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A suite of utility functions for discovering and managaing metadata associated
with sets of spatially unique "known locations".


This package is intended to be used in support of data management activities associated with fixed locations in space. The motivating fields include both air and water quality monitoring where fixed sensors report at regular time intervals.

When working with environmental monitoring time series, one of the first things you have to do is create unique identifiers for each individual time series. In an ideal world, each environmental time series would have both a locationID and a sensorID that uniquely identify the spatial location and specific instrument making measurements. A unique timeseriesID could be produced as locationID_sensorID. Location metadata associated with each time series would contain basic information needed for downstream analysis including at least:

timeseriesID, locationID, sensorID, longitude, latitude, ...

Unfortunately, we are rarely supplied with a truly unique and truly spatial locationID. Instead we often use sensorID or an associated non-spatial identifier as a standin for locationID.

Complications we have seen include:

A Solution

A solution to all these problems is possible if we store spatial metadata in simple tables in a standard directory. These tables will be referred to as collections. Location lookups can be performed with geodesic distance calculations where a location is assigned to a pre-existing known location if it is within radius meters. These will be extremely fast.

If no previously known location is found, the relatively slow (seconds) creation of a new known location metadata record can be performed and then added to the growing collection.

For collections of stationary environmental monitors that only number in the thousands, this entire collection (i.e. “database”) can be stored as either a .rda or .csv file and will be under a megabyte in size making it fast to load. This small size also makes it possible to store multiple known location files, each created with different locations and different radii to address the needs of different scientific studies.

Immediate Advantages

Working in this manner will solve the problems initially mentioned but also provides further useful functionality:

This project is supported by Mazama Science.