Enhance and Augment Statistical Analysis Abilities form Unified Data Sets
Support researchers in the evaluation of citrus scions for tolerance to Citrus Greening (HLB)
In the challenge for researchers to find scions with higher tolerance to HLB, Plant Scientists not only need precise data, they need all of it. They needed assistance in compiling the various data sources and data sets into one unified place to perform statistical analysis.
Digitize trees with LiDAR and aerial multispectral imagery, combined with plot map of trial design and data collected by hand from trial cooperators
Not only did we digitize GroveTracker LiDAR data, and completed an insight-specific multispectral data collect with VitalityTracker, we applied our Bring-Your-Own-Data approach to AgLayers where the client brings their own historical, current, or third-party data sets to augment the data. In this case, the client brought their trial experimental design data and observations on tree mortality.
We fused the data to create a Layer 0 + 1 with the trial experimental design data set which allowed the client’s Plant Scientists to perform a statistical analysis and create a variety performance data set.
Unified data set with the scion type down to the individual tree + associated LiDAR and aerial data
Our client is now able to characterize the performance of varieties and their tolerance to Citrus Greening on a per plot basis. Due to the level of fused data sets, early analysis shows significant differences in scions, even though the trees are still quite small.
LiDAR point cloud of Tango scion and associated map with plant volume:
|1 – Digitize AGERpoint collected data:
||4 – Fuse Data:
||6 – Collaborate
|2 – Insight-specific data collects:
||5 – Statistical Analysis
|3 – Bring Your Own Data (BYOD):
||7 – Synthesize