Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece
The scope of this work is to compare Sentinel-2 and unmanned aerial vehicles (UAV) imagery from northern Greece for use in precision agriculture by implementing statistical analysis and 2D visualization. Surveys took place on five dates with a difference between the sensing dates for the two techniq...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/5/2/35 |
| _version_ | 1797535012184129536 |
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| author | Nikolaos Bollas Eleni Kokinou Vassilios Polychronos |
| author_facet | Nikolaos Bollas Eleni Kokinou Vassilios Polychronos |
| author_sort | Nikolaos Bollas |
| collection | DOAJ |
| description | The scope of this work is to compare Sentinel-2 and unmanned aerial vehicles (UAV) imagery from northern Greece for use in precision agriculture by implementing statistical analysis and 2D visualization. Surveys took place on five dates with a difference between the sensing dates for the two techniques ranging from 1 to 4 days. Using the acquired images, we initially computed the maps of the Normalized Difference Vegetation Index (NDVI), then the values of this index for fifteen points and four polygons (areas). The UAV images were not resampled, aiming to compare both techniques based on their initial standards, as they are used by the farmers. Similarities between the two techniques are depicted on the trend of the NDVI means for both satellite and UAV techniques, considering the points and the polygons. The differences are in the a) mean NDVI values of the points and b) range of the NDVI values of the polygons probably because of the difference in the spatial resolution of the two techniques. The correlation coefficient of the NDVI values, considering both points and polygons, ranges between 83.5% and 98.26%. In conclusion, both techniques provide important information in precision agriculture depending on the spatial extent, resolution, and cost, as well as the requirements of the survey. |
| first_indexed | 2024-03-10T11:38:33Z |
| format | Article |
| id | doaj.art-6642d38766db47b89a3b7ff6113a3348 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-10T11:38:33Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-6642d38766db47b89a3b7ff6113a33482023-11-21T18:40:47ZengMDPI AGDrones2504-446X2021-05-01523510.3390/drones5020035Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern GreeceNikolaos Bollas0Eleni Kokinou1Vassilios Polychronos2Department of Agriculture, School of Agricultural Sciences, Hellenic Mediterranean University, Stavromenos, 71004 Heraklion, Crete, GreeceDepartment of Agriculture, School of Agricultural Sciences, Hellenic Mediterranean University, Stavromenos, 71004 Heraklion, Crete, GreeceGeoSense, Terma Proektasis Maiandrou Str., 57013 Oraiokastro, Thessaloniki, GreeceThe scope of this work is to compare Sentinel-2 and unmanned aerial vehicles (UAV) imagery from northern Greece for use in precision agriculture by implementing statistical analysis and 2D visualization. Surveys took place on five dates with a difference between the sensing dates for the two techniques ranging from 1 to 4 days. Using the acquired images, we initially computed the maps of the Normalized Difference Vegetation Index (NDVI), then the values of this index for fifteen points and four polygons (areas). The UAV images were not resampled, aiming to compare both techniques based on their initial standards, as they are used by the farmers. Similarities between the two techniques are depicted on the trend of the NDVI means for both satellite and UAV techniques, considering the points and the polygons. The differences are in the a) mean NDVI values of the points and b) range of the NDVI values of the polygons probably because of the difference in the spatial resolution of the two techniques. The correlation coefficient of the NDVI values, considering both points and polygons, ranges between 83.5% and 98.26%. In conclusion, both techniques provide important information in precision agriculture depending on the spatial extent, resolution, and cost, as well as the requirements of the survey.https://www.mdpi.com/2504-446X/5/2/35precision agricultureNDVISentinel-2UAV2D visualization |
| spellingShingle | Nikolaos Bollas Eleni Kokinou Vassilios Polychronos Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece Drones precision agriculture NDVI Sentinel-2 UAV 2D visualization |
| title | Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece |
| title_full | Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece |
| title_fullStr | Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece |
| title_full_unstemmed | Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece |
| title_short | Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece |
| title_sort | comparison of sentinel 2 and uav multispectral data for use in precision agriculture an application from northern greece |
| topic | precision agriculture NDVI Sentinel-2 UAV 2D visualization |
| url | https://www.mdpi.com/2504-446X/5/2/35 |
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