Time Series Analysis of Multisensor Data for Precision Viticulture—Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography
"> Figure 1
<p>Overall workflow of this study. For more information, refer to the text.</p> "> Figure 2
<p>Study area near Himmelstadt, Bavaria. Different irrigation systems are shown in red, green, and blue. Locations for hyperspectral measurements on plants are shown depending on their location in the vineyard (yellow outline). Locations of tubes for soil moisture readings are shown in blue. RGB of the flight on 13 July as basemap. The climate station is visible north of the vineyard.</p> "> Figure 3
<p>Example of one NDVI calculation (17 July 2023) showing the plant locations and zonal statistics areas used for correlation with spectroradiometer measurements. As vines are aligned along wires, it is important to automatically derive the maximum VI value locations (for some indices minimum) and avoid sampling erroneous pixels (such as bare soil or stem areas), as can be seen in the zoomed-in location.</p> "> Figure 4
<p>Time series of (<b>A</b>) NDVI, (<b>B</b>) RG Index, (<b>C</b>) NGRDI, (<b>D</b>) MSI. NDVI and NGRDI show lower values for nonirrigated plants from June through to September (NGRDI) and are more pronounced in August for the NDVI. The RG index follows the same pattern with higher values for nonirrigated plants. The moisture stress index, MSI, on the other hand, shows slightly higher values for irrigated plants, especially after strong rainfall in August. Additional plots for VIs not shown here can be found in <a href="#app1-remotesensing-16-01419" class="html-app">Appendix A</a>.</p> "> Figure 5
<p>Time series of (<b>A</b>) NDVI, (<b>B</b>) CIRedEdge Index, (<b>C</b>) RG Index, (<b>D</b>) GLI index. For NDVI, there are no significant differences with respect to topography, while the CIRedEdge index is less favorable for the lower part of the vineyard. The RG index is lower for the lower part of the vineyard, while the GLI is higher for most of the vegetation period. Additional plots for VIs not shown here can be found in <a href="#app1-remotesensing-16-01419" class="html-app">Appendix A</a>.</p> "> Figure 6
<p>Matrix showing results of the Tukey HSD test after performing ANOVA analysis for all indices with respect to topographic and irrigation classes. Test results are shown for in situ data as well as UAV-derived indices. Significant test results are highlighted in green.</p> "> Figure 7
<p>Time series of (<b>A</b>) NDVI, (<b>B</b>) RG index, (<b>C</b>) NGRD index, (<b>D</b>) GNDVI index. Significant differences for nonirrigated plots are clearly pronounced for all indices shown. The steep drop (NDVI, NGRDI, GNDVI) at the end of September is not clearly visible in the spectrometer data, as the last measurement took place on the 14th of September. Additional plots for VIs not shown here can be found in <a href="#app1-remotesensing-16-01419" class="html-app">Appendix A</a>.</p> "> Figure 8
<p>Correlation analysis of in situ data with UAV-derived VIs. (<b>A</b>) CIRedEdge, (<b>B</b>) NDVI.</p> "> Figure 9
<p>(<b>A</b>) Mean soil moisture at different depth levels over the vegetation period. Stdv. is plotted in shaded colors. Rainfall events are shown in blue. We observe high fluctuations in shallow soil levels, while deeper levels mainly react to prolonged rainfall in July to August. (<b>B</b>) GNDVI mean values for plants located at soil moisture measurement tubes. Stdv. is shown in shaded colors. We observe a steep rise in GNDVI values after prolonged rainfall at the end of June and again in August.</p> "> Figure A1
<p>Additional plots for <a href="#remotesensing-16-01419-f004" class="html-fig">Figure 4</a> in the paper: Time series of spectrometer data with respect to irrigation systems for GLI and CIRedEdge.</p> "> Figure A2
<p>Additional plots for <a href="#remotesensing-16-01419-f005" class="html-fig">Figure 5</a> in the paper: Time series of spectrometer data with respect to topography for MSI and NGRDI.</p> "> Figure A3
<p>Additional plot for <a href="#remotesensing-16-01419-f007" class="html-fig">Figure 7</a> in the paper: Time series of UAV data with respect to irrigation for the CIRedEdge (MSI not calculated).</p> ">
Abstract
:1. Introduction
1.1. State-of-the-Art Remote Sensing for Precision Viticulture
1.2. Additional Sensor Systems for Precision Viticulture
2. Materials and Methods
2.1. Study Area
2.2. UAV Flight Campaign and In Situ Measurements
2.3. Data Preprocessing and Calculation of Vegetation Indices
2.4. Time Series Analysis of In Situ-Derived VIs with Respect to Different Irrigation Patterns and Topography
2.5. Correlation of UAV-Derived VIs and Hyperspectral In Situ Measurements
2.6. Analysis of Soil Moisture Patterns during the Vegetation Period for Nonirrigated Plots and Changes in VIs
3. Results
3.1. Time Series Analysis of In Situ-Derived VIs for Different Irrigation Patterns and Topography
3.2. Correlation of UAV-Derived VIs and Hyperspectral In Situ Measurements
3.3. Soil Moisture Patterns during the Vegetation Period for Nonirrigated Plots and Changes in VIs
4. Discussion
4.1. What Do We Learn from Time Series of VIs with Respect to Irrigation, Topography, and Climate—And What Remains to Debate?
4.2. Scaling up from In Situ to UAV—A Critical Assessment
4.3. Comparison with Other Works
5. Conclusions and Outlook
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
VI | Vegetation Index |
UAV | Unmanned Aereal Vehicle |
NDVI | Normalized Difference Vegetation Index |
GNDVI | Green Normalized Difference Vegetation Index |
RE index | Red/Green Index |
CIRedEdge | Chlorophyll Index Rededge |
GLI | Green Leaf Index |
MSI | Moisture Stress Index |
HSD | Honesty Significant Difference |
ANOVA | Analysis of Variance |
Appendix A
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Flight Campaign | Weather Conditions | Spectrometer Measurement |
---|---|---|
31 May 2023 | Sunny | 23 May 2023 |
none | Sunny | 31 May 2023 |
06 June 2023 | Slightly overcast | 6 June 2023 |
none | Slightly overcast | 13 June 2023 |
20 June 2023 | Cloudy | 20 June 2023 |
28 June 2023 | Mostly sunny/scattered clouds | 28 June 2023 |
6 July 2023 | Mostly sunny/scattered clouds | 6 July 2023 |
13 July 2023 | Cloudy | 14 July 2023 |
20 July 2023 | Cloudy | 18 July 2023 |
26 July 2023 | Cloudy | 26 July 2023 |
none | Sunny | 2 August 2023 |
11 August 2023 | Sunny | 10 August 2023 |
18 August 2023 | Sunny | 16 August 2023 |
21 August 2023 | Sunny | 23 August 2023 |
none | Cloudy | 3 September 2023 |
7 September 2023 | Sunny | 7 September 2023 |
27 September 2023 | Cloudy | 14 September 2023 |
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Brandmeier, M.; Heßdörfer, D.; Siebenlist, P.; Meyer-Spelbrink, A.; Kraus, A. Time Series Analysis of Multisensor Data for Precision Viticulture—Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography. Remote Sens. 2024, 16, 1419. https://doi.org/10.3390/rs16081419
Brandmeier M, Heßdörfer D, Siebenlist P, Meyer-Spelbrink A, Kraus A. Time Series Analysis of Multisensor Data for Precision Viticulture—Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography. Remote Sensing. 2024; 16(8):1419. https://doi.org/10.3390/rs16081419
Chicago/Turabian StyleBrandmeier, Melanie, Daniel Heßdörfer, Philipp Siebenlist, Adrian Meyer-Spelbrink, and Anja Kraus. 2024. "Time Series Analysis of Multisensor Data for Precision Viticulture—Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography" Remote Sensing 16, no. 8: 1419. https://doi.org/10.3390/rs16081419