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Melnitchouck, A

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Authors

Hoffmann Silva Karp, F

Adamchuk, V

Melnitchouck, A

Dutilleul, P

Hoffmann Silva Karp, F

Adamchuk, V

Dutilleul, P

Melnitchouck, A

Biswas, A

Topics

Geospatial Data

Proximal and Remote Sensing of Soils and Crops (including Phenotyping)

Type

Oral

Year

2022

2024

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Filter results2 paper(s) found.
1. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processing... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul Download paper
2. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case Study Using proximal soil sensors (PSS) is widely recognized as a strategy to improve the quality of agricultural soil maps. Nevertheless, the signals captured by PSS are complex and usually relate to a combination of processes in the soil. Consequently, there is a need to explore further the interactions at the source of the information provided by PSS. The objectives of this study were to examine the relationship between proximal sensing techniques and soil properties and evaluate the feasibility... F. Hoffmann silva karp, V. Adamchuk, P. Dutilleul, A. Melnitchouck, A. Biswas Download paper

Filter results2 paper(s) found.

1. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes

The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processing... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul

Download paper

2. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case Study

Using proximal soil sensors (PSS) is widely recognized as a strategy to improve the quality of agricultural soil maps. Nevertheless, the signals captured by PSS are complex and usually relate to a combination of processes in the soil. Consequently, there is a need to explore further the interactions at the source of the information provided by PSS. The objectives of this study were to examine the relationship between proximal sensing techniques and soil properties and evaluate the feasibility... F. Hoffmann silva karp, V. Adamchuk, P. Dutilleul, A. Melnitchouck, A. Biswas

Download paper