On the public citation graph
An efficient method for estimating dormant season grass biomass in tallgrass prairie from ultra-high spatial resolution aerial imaging produced with small unmanned aircraft systems
0 signed · 22 inferred · view as graph
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf02861083openalex-snapshot
Rise of the grassland biome, central North America
inferredcites →https://doi.org/10.1016/j.ecolind.2016.03.036openalex-snapshot
Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system
inferredcites →https://doi.org/10.1016/j.jag.2015.02.012openalex-snapshot
Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley
inferredcites →https://doi.org/10.1080/01431161.2017.1420941openalex-snapshot
A meta-analysis and review of unmanned aircraft system (UAS) imagery for terrestrial applications
inferredcites →https://doi.org/10.1097/00010694-196505000-00019openalex-snapshot
Potential Natural Vegetation of the Conterminous United States
inferredcites →https://doi.org/10.1111/j.1365-2494.1980.tb01509.xopenalex-snapshot
A critical review of remote sensing and other methods for non‐destructive estimation of standing crop biomass
inferredcites →https://doi.org/10.1111/j.1442-9993.1992.tb00790.xopenalex-snapshot
Estimating plant biomass: A review of techniques
inferredcites →https://doi.org/10.14358/pers.80.12.1151openalex-snapshot
Modeling Above-Ground Biomass in Tallgrass Prairie Using Ultra-High Spatial Resolution sUAS Imagery
inferredcites →https://doi.org/10.1674/0003-0031(2002)147[0287:eowpit]2.0.co;2openalex-snapshot
Expansion of Woody Plants in Tallgrass Prairie: A Fifteen-year Study of Fire and Fire-grazing Interactions
inferredcites →https://doi.org/10.1894/fmo-19.1openalex-snapshot
Tallgrass prairie vegetation response to spring fires and bison grazing
inferredcites →https://doi.org/10.2134/agronj1997.00021962008900040020xopenalex-snapshot
Determination of Pasture Biomass Using Four Indirect Methods
inferredcites →https://doi.org/10.2307/3899622openalex-snapshot
Long-Term Effects of Annual Burning at Different Dates in Ungrazed Kansas Tallgrass Prairie
inferredcites →https://doi.org/10.2307/4003528openalex-snapshot
Estimating Herbage Standing Crop with Visual Obstruction in Tallgrass Prairie
inferredcites →https://doi.org/10.3390/rs10010089openalex-snapshot
Object-Based Mangrove Species Classification Using Unmanned Aerial Vehicle Hyperspectral Images and Digital Surface Models
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4617637openalex-extracted
Supplement to the Article: Influence of spatial and temporal variability on the performance of machine learning-based pasture biomass prediction
inferred← citeshttps://doi.org/10.1007/s11119-023-10079-9openalex-snapshot
Prediction of pasture yield using machine learning-based optical sensing: a systematic review
inferred← citeshttps://doi.org/10.1007/s41064-024-00322-xopenalex-snapshot
Assessing the Effect of Field Disturbances On Biomass Estimation in Grasslands Using UAV-Derived Canopy Height Models
inferred← citeshttps://doi.org/10.1016/j.ecoinf.2025.103361openalex-snapshot
Forage biomass estimation using UAV-based remote sensing and machine learning: A tool for assessing management practices
inferred← citeshttps://doi.org/10.3390/rs14122903openalex-snapshot
Review of Remote Sensing Applications in Grassland Monitoring
inferred← citeshttps://doi.org/10.3390/rs15030639openalex-snapshot
A Review of Estimation Methods for Aboveground Biomass in Grasslands Using UAV
inferred← citeshttps://doi.org/10.3390/rs15245714openalex-snapshot
Pasture Biomass Estimation Using Ultra-High-Resolution RGB UAVs Images and Deep Learning
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