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Amaral, L.R
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Authors
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
Pereira, F.R
Lima, J.P
Freitas, R.G
Dos Reis, A.A
Amaral, L.R
Figueiredo, G.K
Lamparelli, R.A
Pereira, J.C
Magalhães, P.S
da Cunha, I.A
Oldoni, H
Melo, D.D
Amaral, L.R
Amaral, L.R
Oldoni, H
Melo, D.D
Rosin, N.A
Alves, M.R
Demattê, J.M
Melo, D.D
da Cunha, I.A
Brasco, T.L
Oldoni, H
Amaral, L.R
Melo, D.D
Brasco, T.L
da Cunha, I.A
Castro, S.G
Amaral, L.R
Topics
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Geospatial Data
Site-Specific Nutrient, Lime and Seed Management
Type
Poster
Oral
Year
2022
2024
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Authors

Filter results6 paper(s) found.

1. 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

2. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 Imagery

Pasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of the... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães

3. Delineation of Yield Zones Using Optical and Radar Remote Sensing

Identifying yield zones in agricultural areas is essential for efficient resource allocation, operational optimization, and decision-making. While optical remote sensing is widely used in precision agriculture, the interest in radar remote sensing data, notably from the Sentinel-1 Synthetic Aperture Radar (SAR), has increased due to its operation in the C-band frequency, capturing data through cloud cover and the availability of free data. The main objective of this study was to evaluate whether... I.A. Da cunha, H. Oldoni, D.D. Melo, L.R. Amaral

4. Yield Potential Zones and Their Relationship with Soil Taxonomic Classes and Management Zones

The use of management zones (MZ) to subdivide agricultural areas based on the variability of yield potential and production factors is increasingly being explored by scientific research and demanded by farmers. However, there is still much uncertainty about which layers of information and procedures should be adopted for this purpose. Thus, our goal was to demonstrate whether simplistic approaches to creating MZ can satisfactorily address the variability of yield potential and soil classes. For... L.R. Amaral, H. Oldoni, D.D. Melo, N.A. Rosin, M.R. Alves, J.M. Demattê

5. Hierarchical Zoning: Targeted Sampling for Soil Attribute Mapping

The mapping of soil attributes for fertilizer recommendation remains challenging in precision agriculture. Traditionally, this mapping is done through soil sampling in a regular grid, which generally yields good results when done in denser grids. However, due to the high costs associated with sampling and analysis, sparser grids have been adopted, which has not produced good prediction results. Some studies with directed sampling points to obtain more accurate soil maps have been adopted to address... D.D. Melo, I.A. Da cunha, T.L. Brasco, H. Oldoni, L.R. Amaral

6. Sampling-based on Plant Vigor Zones As a Strategy for Creating Soil Attribute Maps

Mapping agronomically relevant soil properties for fertilizer recommendation remains challenging in precision agriculture. Traditionally, this mapping is conducted through soil sampling on a regular grid basis, where points are equally spaced primarily to ensure spatial coverage. However, directing soil sampling points based on plant vigor may be more efficient in capturing soil variability that directly affects plant development. Several commercial platforms offer solutions for defining management... D.D. Melo, T.L. Brasco, I.A. Da cunha, S.G. Castro, L.R. Amaral