scholarly journals Remote and Close Range Sensing for the Automatic Identification and Characterization of Archaeological Looting. The Case of Peru

2021 ◽  
Vol 4 (1) ◽  
pp. 126-144
Author(s):  
Nicola Masini ◽  
Rosa Lasaponara
Keyword(s):  
Automatic Identification ◽  
Range Sensing ◽  
Close Range ◽  
Identification And Characterization

scholarly journals Automatic identification and characterization of the epiretinal membrane in OCT images

2019 ◽  
Vol 10 (8) ◽  
pp. 4018 ◽  
Author(s):  
Sergio Baamonde ◽  
Joaquim de Moura ◽  
Jorge Novo ◽  
Pablo Charlón ◽  
Marcos Ortega
Keyword(s):  
Epiretinal Membrane ◽  
Automatic Identification ◽  
Identification And Characterization

scholarly journals Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands

2020 ◽  
Vol 9 (5) ◽  
pp. 309 ◽  
Author(s):  
Tuomas Yrttimaa ◽  
Ninni Saarinen ◽  
Ville Kankare ◽  
Niko Viljanen ◽  
Jari Hynynen ◽  
...  
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Forest Canopy ◽  
Basal Area ◽  
Point Clouds ◽  
Stem Volume ◽  
Weighted Mean ◽  
Range Sensing ◽  
Close Range

Terrestrial laser scanning (TLS) provides a detailed three-dimensional representation of surrounding forest structures. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees, and especially upper parts of forest canopy, is often limited. In this study, we investigated how much forest characterization capacity can be improved in managed Scots pine (Pinus sylvestris L.) stands if TLS point clouds are complemented with photogrammetric point clouds acquired from above the canopy using unmanned aerial vehicle (UAV). In this multisensorial (TLS+UAV) close-range sensing approach, the used UAV point cloud data were considered especially suitable for characterizing the vertical forest structure and improvements were obtained in estimation accuracy of tree height as well as plot-level basal-area weighted mean height (Hg) and mean stem volume (Vmean). Most notably, the root-mean-square-error (RMSE) in Hg improved from 0.8 to 0.58 m and the bias improved from −0.75 to −0.45 m with the multisensorial close-range sensing approach. However, in managed Scots pine stands, the mere TLS also captured the upper parts of the forest canopy rather well. Both approaches were capable of deriving stem number, basal area, Vmean, Hg, and basal area-weighted mean diameter with the relative RMSE less than 5.5% for all the sample plots. Although the multisensorial close-range sensing approach mainly enhanced the characterization of the forest vertical structure in single-species, single-layer forest conditions, representation of more complex forest structures may benefit more from point clouds collected with sensors of different measurement geometries.

scholarly journals Automatic identification and characterization of radial files in light microscopy images of wood

2014 ◽  
Vol 114 (4) ◽  
pp. 829-840 ◽  
Author(s):  
Guilhem Brunel ◽  
Philippe Borianne ◽  
Gérard Subsol ◽  
Marc Jaeger ◽  
Yves Caraglio
Keyword(s):  
Light Microscopy ◽  
Automatic Identification ◽  
Identification And Characterization ◽  
Microscopy Images

scholarly journals Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands

2020 ◽  
Author(s):  
Tuomas Yrttimaa ◽  
Ninni Saarinen ◽  
Ville Kankare ◽  
Niko Viljanen ◽  
Jari Hynynen ◽  
...  
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Forest Structure ◽  
Point Cloud ◽  
Forest Canopy ◽  
Basal Area ◽  
Weighted Mean ◽  
Range Sensing ◽  
Close Range

Terrestrial laser scanning (TLS) provides detailed three-dimensional representation of the surrounding forest structure. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees and especially the upper parts of forest canopy is often limited. In this study, we investigated how much forest characterization capacity can be improved in managed Scots pine (Pinus sylvestris L.) stands if TLS point cloud is complemented with a photogrammetric point cloud acquired from above the canopy using unmanned aerial vehicle (UAV). In this multisensorial (TLS+UAV) close-range sensing approach, the used UAV point cloud data was considered feasible especially in characterizing the vertical forest structure and improvements were obtained in estimation accuracy of tree height as well as plot-level basal-area weighted mean height (Hg) and mean stem volume (Vmean). Most notably the root mean square error (RMSE) in Hg improved from 0.88 m to 0.58 m and the bias improved from -0.75 m to -0.45 m with the multisensorial close-range sensing approach. However, in managed Scots pine stands the mere TLS captured also the upper parts of the forest canopy rather well. Both approaches were capable of deriving stem number, basal area, Vmean, Hg and basal area-weighted mean diameter with a relative RMSE less than 5.5% for all of the sample plots. Although the multisensorial close-range sensing approach mainly enhanced characterization of forest vertical structure in single-species, single-layer forest conditions, representation of more complex forest structures may benefit more from point clouds collected with sensors of different measurement geometries.

scholarly journals Star Image Identification and Characterization on Astrographic Plates

1994 ◽  
Vol 161 ◽  
pp. 225-226
Author(s):  
A. López García ◽  
A. Ortiz Gil ◽  
J.M. Martínez González ◽  
V. Yershov
Keyword(s):  
Preliminary Analysis ◽  
Computer Control ◽  
Ccd Camera ◽  
Automatic Identification ◽  
Stellar Objects ◽  
Pulkovo Observatory ◽  
Star Image ◽  
Star Images ◽  
Identification And Characterization

The automatic identification and characterization of star images has great value for the preliminary analysis and measurement of astrographic plates. Our group at Valencia Observatory is using a small 2-D stage and a CCD camera under computer control to perform systematic measurements of bright asteroid plates. We are also applying this method to the processing of astrographic plates with crowded stellar fields and non-stellar objects in collaboration with the Pulkovo Observatory.

Identification and characterization of peptidases secreted by quahog parasite unknown (QPX), the protistan parasite of hard clams

2016 ◽  
Vol 122 (1) ◽  
pp. 21-33 ◽  
Author(s):  
E Rubin ◽  
GT Werneburg ◽  
E Pales Espinosa ◽  
DG Thanassi ◽  
B Allam
Keyword(s):  
Quahog Parasite Unknown ◽  
Hard Clams ◽  
Identification And Characterization
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