Proceedings :: International Society of Precision Agriculture

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Ferreira, E

Chaves, C

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Authors

Heideker, A

Speranza, E.A

Ferreira, E

Silva, D

Kamienski, C

Bianchi, R

Johari, F

Ferreira, E

Prati, R

Hermes, M

Albuquerque, M

Andreoli, A

, C

Chaves, C

Quicaña, A.

Chimello, L

Hermes, M

Andreoli, A

Albuquerque, M

Figueiredo, G

Topics

Remote and Proximal Sensing of Soils and Crops

Wireless Sensor Networks, Edge Computing, and Farm Connectivity

Digital Solutions for Soil Health, Water Quality, and Conservation Practices

Type

Oral

Poster

Year

2026

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Authors

Filter results4 paper(s) found.
1. Satellite Imagery to Machine Learning Datasets: An Automated System for Soil Water Stress Monitoring in Agriculture Satellite remote sensing has become a key data source for precision agriculture, particularly for monitoring vegetation dynamics and soil water stress over large areas. Multispectral satellite imagery enables the computation of vegetation indices, including NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index), which are commonly employed to quantify vegetation health, vigor, and canopy development. However, the practical use of satellite imagery in data-driven agricultural... A. Heideker, E.A. Speranza, E. Ferreira, D. Silva, C. Kamienski, R. Bianchi Download paper
2. Manifold-Based Time-Lag Analysis of Soil Water Availability and Satellite Vegetation Indices for Irrigation Monitoring in Coffee Plantations Monitoring soil water availability is essential for optimizing irrigation in perennial crops such as coffee, yet deploying dense in situ sensor networks remains impractical at scale. Although sensors like IGstat provide high-fidelity measurements of soil-water matric potential (SMP), their installation and maintenance costs limit broad adoption. A scalable alternative is to integrate sparse in situ observations with satellite-derived vegetation indices, including the Normalized Difference Moisture... F. Johari, E. Ferreira, R. Prati Download paper
3. Development of a LoRaWAN Network for Remote Sensing in Precision Agriculture The modernization of agriculture through Agriculture 4.0 requires the use of advanced sensors and wireless communication networks for the precise monitoring of environmental variables and process optimization. However, the implementation of these Internet of Things (IoT) technologies in rural areas frequently faces the challenge of limited infrastructure over large territorial expanses. In this scenario, Low-Power Wide-Area Networks (LPWAN), specifically the LoRaWAN protocol, stand out for their... M. Hermes, M. Albuquerque, A. Andreoli, C. , C. Chaves
4. Use of Digital Permeameter for the Functional Characterization of Geoenvironments Characterizing agricultural geoenvironments with precision is inherently a complex task. Historically, this process has relied on quasi-static edaphic attributes, such as soil texture and apparent electrical conductivity. However, a critical problem exists, as these parameters exhibit low sensitivity to ephemeral structural changes resulting from soil management systems. Texture conditions the productive potential, yet it fails to reflect modifications in pore geometry induced by mechanical pressures... C. Chaves, A. . Quicaña, L. Chimello, M. Hermes, A. Andreoli, M. Albuquerque, G. Figueiredo, M. Hermes

Filter results4 paper(s) found.

1. Satellite Imagery to Machine Learning Datasets: An Automated System for Soil Water Stress Monitoring in Agriculture

Satellite remote sensing has become a key data source for precision agriculture, particularly for monitoring vegetation dynamics and soil water stress over large areas. Multispectral satellite imagery enables the computation of vegetation indices, including NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index), which are commonly employed to quantify vegetation health, vigor, and canopy development. However, the practical use of satellite imagery in data-driven agricultural... A. Heideker, E.A. Speranza, E. Ferreira, D. Silva, C. Kamienski, R. Bianchi

Download paper

2. Manifold-Based Time-Lag Analysis of Soil Water Availability and Satellite Vegetation Indices for Irrigation Monitoring in Coffee Plantations

Monitoring soil water availability is essential for optimizing irrigation in perennial crops such as coffee, yet deploying dense in situ sensor networks remains impractical at scale. Although sensors like IGstat provide high-fidelity measurements of soil-water matric potential (SMP), their installation and maintenance costs limit broad adoption. A scalable alternative is to integrate sparse in situ observations with satellite-derived vegetation indices, including the Normalized Difference Moisture... F. Johari, E. Ferreira, R. Prati

Download paper

3. Development of a LoRaWAN Network for Remote Sensing in Precision Agriculture

The modernization of agriculture through Agriculture 4.0 requires the use of advanced sensors and wireless communication networks for the precise monitoring of environmental variables and process optimization. However, the implementation of these Internet of Things (IoT) technologies in rural areas frequently faces the challenge of limited infrastructure over large territorial expanses. In this scenario, Low-Power Wide-Area Networks (LPWAN), specifically the LoRaWAN protocol, stand out for their... M. Hermes, M. Albuquerque, A. Andreoli, C. , C. Chaves

4. Use of Digital Permeameter for the Functional Characterization of Geoenvironments

Characterizing agricultural geoenvironments with precision is inherently a complex task. Historically, this process has relied on quasi-static edaphic attributes, such as soil texture and apparent electrical conductivity. However, a critical problem exists, as these parameters exhibit low sensitivity to ephemeral structural changes resulting from soil management systems. Texture conditions the productive potential, yet it fails to reflect modifications in pore geometry induced by mechanical pressures... C. Chaves, A. . Quicaña, L. Chimello, M. Hermes, A. Andreoli, M. Albuquerque, G. Figueiredo, M. Hermes