Proceedings

Find matching any: Reset
Company, J
Lacey, R
Add filter to result:
Authors
Arno, J
DEL MORAL, I
Escolà, A
Company, J
MARTÍNEZ-CASASNOVAS, J.A
MASIP, J
SANZ, R
ROSELL, J.R
Zhang, H
Lan, Y
Westbrook, J
Suh, C
Hoffmann, C
Lacey, R
Topics
Proximal Sensing in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Type
Poster
Year
2012
2010
Home » Authors » Results

Authors

Filter results2 paper(s) found.

1. Mapping the Leaf Area Index In Vineyard Using a Ground-Based LIDAR Scanner

The leaf area index (LAI) is defined as the one-sided leaf area per unit ground area and is probably the most widely used index to characterize grapevine vigour. However, direct LAI measurement requires the use of destructive leaves sampling methods which are costly and time-consuming and so are other indirect methods. Faced with these techniques, vineyard leaf area can be indirectly estimated using ground-based LIDAR sensors that scan the vines and get information about the geometry and/or structure... J. Arno, I. Del Moral, A. Escolà, J. Company, J.A. MartÍnez-casasnovas, J. Masip, R. Sanz, J.R. Rosell

2. Investigation Of Crop Varieties At Different Growth Stages Using Optical Sensor Data

Cotton, soybean and sorghum are economically important crops in Texas. Knowing the growing status of crops at different stages of growth is crucial to apply site-specific management and increase crop yield for farmers. Field experiments were initiated to measure cotton, soybean and sorghum plants growth status and spatial variability through the whole growing cycle. A ground-based active optical sensor, Greenseeker®, was used to collect the Normalized Difference Vegetation Index (NDVI) data... H. Zhang, Y. Lan, J. Westbrook, C. Suh, C. Hoffmann, R. Lacey