Proceedings

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Duarte, C
Abenina, M
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Authors
Maldaner, L
Molin, J
Tavares, T
Mendez, L
Corrêdo, L
Duarte, C
Maja, J.J
Abenina, M
Cutulle, M
Melgar, J
Liu, H
Topics
Geospatial Data
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Oral
Poster
Year
2018
2022
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Filter results2 paper(s) found.

1. Identifying and Filtering Out Outliers in Spatial Datasets

Outliers present in the dataset is harmful to the information quality contained in the map and may lead to wrong interpretations, even if the number of outliers to the total data collected is small. Thus, before any analysis, it is extremely important to remove these errors. This work proposes a sequential process model capable of identifying outlier data when compared their neighbors using statistical parameters. First, limits are determined based on the median range of the values of all the... L. Maldaner, J. Molin, T. Tavares, L. Mendez, L. Corrêdo, C. Duarte

2. Snap-shot Hyperspectral Camera for Potassium Prediction of Peach Trees Using Multivariate Analysis

Hyperspectral imaging (HSI) is an emerging technology being utilized in agriculture. This system could be used to monitor the overall health of plants or pest disease detection. As sensing technology advances, measuring nutrient levels and disease detection also progresses. This study aimed to predict the levels of potassium (K) content in peach leaves with the new snapshot hyperspectral camera. The study was conducted at the Clemson University Musser Fruit Research Farm (Seneca, SC, USA, 34.61... J.J. Maja, M. Abenina, M. Cutulle, J. Melgar, H. Liu