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| Type: | Resource | |
| Storage: | The size of this resource is 4.3 MB | |
| Created: | Apr 25, 2023 at 1:15 a.m. (UTC) | |
| Last updated: | Jan 26, 2024 at 2:49 a.m. (UTC) | |
| Citation: | See how to cite this resource | 
| Sharing Status: | Public | 
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| Views: | 2167 | 
| Downloads: | 34 | 
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Abstract
Biomass and Leaf Area Index (LAI) are crucial parameters for accurate evapotranspiration modeling. LAI is particularly useful for assessing the photosynthetic capacity of turfgrass canopies. However, there is a shortage of instruments available to measure ground-based LAI for urban turfgrass, necessitating the use of destructive methods to generate LAI input for remote-sensing-based surface energy balance models. To address this issue, turfgrass samples were collected and then their leaves were scanned. Using unsupervised classification technique, K-means, and the scanned leaves, leaf area was estimate to calculate LAI for urban turfgrass. To facilitate the process, we developed a Google Collaboratory notebook that employs the K-means algorithm for estimating leaf area.
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Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number | 
|---|---|---|
| Research Water Laboratory, Utah State University | 
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
                        
                
            
        
            
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