Advanced

Evaluation of water stress mapping methods in vineyards using airborne thermal imaging

Zuta, Alon LU (2020) In Master Thesis in Geographical Information Science GISM01 20201
Dept of Physical Geography and Ecosystem Science
Abstract
With low cost and high efficiency, use of airborne infrared thermography imaging from an unmanned aerial vehicle (UAV) has become a widely used technique to measure plant water stress. With that, the use of UAV mounted thermal camera as a precision agriculture technique to map crop water stress is not trivial and its success is depended on variety of factors which are still needed to be studied and understood.

The current research study sought to explore three crucial components of mapping water status based on airborne thermal imaging: a) the quality, quantity and distribution of the sampling points, b) the type of thermal index used, and c) the choice of interpolation method. The following three objectives were highlighted:
a)... (More)
With low cost and high efficiency, use of airborne infrared thermography imaging from an unmanned aerial vehicle (UAV) has become a widely used technique to measure plant water stress. With that, the use of UAV mounted thermal camera as a precision agriculture technique to map crop water stress is not trivial and its success is depended on variety of factors which are still needed to be studied and understood.

The current research study sought to explore three crucial components of mapping water status based on airborne thermal imaging: a) the quality, quantity and distribution of the sampling points, b) the type of thermal index used, and c) the choice of interpolation method. The following three objectives were highlighted:
a) Comparison of two commonly used thermal indices, the crop water stress index (CWSI) and the Jones stomatal conductance index (Ig), to assess index performance in regions with high climatic variability.
b) Assessment of the impact of spatial and temporal changes on the performance of interpolation algorithms.
c) Investigation of the possibility of mapping vineyard water stress through collection and analysis of the vineyard cover crop thermal data in comparison to the grapevine canopy.
The study was conducted in two commercial vineyards in the Rheingau region of Germany. Airborne thermal imaging using UAV was collected at four different periods during the 2019 growing season (July-September) and was accompanied by ground measurements including mid-day stem water potential (Ψstem) and proximal thermal imaging.
The airborne data was interpolated using the following interpolation algorithms: Inverse Distance Weighting (IDW), Kriging, Local Polynomial, and Spline. The resulting interpolated surfaces were evaluated through cross validation and, through comparison to the ground measurements.
Cross-validation results showed definite preference for CWSI based interpolations. The result can be attributed to the range of potential values rather than the suitability of the index. In contrast, comparison to the ground measurement results show definite preference for Ig based interpolations. Both the cross validation and the comparison to the ground measurement results showed a high range of interpolation algorithms varying spatially between the two vineyards and temporarily between the different measurement dates. Cross-validation analyses and comparison with the proximal thermal imaging measurements revealed a preference for cover crop-based interpolation. While comparison with the Ψstem showed a preference for the cover crop during the July measurements and preference for the grapevine during the August-September measurements. It is inferred that the results are related to the small sample size of the Ψstem procedure and operator bias.
Results of the study indicated that the Ig index exhibits much higher suitability than CWSI for mapping water stress index in regions with higher humidity and variable climate such as the Rheingau. Additionally, the study showed the affect of sampled data points on the resulting interpolated surface, the importance of evaluating different algorithms and choosing the most suitable one. Finally, the results demonstrated that cover crop-based data have the potential to producing better quality water stress maps in steep-slopped vineyards which are characterized by low soil depth. Further research is thus recommended to evaluate suitability of this method in vineyards with deeper soil profile to confirm that this phenomenon is not restricted to steeped sloped vineyards. (Less)
Popular Abstract
Water budget is a key factor in quality grape development and insufficient water supply might limit the quality and yield of grapes for wine. This issue is becoming more prevalent due to climate change which causes shifts in the precipitation rate and distribution resulting in increased severity and frequency of droughts. The situation can be mitigated through implementation of irrigation systems. However, spatial variability in water requirements, caused by variations in soil, slope, aspect and other variables across a vineyard limits the efficient use of such systems. Therefore, it is vital to characterize spatial variability before deciding on an irrigation strategy.
Due to its low cost and high efficiency, the use of airborne... (More)
Water budget is a key factor in quality grape development and insufficient water supply might limit the quality and yield of grapes for wine. This issue is becoming more prevalent due to climate change which causes shifts in the precipitation rate and distribution resulting in increased severity and frequency of droughts. The situation can be mitigated through implementation of irrigation systems. However, spatial variability in water requirements, caused by variations in soil, slope, aspect and other variables across a vineyard limits the efficient use of such systems. Therefore, it is vital to characterize spatial variability before deciding on an irrigation strategy.
Due to its low cost and high efficiency, the use of airborne infrared thermography imaging from an unmanned aerial vehicle (UAV) has become a widely used technique for measuring plant water stress. The technique is based on a plant’s physiological mechanism during which a plant under water stress reduces transpiration through stomatal closure to conserve water. The stomatal closure leads to an increase in plant surface temperature which can be detected by thermal camera image acquisition. Mounting the camera on an UAV enables coverage of a large area in a short time.
Rapid improvement of these technologies with considerable reduction in cost, and the evolvement of open source electronic community have the potential to enable this tool to be available for winegrowers. In consequence, this leads to both reduction in irrigation costs and more sustainable use of water which is a vital necessity in the current context of climate change and water scarcity. Use of UAV-based thermography to map crop water stress is not trivial and its success is dependent on several factors. Thus, continued study is necessary to enhance the efficiency and accuracy of the process.
Our study was conducted in two commercial steeped sloped vineyards in the Rheingau region of Germany, renowned for high-quality wine production. In recent years due to climate change, droughts have become prevalent in this temperate climate, resulting in the need for irrigation. This is the first time that this type of study was conducted in this climate type as previous studies were restricted to semi-arid and Mediterranean climate regions.
The study consisted of three objectives: A. comparing two commonly used thermal indices, the crop water stress index (CWSI) and the Jones stomatal conductance index (Ig) to observe the most suitable index for temperate climates. Thermal indices are used to quantify the relationship between water stress and plant temperature. B. Assessing spatial and temporal impacts on the performance of different interpolation algorithms. Interpolation is used to determine values in locations that could not be sampled. The choice of the most appropriate interpolation method was not properly covered in past studies and in the current experiment, the importance of selecting an appropriate method was highlighted. C. Exploring the possibility of mapping water stress by collecting and analysing thermal data of the vineyard cover crop rather than the grapevine canopy itself. Grapevine canopy structure is highly complex and narrow in width which limits the amount of data points that can be sampled by UAV. In contrast, cover crops have a much simpler structure and the greater width is beneficial for data point collection.
The study occurred during the 2019 growing season (July-September). Airborne thermal imaging using UAV was collected at four different periods and was accompanied by ground measurements used to validate the airborne data.
Results of the study showed that the Ig index was more suitable than the CWSI index for mapping water stress in regions with climatic variability and high humidity such as the Rheingau, Germany. Additionally, it was found that no single interpolation method fits both vineyards, crop type (cover and grapevine) and measurement dates, indicating the importance of the comparison and selection of the most appropriate interpolation algorithm. Finally, the results showed that cover crop provides better quality data in terms of quantity and distribution of sample points relatively to grapevine data. Thus, the recommendation for future studies stresses the importance in conducting similar experiments in vineyards with deeper soil profile to confirm that this phenomenon is not restricted to steeped sloped vineyards.
The study highlighted several important considerations and implications in measuring and mapping the spatial and temporal crop water stress in vineyards. The results gathered will assist future research on further development of this technique. (Less)
Please use this url to cite or link to this publication:
author
Zuta, Alon LU
supervisor
organization
course
GISM01 20201
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Geography, Geographical information systems, GIS, Remote sensing, Cover crop, Thermal imaging, Spatial variability, vineyards, interpolation, water stress index, CWSI, Ig, stem water potential, UAV, Rheingau, Interpolation.
publication/series
Master Thesis in Geographical Information Science
report number
117
language
English
additional info
External supervisor: Prof. Dr. Manfred Stoll, Geisenheim University
id
9015805
date added to LUP
2020-06-11 17:38:57
date last changed
2020-06-11 17:38:57
@misc{9015805,
  abstract     = {With low cost and high efficiency, use of airborne infrared thermography imaging from an unmanned aerial vehicle (UAV) has become a widely used technique to measure plant water stress. With that, the use of UAV mounted thermal camera as a precision agriculture technique to map crop water stress is not trivial and its success is depended on variety of factors which are still needed to be studied and understood.

The current research study sought to explore three crucial components of mapping water status based on airborne thermal imaging: a) the quality, quantity and distribution of the sampling points, b) the type of thermal index used, and c) the choice of interpolation method. The following three objectives were highlighted:
a) Comparison of two commonly used thermal indices, the crop water stress index (CWSI) and the Jones stomatal conductance index (Ig), to assess index performance in regions with high climatic variability.
b) Assessment of the impact of spatial and temporal changes on the performance of interpolation algorithms.
c) Investigation of the possibility of mapping vineyard water stress through collection and analysis of the vineyard cover crop thermal data in comparison to the grapevine canopy. 
The study was conducted in two commercial vineyards in the Rheingau region of Germany. Airborne thermal imaging using UAV was collected at four different periods during the 2019 growing season (July-September) and was accompanied by ground measurements including mid-day stem water potential (Ψstem) and proximal thermal imaging. 
The airborne data was interpolated using the following interpolation algorithms: Inverse Distance Weighting (IDW), Kriging, Local Polynomial, and Spline. The resulting interpolated surfaces were evaluated through cross validation and, through comparison to the ground measurements.
Cross-validation results showed definite preference for CWSI based interpolations. The result can be attributed to the range of potential values rather than the suitability of the index. In contrast, comparison to the ground measurement results show definite preference for Ig based interpolations. Both the cross validation and the comparison to the ground measurement results showed a high range of interpolation algorithms varying spatially between the two vineyards and temporarily between the different measurement dates. Cross-validation analyses and comparison with the proximal thermal imaging measurements revealed a preference for cover crop-based interpolation. While comparison with the Ψstem showed a preference for the cover crop during the July measurements and preference for the grapevine during the August-September measurements. It is inferred that the results are related to the small sample size of the Ψstem procedure and operator bias. 
Results of the study indicated that the Ig index exhibits much higher suitability than CWSI for mapping water stress index in regions with higher humidity and variable climate such as the Rheingau. Additionally, the study showed the affect of sampled data points on the resulting interpolated surface, the importance of evaluating different algorithms and choosing the most suitable one. Finally, the results demonstrated that cover crop-based data have the potential to producing better quality water stress maps in steep-slopped vineyards which are characterized by low soil depth. Further research is thus recommended to evaluate suitability of this method in vineyards with deeper soil profile to confirm that this phenomenon is not restricted to steeped sloped vineyards.},
  author       = {Zuta, Alon},
  keyword      = {Geography,Geographical information systems,GIS,Remote sensing,Cover crop,Thermal imaging,Spatial variability,vineyards,interpolation,water stress index,CWSI,Ig,stem water potential,UAV,Rheingau,Interpolation.},
  language     = {eng},
  note         = {Student Paper},
  series       = {Master Thesis in Geographical Information Science},
  title        = {Evaluation of water stress mapping methods in vineyards using airborne thermal imaging},
  year         = {2020},
}