Journal:GeoFIS: An open-source decision support tool for precision agriculture data
| Full article title | GeoFIS: An open-source decision support tool for precision agriculture data |
|---|---|
| Journal | Agriculture |
| Author(s) |
Leroux, Corentin; Jones, Hazaël; Pichon, Léo; Guillaume, Serge; Lamour, Julien; Taylor, James; Naud, Olivier; Crestey, Thomas; Lablee, Jean-Luc; Tisseyre, Bruno |
| Author affiliation(s) | University of Montpellier, SMAG, Compagnie Fruitière |
| Primary contact | Email: cleroux at smag-group dot com |
| Year published | 2018 |
| Volume and issue | 8(6) |
| Page(s) | 73 |
| DOI | 10.3390/agriculture8060073 |
| ISSN | 2077-0472 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | http://www.mdpi.com/2077-0472/8/6/73/htm |
| Download | http://www.mdpi.com/2077-0472/8/6/73/pdf (PDF) |
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Abstract
The world we live in is an increasingly spatial and temporal data-rich environment, and the agriculture industry is no exception. However, data needs to be processed in order to first get information and then make informed management decisions. The concepts of "precision agriculture" and "smart agriculture" can and will be fully effective when methods and tools are available to practitioners to support this transformation. An open-source program called GeoFIS has been designed with this objective. It was designed to cover the whole process from spatial data to spatial information and decision support. The purpose of this paper is to evaluate the abilities of GeoFIS along with its embedded algorithms to address the main features required by farmers, advisors, or spatial analysts when dealing with precision agriculture data. Three case studies are investigated in the paper: (i) mapping of the spatial variability in the data, (ii) evaluation and cross-comparison of the opportunity for site-specific management in multiple fields, and (iii) delineation of within-field zones for variable-rate applications when these latter are considered opportune. These case studies were applied to three contrasting crop types: banana, wheat, and grapes. These were chosen to highlight the diversity of applications and data characteristics that might be handled with GeoFIS. For each case-study, up-to-date algorithms arising from research studies and implemented in GeoFIS were used to process these precision agriculture data. Areas for future development and possible relations with existing geographic information systems (GIS) software is also discussed.
Keywords: decision making, GeoFIS, geostatistics, open-source software, precision agriculture, spatial analysis
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Notes
This presentation is faithful to the original, with only a few minor changes to grammar, spelling, and presentation, including the addition of PMCID and DOI when they were missing from the original reference.
