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geemaee macro  (SAS institute)


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    SAS institute geemaee macro
    Geemaee Macro, supplied by SAS institute, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/geemaee macro/product/SAS institute
    Average 96 stars, based on 1 article reviews
    geemaee macro - by Bioz Stars, 2026-05
    96/100 stars

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    Image Search Results


    Spatial distribution of point cloud density (number of points per 0.5 m grid) for four LiDAR sensors: UAV-LiDARs (Explorer and Voyager) and HLSs (TrionS1 and Hovermap-ST). Warmer colors indicate higher point densities on a logarithmic scale. Each sensor exhibits distinct spatial coverage and density gradients reflecting differences in scanning geometry and platform motion.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Evaluating UAV and Handheld LiDAR Point Clouds for Radiative Transfer Modeling Using a Voxel-Based Point Density Proxy

    doi: 10.3390/s26020590

    Figure Lengend Snippet: Spatial distribution of point cloud density (number of points per 0.5 m grid) for four LiDAR sensors: UAV-LiDARs (Explorer and Voyager) and HLSs (TrionS1 and Hovermap-ST). Warmer colors indicate higher point densities on a logarithmic scale. Each sensor exhibits distinct spatial coverage and density gradients reflecting differences in scanning geometry and platform motion.

    Article Snippet: Four different LiDAR sensors were employed to capture forest structural information: two UAV-LiDAR (Explorer and Voyager, YellowScan SAS, Saint-Clément-de-Rivière, France) and two HLSs (Hovermap-ST, Emesent Pty Ltd., Milton, QLD, Australia; Trion S1, FJD Dynamics, Singapore).

    Techniques:

    Relationship between voxel size (20, 50, 100, and 200 cm) and correlation coefficient ( r ) between simulated radiance and Sentinel-2 NIR reflectance for each LiDAR sensor. UAV-LiDAR (Explorer and Voyager) maintained relatively high and stable correlations across voxel sizes, whereas HLSs (TrionS1 and Hovermap-ST) showed a marked decline in correlation at coarsest voxel resolution (200 cm).

    Journal: Sensors (Basel, Switzerland)

    Article Title: Evaluating UAV and Handheld LiDAR Point Clouds for Radiative Transfer Modeling Using a Voxel-Based Point Density Proxy

    doi: 10.3390/s26020590

    Figure Lengend Snippet: Relationship between voxel size (20, 50, 100, and 200 cm) and correlation coefficient ( r ) between simulated radiance and Sentinel-2 NIR reflectance for each LiDAR sensor. UAV-LiDAR (Explorer and Voyager) maintained relatively high and stable correlations across voxel sizes, whereas HLSs (TrionS1 and Hovermap-ST) showed a marked decline in correlation at coarsest voxel resolution (200 cm).

    Article Snippet: Four different LiDAR sensors were employed to capture forest structural information: two UAV-LiDAR (Explorer and Voyager, YellowScan SAS, Saint-Clément-de-Rivière, France) and two HLSs (Hovermap-ST, Emesent Pty Ltd., Milton, QLD, Australia; Trion S1, FJD Dynamics, Singapore).

    Techniques: