Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification Techniques
ABSTRACT In much of the northern Great Basin of the western United States, rangelands, and semi‐arid ecosystems invaded by exotic annual grasses such as cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput‐medusae) are experiencing an increasingly short fire cycle, which is compounding an...
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| Format: | Article |
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Wiley
2025-01-01
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| Series: | Ecology and Evolution |
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| Online Access: | https://doi.org/10.1002/ece3.70883 |
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| author | Josh Enterkine Ahmad Hojatimalekshah Monica Vermillion Thomas Van Der Weide Sergio A. Arispe William J. Price April Hulet Nancy F. Glenn |
| author_facet | Josh Enterkine Ahmad Hojatimalekshah Monica Vermillion Thomas Van Der Weide Sergio A. Arispe William J. Price April Hulet Nancy F. Glenn |
| author_sort | Josh Enterkine |
| collection | DOAJ |
| description | ABSTRACT In much of the northern Great Basin of the western United States, rangelands, and semi‐arid ecosystems invaded by exotic annual grasses such as cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput‐medusae) are experiencing an increasingly short fire cycle, which is compounding and persistent. Improving and expanding ground‐based field methods for measuring the above‐ground biomass (AGB) may enable more sample collections across a landscape and over succession regimes and better harmonize with other remote sensing techniques. Developments and increased adoption of unoccupied aerial systems (UAS) and instrumentation for vegetation monitoring enable greater understanding of vegetation in many ecosystems. Research to understand the relationship of traditional field measurements with remotely sensed data in rangeland environments is growing rapidly, and there is increasing interest in the use of aerial platforms to quantify AGB and fine‐fuel load at pasture and landscape scales. Our study uses relatively inexpensive handheld photography with custom quadrat sampling frames to collect and automatically reconstruct 3D models of the vegetation within 0.2 m2 quadrats (n = 288). Next, we examine the relationship between volumetric estimates of vegetation with biomass. We found that volumes calculated with 0.5 cm voxel sizes (0.125 cm3) most closely represented the range of biomass weights. We further develop methods to classify ground points, finding a 2% reduction in predictive ability compared with validation ground surface reconstructions. This finding is significant given that our study site is characterized by a dense litter layer covering the ground surface, making reconstruction challenging. Overall, our best reconstruction workflow had an R2 of 0.42, further emphasizing the importance of high‐resolution imagery and reconstruction techniques. Ultimately, we conclude that more work is needed of increasing extents (such as from UAS) to better understand and constrain uncertainties in volumetric estimations of biomass in ecosystems with high amounts of invasive annual grasses and fine‐fuel litter. |
| format | Article |
| id | doaj-art-b467255633314062b0856d5d39d195a3 |
| institution | Kabale University |
| issn | 2045-7758 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj-art-b467255633314062b0856d5d39d195a32025-01-29T05:08:42ZengWileyEcology and Evolution2045-77582025-01-01151n/an/a10.1002/ece3.70883Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification TechniquesJosh Enterkine0Ahmad Hojatimalekshah1Monica Vermillion2Thomas Van Der Weide3Sergio A. Arispe4William J. Price5April Hulet6Nancy F. Glenn7Boise State University Department of Geosciences Boise Idaho USABoise State University Department of Geosciences Boise Idaho USAUSDA US Forest Service, Forest Health Protection Region 4 Boise Idaho USABoise State University Department of Geosciences Boise Idaho USAOregon State University Extension Service‐Malheur County Oregon State University Ontario Oregon USAOregon State University Extension Service‐Baker & Union Counties Oregon State University Baker City Oregon USAPlant & Wildlife Sciences Brigham Young University Provo Utah USABoise State University Department of Geosciences Boise Idaho USAABSTRACT In much of the northern Great Basin of the western United States, rangelands, and semi‐arid ecosystems invaded by exotic annual grasses such as cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput‐medusae) are experiencing an increasingly short fire cycle, which is compounding and persistent. Improving and expanding ground‐based field methods for measuring the above‐ground biomass (AGB) may enable more sample collections across a landscape and over succession regimes and better harmonize with other remote sensing techniques. Developments and increased adoption of unoccupied aerial systems (UAS) and instrumentation for vegetation monitoring enable greater understanding of vegetation in many ecosystems. Research to understand the relationship of traditional field measurements with remotely sensed data in rangeland environments is growing rapidly, and there is increasing interest in the use of aerial platforms to quantify AGB and fine‐fuel load at pasture and landscape scales. Our study uses relatively inexpensive handheld photography with custom quadrat sampling frames to collect and automatically reconstruct 3D models of the vegetation within 0.2 m2 quadrats (n = 288). Next, we examine the relationship between volumetric estimates of vegetation with biomass. We found that volumes calculated with 0.5 cm voxel sizes (0.125 cm3) most closely represented the range of biomass weights. We further develop methods to classify ground points, finding a 2% reduction in predictive ability compared with validation ground surface reconstructions. This finding is significant given that our study site is characterized by a dense litter layer covering the ground surface, making reconstruction challenging. Overall, our best reconstruction workflow had an R2 of 0.42, further emphasizing the importance of high‐resolution imagery and reconstruction techniques. Ultimately, we conclude that more work is needed of increasing extents (such as from UAS) to better understand and constrain uncertainties in volumetric estimations of biomass in ecosystems with high amounts of invasive annual grasses and fine‐fuel litter.https://doi.org/10.1002/ece3.70883biomassfine fuelsmedusaheadrangelandSfM |
| spellingShingle | Josh Enterkine Ahmad Hojatimalekshah Monica Vermillion Thomas Van Der Weide Sergio A. Arispe William J. Price April Hulet Nancy F. Glenn Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification Techniques Ecology and Evolution biomass fine fuels medusahead rangeland SfM |
| title | Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification Techniques |
| title_full | Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification Techniques |
| title_fullStr | Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification Techniques |
| title_full_unstemmed | Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification Techniques |
| title_short | Voxel Volumes and Biomass: Estimating Vegetation Volume and Litter Accumulation of Exotic Annual Grasses Using Automated Ultra‐High‐Resolution SfM and Advanced Classification Techniques |
| title_sort | voxel volumes and biomass estimating vegetation volume and litter accumulation of exotic annual grasses using automated ultra high resolution sfm and advanced classification techniques |
| topic | biomass fine fuels medusahead rangeland SfM |
| url | https://doi.org/10.1002/ece3.70883 |
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