Remote sensing applications for precision agriculture: A learning community approach

By S. Seelan, S. Laguette, G. Casady, G. Seielstad. 2003

423 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1dfc29115955d100124523e74fc273219a17db0b

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In Plant Science

Citations in the corpus

Green area index from an unmanned aerial system over wheat and rapeseed crops (2014, background): “The measured radiances are generally transformed into vegetation indices to produce maps showing the relative variability within fields (Seelan et al., 2003).”
Deep learning and machine vision for food processing: A survey (2021, background): “Nowadays, RS is one of the essential techniques for precision agriculture (Seelan et al., 2003). Fan (2016) and Sun (2016) used near-infrared (NIR) spectroscopy to detect soluble solids content of apples and the apple firmness, respectively. Khatiwada (2016) adopted NIR spectroscopy to detect the in”
Fourier analysis of historical NOAA time series data to estimate bimodal agriculture (2007, background): “2003 ) to large continuous irrigation schemes (Thenkabail et al.”
Applications of Remote Sensing in Precision Agriculture: A Review (2020, background): “2 m) 3 days Crop yield [85]; soil properties [86]; nutrient management [77]; ET estimation [87]”
Evaluating Multispectral Images and Vegetation Indices for Precision Farming Applications from UAV Images (2015, background): “Field surveying and Precision Agriculture (PA) are among the emerging applications [1,2].”
A Survey of Deep Learning Techniques for Weed Detection from Images (2021, background): “Precision agriculture or digital agriculture can provide strategies to mitigate these issues (Lal, 1991; Radoglou-Grammatikis et al., 2020; Seelan et al., 2003).”
Factors influencing the adoption of precision agricultural technologies: a review for policy implications (2012, background): “Precision agriculture is a production system that involves crop management according to field variability and site-specific conditions (Seelan et al. 2003).”
High-Throughput Field-Phenotyping Tools for Plant Breeding and Precision Agriculture (2019, background): “Applications of satellite imaging for precision agriculture has been reviewed earlier [24,25].”
A compilation of UAV applications for precision agriculture (2020, positive): “Next, these images can be utilized to extract vegetation indices that enable farmers to monitor constantly the crop variability and stress conditions.”