There are many scenarios where data can play an important role on a vineyard. While these situations are very different, they follow a similar data-usage pattern. This document aims to document a common data cycle that can be applied to many areas of your vineyards
Collection
Visualization
Filtering and Trimming
Interpolation
Sampling Validation Points
Translation
Data Collection
There are many ways to collect spatial data on your farm:
Proximal Sensors: Proximal sensors are devices that are used in the field to measure things like NDVI, soil electrical conductivity, harvest yield, and more. These sensors log data that can often be imported directly into myEV.
Handheld Collector Data: myEV allows data to be collected directly from a mobile device in the field. Any kind of information that can be counted, seen, etc, by a human being, can be collected using a data collector.
Remote Sensors: More and more, services are popping up that give growers access to remotely captured data – usually gathered by satellites in space. This data can come in many forms but is often a raster image.
Once data is in myEV, it can be organized by folder, shared with collaborators, and even edited directly.
Data Visualization
Visualization is the process of representing data visually. Within myEV, this means coloring mapped data based on variables. Each dataset in myEV (as well as farms/farm blocks) has a series of settings for establishing how the data is visualized. Visualization is important throughout the following steps as it provides visual feedback as data is being processed.
Filtering and Trimming
Data collected within biological systems (like vineyards) tends to have noise and extend beyond the geographic boundary that we are interested in learning about. myEV provides simple features that allow for noise to be filtered out and data to be trimmed to areas of interest. By filtering and trimming data, our visualization will become more distinct and we will begin to see trends emerging within the data.