trend

trend is a web tool using D3 and Semantic UI for visualizing Gradient Nearest Neighbor (GNN) trends over time. GNN is a forest vegetation mapping method based on ordination (canonical correspondence analysis) and nearest-neighbor imputation.

We have run GNN models across Washington, Oregon and California from 1984 to 2012 (data avaialable online at http://lemma.forestry.oregonstate.edu/data). Using these models and ancillary stratifying variables (such as ownership, disturbance patterns, etc.), we create strata that include counts of pixels in a stratum and statistics from GNN continuous variables. The trend tool allows a user to:

1. select a continuous variable to graph
2. select a categorical variable to represent multiple series
3. define the time range
4. narrow the focus area based on other categorical (e.g. stratifying) variables

We anticipate that the tool will most likely be used by forest managers for assessing regional-scale trends, but the application should be adaptable to include any categorical/continuous variables.

Inputs

trend relies on a JSON file to describe the data fields and point to a CSV file which holds the actual data. Right now it is hard-coded to read from a file called 'trajectory.json', which should be a user input in later iterations. For now, we have not posted the data files as they are big and change often, but they are currently available here:

• http://lemma.forestry.oregonstate.edu/sandbox/trajectory/trajectory.json
• http://lemma.forestry.oregonstate.edu/sandbox/trajectory/trajectory.csv

Status

This is very much a research tool right now and apt to large changes.

Example

We are currently hosting the example application at:

• http://lemma.forestry.oregonstate.edu/sandbox/trajectory/index.html