Evaluating Field Sampling Design and LiDAR-Based Approaches for Woody Vegetation Assessment in Reclaimed Wellsite Certification.
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| Title: | Evaluating Field Sampling Design and LiDAR-Based Approaches for Woody Vegetation Assessment in Reclaimed Wellsite Certification. |
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| Authors: | Van Dongen, Angeline1 (AUTHOR), Movchan, Dmytro1 (AUTHOR), Selvaraj, Charumitha1 (AUTHOR), Degenhardt, Dani1 (AUTHOR) dani.degenhardt@nrcan-rncan.gc.ca |
| Source: | Remote Sensing. May2026, Vol. 18 Issue 10, p1464. 28p. |
| Subjects: | LIDAR, Statistical sampling, Remote sensing, Woody plants, Field research, Restoration ecology |
| Geographic Terms: | Alberta |
| Abstract: | Highlights: What are the main findings? Subjective plot placement overestimated woody stem density compared to random plots at sites with heterogenous vegetation recovery. LiDAR data provided valuable spatial information but underestimated woody stem density, particularly at sites with high stem density. What are the implications of the main findings? Random sampling provides a more representative assessment of site conditions, if site-level rather than plot-level criteria are emphasized. LiDAR data may be a useful preliminary recovery screening tool or used to inform targeted field sampling. Responsible resource development in Alberta requires the reclamation of disturbed lands to achieve equivalent land capability to pre-disturbance conditions. Vegetation assessments on reclaimed wellsites and oil sand exploration (OSE) sites currently rely on plots placed in areas deemed representative using professional judgement, which may introduce sampling bias. This study compared woody vegetation attributes derived from conventionally placed plots with those from randomly placed plots on certified reclaimed sites. Furthermore, increased sampling intensity was evaluated on a subset of sites. Site-level plot-based estimates were also compared with estimates from uncrewed aerial vehicle light detection and ranging (UAV-LiDAR) and airborne laser scanning (ALS). Woody stem density and height estimates from random and judgment-based plots were generally comparable; however, on sites with spatially heterogeneous recovery, judgment-based placement tended to overestimate woody stem density relative to larger-area sampling. LiDAR data captured spatial patterns of woody vegetation but underestimated stem densities, particularly on high-density, clustered sites. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? Subjective plot placement overestimated woody stem density compared to random plots at sites with heterogenous vegetation recovery. LiDAR data provided valuable spatial information but underestimated woody stem density, particularly at sites with high stem density. What are the implications of the main findings? Random sampling provides a more representative assessment of site conditions, if site-level rather than plot-level criteria are emphasized. LiDAR data may be a useful preliminary recovery screening tool or used to inform targeted field sampling. Responsible resource development in Alberta requires the reclamation of disturbed lands to achieve equivalent land capability to pre-disturbance conditions. Vegetation assessments on reclaimed wellsites and oil sand exploration (OSE) sites currently rely on plots placed in areas deemed representative using professional judgement, which may introduce sampling bias. This study compared woody vegetation attributes derived from conventionally placed plots with those from randomly placed plots on certified reclaimed sites. Furthermore, increased sampling intensity was evaluated on a subset of sites. Site-level plot-based estimates were also compared with estimates from uncrewed aerial vehicle light detection and ranging (UAV-LiDAR) and airborne laser scanning (ALS). Woody stem density and height estimates from random and judgment-based plots were generally comparable; however, on sites with spatially heterogeneous recovery, judgment-based placement tended to overestimate woody stem density relative to larger-area sampling. LiDAR data captured spatial patterns of woody vegetation but underestimated stem densities, particularly on high-density, clustered sites. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18101464 |
