FORMA Vegetation T-Statistics

WRI/GFW/FORMA/vegetation_tstats
Dataset Provider
Earth Engine Snippet
ee.ImageCollection("WRI/GFW/FORMA/vegetation_tstats")
Tags
forests deforestation modis monitoring daily forma gfw wri

Description

FORMA alerts are detected using a combination of two MODIS products: NDVI (Normalized Difference Vegetation Index) and FIRMS (Fires Information for Resource Management System). NDVI updates are processed every 16 days, while fire updates are processed daily. Models are developed individually for each ecogroup to relate the two inputs to the area of clearing, using the Hansen annual tree cover loss data to train the model. The minimum threshold to qualify as an alert is 25% of the pixel cleared, though thresholds vary by ecogroup to minimize false positives. Here is an example script for a quick introduction to the FORMA datasets.

The images in this ImageCollection contain the “reversed rectified t-statistics” used in calculating NTT, the vegetation color index derived from MODIS NDVI that FORMA uses to measure browning. Using a sum reducer on over various date ranges in this ImageCollection produces an “NTT” image.

The images are broken by "ecogroup". Ecogroup geometries can be found here.

Bands

Resolution
250 meters

Bands

Name Min Max Description
tstat_r 0* 25.41*

Reversed rectified, ie (max(0,-t_stat)), t-statistics.

* estimated min or max value

Image Properties

Image Properties

Name Type Description
year INT

Year of the most recent data included in the dataset

biweekly INT

The biweekly (every 16 days) period of the year

ecogroup_id STRING

ID of associated ecogroup. Ecogroup geometries and IDs are available in the fusion table found here

Terms of Use

Terms of Use

The FORMA datasets are available without restriction on use or distribution. WRI does request that the user give proper attribution and identify WRI and GFW, where applicable, as the source of the data.

Explore in Earth Engine

var dataset = ee.ImageCollection('WRI/GFW/FORMA/vegetation_tstats')
                  .filter(ee.Filter.date('2018-07-01', '2018-07-15'));
var tstat = dataset.select('tstat_r');
var visParams = {
  min: 0.0,
  max: 1.0,
};
Map.setCenter(25.73, -7.61, 2);
Map.addLayer(tstat, visParams, 'Reversed rectified t-statistics');