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The mapping layer

The STA logger isn’t a one trick pony. You can take the same unit and put it on a high-volume, vehicle-mounted sprayer, or a backpack sprayer. You can even put it on a tree planter, or handle for mapping cut and paint work!

STA logger on a tree planter

What is the mapping layer?

The mapping layer visualises the non-spraying workflows. If you spray for 3 seconds, the spray data will appear everywhere the logger was located during those 3 seconds. However, in a mapping situation, it will appear as a single point at the location you were when you first pressed the button.

Mapping data appears as points.

This is ideal for mapping single point locations like the installation of a tree, of the location of a tree that was cut down.

How to use the data

When viewing the ‘point’ data of the STA logger in the attribute table, if you sprayed for 3 seconds, you would get 3 rows of data where the “GPS_trigger” column equals ‘1’ (‘0’ means the trigger was not pulled). However, if you look at the “Mapping” column, you would get a ‘1’ on the first row, but not the subsequent two rows.

This means, if planting a tree, and you accidentally held the button for 3 seconds, you will still only get one plant recorded. And if you wanted to sum the number of plants installed for a day, you would sum the “Mapping” column, not the “GPS_trigger” column.

In this example, the newest data is at the top of the list. The button was pressed for 2 seconds. The first point (bottom) has a ‘1’ in both the GPS Trigger and Mapping columns. But not in the second (middle) row. Both columns have a ‘0’ in the top row.

Private Contractors

Contractors that offer weed management, land management, site rehabilitation / restoration services.

Click TO VIEW SAMPLE DATA

Government and Industry

Organisations who have weed management teams or engage private contractors. Industry (like forestry, mining, oil and gas, water, planning, etc.) who have legal environmental obligations and are required to report to government.

CLICK TO VIEW SAMPLE DATA

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