POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANY
Forage monitoring in grassland is an important task to support management decisions. Spatial data on (i) yield,(ii) quality, and (iii) floristic composition are of interest. The spatio-temporal variability in grasslands is significant and requires fast and low-cost methods for data delivery. Therefo...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/203/2019/isprs-archives-XLII-2-W13-203-2019.pdf |
| _version_ | 1818303021719748608 |
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| author | G. Bareth U. Lussem J. Menne J. Hollberg J. Schellberg |
| author_facet | G. Bareth U. Lussem J. Menne J. Hollberg J. Schellberg |
| author_sort | G. Bareth |
| collection | DOAJ |
| description | Forage monitoring in grassland is an important task to support management decisions. Spatial data on (i) yield,(ii) quality, and (iii) floristic composition are of interest. The spatio-temporal variability in grasslands is significant and requires fast and low-cost methods for data delivery. Therefore, the overarching aim of this contribution is the investigation of low-cost and non-calibrated UAV-derived RGB imagery for forage monitoring. Study area is the Rengen Grassland Experiment (RGE) in Germany which is a long-term field experiment since 1941. Due to the experiment layout, destructive biomass sampling during the growing period was not possible. Hence, non-destructive Rising Plate Meter (RPM) measurements, which are a common method to estimate biomass in grasslands, were carried out. UAV campaigns with a Canon Powershot 110 mounted on a DJI Phantom 2 were conducted in the first growing season in 2014. From the RGB imagery, the RGB vegetation index (RGBVI) and the Grassland Index (GrassI) introduced by Bendig et al. (2015) and Bareth et al. (2015), respectively, were computed. The RGBVI and the GrassI perform very well against the RPM measurements resulting in R<sup>2</sup> of 0.84 and 0.9, respectively. These results indicate the potential of low-cost UAV methods for grassland monitoring and correspond well to the studies of Viljanen et al. (2018) and Näsi et al. (2018). |
| first_indexed | 2024-12-13T05:48:11Z |
| format | Article |
| id | doaj.art-1e7f0d4b95ee4899b4acdc38ff8149ef |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-13T05:48:11Z |
| publishDate | 2019-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-1e7f0d4b95ee4899b4acdc38ff8149ef2022-12-21T23:57:37ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342019-06-01XLII-2-W1320320610.5194/isprs-archives-XLII-2-W13-203-2019POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANYG. Bareth0U. Lussem1J. Menne2J. Hollberg3J. Schellberg4GIS & RS Group, Institute of Geography, University of Cologne, GermanyGIS & RS Group, Institute of Geography, University of Cologne, GermanyGIS & RS Group, Institute of Geography, University of Cologne, GermanyInstitute of Crop Production (INRES), Bonn University, GermanyInstitute of Crop Production (INRES), Bonn University, GermanyForage monitoring in grassland is an important task to support management decisions. Spatial data on (i) yield,(ii) quality, and (iii) floristic composition are of interest. The spatio-temporal variability in grasslands is significant and requires fast and low-cost methods for data delivery. Therefore, the overarching aim of this contribution is the investigation of low-cost and non-calibrated UAV-derived RGB imagery for forage monitoring. Study area is the Rengen Grassland Experiment (RGE) in Germany which is a long-term field experiment since 1941. Due to the experiment layout, destructive biomass sampling during the growing period was not possible. Hence, non-destructive Rising Plate Meter (RPM) measurements, which are a common method to estimate biomass in grasslands, were carried out. UAV campaigns with a Canon Powershot 110 mounted on a DJI Phantom 2 were conducted in the first growing season in 2014. From the RGB imagery, the RGB vegetation index (RGBVI) and the Grassland Index (GrassI) introduced by Bendig et al. (2015) and Bareth et al. (2015), respectively, were computed. The RGBVI and the GrassI perform very well against the RPM measurements resulting in R<sup>2</sup> of 0.84 and 0.9, respectively. These results indicate the potential of low-cost UAV methods for grassland monitoring and correspond well to the studies of Viljanen et al. (2018) and Näsi et al. (2018).https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/203/2019/isprs-archives-XLII-2-W13-203-2019.pdf |
| spellingShingle | G. Bareth U. Lussem J. Menne J. Hollberg J. Schellberg POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANY The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANY |
| title_full | POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANY |
| title_fullStr | POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANY |
| title_full_unstemmed | POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANY |
| title_short | POTENTIAL OF NON-CALIBRATED UAV-BASED RGB IMAGERY FOR FORAGE MONITORING: CASE STUDY AT THE RENGEN LONG-TERM GRASSLAND EXPERIMENT (RGE), GERMANY |
| title_sort | potential of non calibrated uav based rgb imagery for forage monitoring case study at the rengen long term grassland experiment rge germany |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/203/2019/isprs-archives-XLII-2-W13-203-2019.pdf |
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