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Huang, W

Hegedus, P.D

Hueppi, R

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Authors

Song, X

Zhao, C

Chen, L

Huang, W

Cui, B

Huang, W

Zhao, C

Holpp, M

Anken, T

Seatovic, D

Grueninger, R

Hueppi, R

Maxwell, B.D

Hegedus, P.D

Loewen, S.D

Duff, H.D

Sheppard, J.W

Peerlinck, A.D

Morales, G.L

Bekkerman, A

Topics

Spatial Variability in Crop, Soil and Natural Resources

Remote Sensing Applications in Precision Agriculture

Spatial and Temporal Variability in Crop, Soil and Natural Resources

Decision Support Systems

Type

Poster

Oral

Year

2012

2010

2008

2022

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Filter results4 paper(s) found.
1. Inversion Of Vertical Distribution Of Chlorophyll Concentration By Canopy Reflectance Spectrum In Winter Wheat The objective of this study was to investigate the inversion of foliage chlorophyll concentration(Chl) vertical-layer distribution by bidirectional reflectance difference function (BRDF) data, so as to provide guidance on the application of fertilizer. The ratio of transformed chlorophyll absorption reflectance index (TCARI) to optimized soil adjusted vegetation index (OSAVI) was named as canopy chlorophyll inversion index (CCII) in... W. Huang, C. Zhao Download paper
2. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images ... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui Download paper
3. 3d Object Recognition, Localization and Treatment of Rumex Obtusifolius in Its Natural Environment Rumex obtusifolius is one of the most highly competitive and persistent sorts of weed in agriculture. An automatic recognition and plant-treatment system is currently under development as an alternative treatment technique. An infrared-laser triangulation sensor and a high-resolution smart camera are used to generate 3D images of the weeds and their natural environment. In a segmentation process, contiguous surface patches are separated from one other. These 3D surface patches... M. Holpp, T. Anken, D. Seatovic, R. Grueninger, R. Hueppi Download paper
4. Decision Support from On-field Precision Experiments Empirically driven adaptive management in large-scale commodity crop production has become possible with spatially controlled application and sub-field scale crop monitoring technology. Site-specific experimentation is fundamental to an agroecosystem adaptive management (AAM) framework that results in information for growers to make informed decisions about their practices. Crop production and quality response data from combine harvester mounted sensors and internet available remote sensing data... B.D. Maxwell, P.D. Hegedus, S.D. Loewen, H.D. Duff, J.W. Sheppard, A.D. Peerlinck, G.L. Morales, A. Bekkerman Download paper

Filter results4 paper(s) found.

1. Inversion Of Vertical Distribution Of Chlorophyll Concentration By Canopy Reflectance Spectrum In Winter Wheat

The objective of this study was to investigate the inversion of foliage chlorophyll concentration(Chl) vertical-layer distribution by bidirectional reflectance difference function (BRDF) data, so as to provide guidance on the application of fertilizer. The ratio of transformed chlorophyll absorption reflectance index (TCARI) to optimized soil adjusted vegetation index (OSAVI) was named as canopy chlorophyll inversion index (CCII) in... W. Huang, C. Zhao

Download paper

2. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images

... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui

Download paper

3. 3d Object Recognition, Localization and Treatment of Rumex Obtusifolius in Its Natural Environment

Rumex obtusifolius is one of the most highly competitive and persistent sorts of weed in agriculture. An automatic recognition and plant-treatment system is currently under development as an alternative treatment technique. An infrared-laser triangulation sensor and a high-resolution smart camera are used to generate 3D images of the weeds and their natural environment. In a segmentation process, contiguous surface patches are separated from one other. These 3D surface patches... M. Holpp, T. Anken, D. Seatovic, R. Grueninger, R. Hueppi

Download paper

4. Decision Support from On-field Precision Experiments

Empirically driven adaptive management in large-scale commodity crop production has become possible with spatially controlled application and sub-field scale crop monitoring technology. Site-specific experimentation is fundamental to an agroecosystem adaptive management (AAM) framework that results in information for growers to make informed decisions about their practices. Crop production and quality response data from combine harvester mounted sensors and internet available remote sensing data... B.D. Maxwell, P.D. Hegedus, S.D. Loewen, H.D. Duff, J.W. Sheppard, A.D. Peerlinck, G.L. Morales, A. Bekkerman

Download paper