, K.I. Waddington, H.T. Kobryn, P.W. Bateman, and P.A. Fleming. 2018. Peak hour in the bush: Linear anthropogenic clearings funnel predator and prey species. Austral Ecology 43, no. 2: 159–71.
   Web of Science ®Google Scholar
• Dean, T. 2023. The application of graph theory to optimise the design of onshore 2D seismic surveys. The Leading Edge 42 no. 10: 654–724.
   Google Scholar
• Dean, T., H. Nguyen, A. Kepic, and D. Halliday. 2018. The construction of a simple portable electromagnetic vibrator from commercially available components. Geophysical Prospecting 67, no. 6: 1686–97.
   Web of Science ®Google Scholar
• Dean, T., and D. Sweeney. 2019. The use of nodal seismic acquisition systems to acquire limited-scale surveys. First Break 37, no. 1: 55–60.
   Google Scholar
• Dean, T., D. Sweeney, and J. Miller. 2023. Assessing and reducing the environmental impact of onshore geophysical surveys. Paper read at Australasian exploration geoscience conference, at Brisbane.
   Google Scholar
• Dean, T., J. Tulett, and R. Barnwell. 2018. Nodal land seismic acquisition: The next generation. First Break 36: 47–52.
   Google Scholar
• Dean, T., J. Whitfield, J. Miller, and P. Brady. 2022. An automated survey design process to reduce the environmental impact of onshore seismic surveys. The Leading Edge 41, no. 11: 786–91.
   Google Scholar
• Dickie, M., S.R. McNay, G.D. Sutherland, M. Cody, and T. Avgar. 2020. Corridors or risk? Movement along, and use of, linear features varies predictably among large mammal predator and prey species. Journal of Animal Ecology 89, no. 2: 623–34.
   PubMed Web of Science ®Google Scholar
• Dijkstra, E.W. 1959. A note on two problems in connexion with graphs. Numerische Mathematik 1: 269–71.
   Web of Science ®Google Scholar
• Embar, K., and B.P. Kotler Shomen Mukherjee. 2011. Risk management in optimal foragers: The effect of sightlines and predator type on patch use, time allocation, and vigilance in gerbils. Oikos 120, no. 11: 1657–66.
   Web of Science ®Google Scholar
• Filippelli, S.K., M.A. Lefsky, and M.E. Rocca. 2019. Comparison and integration of Lidar and photogrammetric point clouds for mapping pre-fire forest structure. Remote Sensing of Environment 224: 154–66.
   Web of Science ®Google Scholar
• Fitts, L.A., G.M. Domke, and M.B. Russell. 2022. Comparing methods that quantify forest disturbances in the United States’ national forest inventory. Environmental Monitoring and Assessment 194, no. 4: 304.
   PubMed Web of Science ®Google Scholar
• Herrmann, F.J. 2010. Randomized sampling and sparsity: Getting more information from fewer samples. Geophysics 75, no. 6: WWB173–WWB187.
   Web of Science ®Google Scholar
• Hu, X., W. Chen, and W. Xu. 2017. Adaptive mean shift-based identification of individual trees using airborne LiDAR data. Remote Sensing 9, no. 2.
   Web of Science ®Google Scholar
• Keim, J.L., R.L. Subhash, P.D. DeWitt, J.J. Fitzpatrick, and N.S. Jenni. 2019. Estimating the intensity of use by interacting predators and prey using camera traps. Journal of Animal Ecology 88, no. 5: 690–701.
   PubMed Web of Science ®Google Scholar
• Laake, A., and M. Insley. 2004. Applications of satellite imagery to seismic survey design. The Leading Edge 23, no. 10: 1062–4.
   Google Scholar
• Latham, A., M. David, M. Cecilia Latham, M.S. Boyce, and S. Boutin. 2011. Movement responses by wolves to industrial linear features and their effect on woodland caribou in northeastern Alberta. Ecological Applications 21, no. 8: 2854–65.
   Web of Science ®Google Scholar
• Laurance, W.F., M. Goosem, and S.G.W. Laurance. 2009. Impacts of roads and linear clearings on tropical forests. Trends in Ecology & Evolution 24, no. 12: 659–69.
   PubMed Web of Science ®Google Scholar
• Li, W., Q. Guo, M. Jakubowski, and M. Kelly. 2012. A new method for segmenting individual trees from the Lidar point cloud. Photogrammetric Engineering & Remote Sensing 78: 75–84.
   Web of Science ®Google Scholar
• Li, L., X. Mu, H. Jiang, F. Chianucci, R. Hu, W. Song, J. Qi, et al. 2023. Review of ground and aerial methods for vegetation cover fraction (fCover) and related quantities estimation: Definitions, advances, challenges, and future perspectives. ISPRS Journal of Photogrammetry and Remote Sensing 199: 133–56.
   Web of Science ®Google Scholar
• Liu, H., P. Dong, C. Wu, P. Wang, and M. Fang. 2021. Individual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data. Remote Sensing of Environment 258.
   Web of Science ®Google Scholar
• McNicol, I.M., T.A.M. Edward, C. Aquino, A. Burt, H. Carstairs, C. Dassi, A. Modinga Dikongo, and M.I. Disney. 2021. To what extent Can UAV photogrammetry replicate UAV LiDAR to determine forest structure? A test in two contrasting tropical forests. Journal of Geophysical Research: Biogeosciences 126, no. 12.
   Web of Science ®Google Scholar
• Millis, K. 2017. Compressive seismic imaging and source driven shooting in land acquisition: Aklaq 3D, an Alaskan North Slope case study. In SEG Technical Program Expanded Abstracts 2017, 132–135.
   Google Scholar
• Millis, K. 2018. Compressive seismic imaging: A land-acquisition case study and operational considerations. In SEG Technical Program Expanded Abstracts 2018, 112–115.
   Google Scholar
• Nagy-Reis, M., M. Dickie, A.M. Calvert, M. Hebblewhite, D. Hervieux, D.R. Seip, S.L. Gilbert, et al. 2021. Habitat loss accelerates for the endangered woodland caribou in western Canada. Conservation Science and Practice 3, no. 7.
   Google Scholar
• Neldner, V.J., M.J. Laidlaw, K.R. McDonald, M.T. Mathieson, R.I. Melzer, R. Seaton, W.J.F. McDonald, R. Hobson, and C.J. Limpus. 2017. Scientific review of the impacts of land clearing on threatened species in Queensland. Brisbane.: Queensland Government.
   Google Scholar
• Noorlandt, R., G. Drijkoningen, J. Dams, and R. Jenneskens. 2015. A seismic vertical vibrator driven by linear synchronous motors. GEOPHYSICS 80, no. 2: EEN57–EEN67.
   Web of Science ®Google Scholar
• Onishi, M., and T. Ise. 2021. Explainable identification and mapping of trees using UAV RGB image and deep learning. Scientific Reports 11, no. 1: 903.
   PubMed Web of Science ®Google Scholar
• Ourabah, A., and A. Chatenay. 2022. Unlocking ultra-high-density seismic for CCUS applications by combining nimble nodes and agile source technologies. The Leading Edge 41, no. 1: 27–33.
   Google Scholar
• Ramalho de Oliveira, L.F., H.A. Lassiter, B. Wilkinson, T. Whitley, P. Ifju, S.R. Logan, G.F. Peter, J.G. Vogel, and T.A. Martin. 2020. Moving to automated tree inventory: Comparison of UAS-derived Lidar and photogrammetric data with manual ground estimates. Remote Sensing 13, no. 1.
   Web of Science ®Google Scholar
• Serrouya, M.D.R., R. Scott McNay, and S. Boutin. 2017. Faster and farther: Wolf movement on linear features and implications for hunting behaviour. Journal of Applied Ecology 54, no. 1: 253–63.
   Web of Science ®Google Scholar
• Strimbu, B.M., A. Paun, A. Amarioarei, M. Paun, and V.F. Strimbu. 2021. Efficient synthetic generation of ecological data with preset spatial association of individuals. Canadian Journal of Forest Research 51, no. 8: 1148–65.
   Google Scholar
• Trad, D. 2009. Five-dimensional interpolation: Recovering from acquisition constraints. Geophysics 74, no. 6: V123–V132.
   Web of Science ®Google Scholar
• Vermeer, G.J.O. 2012. 3D seismic survey design. 2nd ed. Tulsa: SEG.
   Google Scholar