Proceedings
Authors
| Filter results2 paper(s) found. |
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1. Satellite Imagery to Machine Learning Datasets: An Automated System for Soil Water Stress Monitoring in AgricultureSatellite 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 |
2. Manifold-Based Time-Lag Analysis of Soil Water Availability and Satellite Vegetation Indices for Irrigation Monitoring in Coffee PlantationsMonitoring 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 |