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Levi, O
Souza, W.J
Pereira, F.R
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Authors
Cohen, Y
Alchanatis, V
Levi, O
Cohen, S
Sanches, G.M
Otto, R
Pereira, F.R
Pereira, F.R
Dos Reis, A.A
Freitas, R.G
Oliveira, S.R
Amaral, L.R
Figueiredo, G.K
Antunes, J.F
Lamparelli, R.A
Moro, E
Pereira, N.D
Magalhães, P.S
Souza, W.J
Silva, A.N
Apolinário, E
Souza, W.J
Topics
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Geospatial Data
Type
Poster
Oral
Year
2012
2022
2024
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Filter results5 paper(s) found.

1. A Method for Combining Spatial and Hyperspectral Information for Delineation of Homogenous Management Zones

Hyperspectral (HS) remote sensing is a constantly developing field. New remote sensing applications of different fields constantly appear. The possibility of acquisition information about an object without physical contact is spanning new opportunities in many fields and for precision agricultural in particular. These opportunities demand constant improvement and development of new analysis approaches and algorithms,... Y. Cohen, V. Alchanatis, O. Levi, S. Cohen

2. Soil and Crop Factors to Site-specific Nitrogen Management on Sugarcane Fields

Nitrogen (N) is one of the most widely used fertilizers in crops and the most harmful to the environment. The increase fertilizers consumption, mainly N sources (one of the most widely fertilizer used in sugarcane fields), is one of the main factors underlying the sustainability of the entire production process. Currently, N recommendations in sugarcane are based only on the expected yield. However, there is little agronomic support for nitrogen (N) recommendations based on expected yield, despite... G.M. Sanches, R. Otto, F.R. Pereira

3. A Framework for Imputation of Missing Parts in UAV Orthomosaics Using Planetscope and Sentinel-2 Data

In recent years, the emergence of Unmanned Aerial Vehicles (UAV), also known as drones, with high spatial resolution, has broadened the application of remote sensing in agriculture. However, UAV images commonly have specific problems with missing areas due to drone flight restrictions. Data mining techniques for imputing missing data is an activity often demanded in several fields of science. In this context, this research used the same approach to predict missing parts on orthomosaics obtained... F.R. Pereira, A.A. Dos reis, R.G. Freitas, S.R. Oliveira, L.R. Amaral, G.K. Figueiredo, J.F. Antunes, R.A. Lamparelli, E. Moro, N.D. Pereira, P.S. Magalhães

4. Precision Agriculture: Forage Chopper Noise Level As an Estimator of Corn Silage Production in Small Farms

The objective of the work carried out in the Registro County, SP, Brazil, in the year 2021, was to study the forage chopper noise level as an estimator of corn silage production in small farms. The corn crop study and characterization were measured plant height (PH), height of first ear insertion (HEI) and green mass production of plants (GM) were studied. The noise (NO) produced by the forage machine during ensiling was collected by recording, considering it as a potential yield estimator during... W.J. Souza, A.N. Silva

5. Soybean Production Components As Indicators of Soil Variability As a Subsidy for Precision Agriculture

The soil variability in its physical, chemical and biological parameters can be analyzed using direct methods applicable to each variable studied. Plant responses, manifested in the establishment of the final population, biomass production and grain productivity can reflect the soil conditions, associating them with the variability observed in the area. Localized soil management and the use of machines with variable rate applications, including drones for applications in specific sites, depend... E. Apolinário, W.J. Souza