ModL2T Burned Area

ModL2T: hybrid MODIS and Landsat algorithm for estimating post-monsoon burned area from agricultural fires in northwestern India

This algorithm is based in Google Earth Engine (EE) and R.

EE Repository

For EE Code Editor:

https://code.earthengine.google.com/?accept_repo=users/tl2581/ModL2T_BA

Clone EE Git Repository in Terminal:

git clone https://earthengine.googlesource.com/users/tl2581/ModL2T_BA

ModL2T Burned Area in EE

The output dataset, ModL2T burned area, is annual and at 30-m spatial resolution.

Example script:

// Read ModL2T burned area in Earth Engine
var modl2tBA = ee.ImageCollection('projects/GlobalFires/IndiaAgFires/ModL2T_BA');

// Example: filter 'modl2tBA' image collection for the year 2016
// Each image pixel has confidence values from 1-6
var modl2tBA_yrConf = modl2tBA.filter(ee.Filter.calendarRange(2016,2016,'year')).first();

// We used only values > 1 in our final classification of burned area
var modl2tBAyr = modl2tBA_yrConf.gt(1).selfMask();

// Visualize burned area classification confidence
Map.setCenter(76,30,7);
Map.addLayer(modl2tBA_yrConf, {min: 1, max: 6, palette: ['yellow','orange','red']});

Input Datasets

We use the following datasets:

MODIS, Collection 6:

• MCD64A1 Burned Area, 500m
• MOD09A1 8-Day Composite Surface Reflectance, 500m
• MxD14A1 Active Fires, 1km

Landsat 5 (TM), 7 (ETM+), 8 (OLI/TIRS):

• Surface Reflectance, 30m

GlobeLand30:

• 10-class global land cover for 2010, 30m

Updates

• March 10, 2018: MCD64A1 C6 added as a collection in GEE

Known Issues

• MODIS and Landsat NBR composites were projected to geographic projection (lat/lon, EPSG:4326) and exported as assets to speed up calculations in GEE and prevent computational timeouts

Publication

Liu T., Marlier M.E., Karambelas A.N., Jain M., Singh S., Singh M.K., Gautam, R., and DeFries R.S. (2019). Missing emissions from post-monsoon agricultural fires in northwestern India: regional limitations of MODIS burned area and active fire products. Environ. Res. Commun., 1, 011007. https://doi.org/10.1088/2515-7620/ab056c

EarthArXiv Preprint DOI: https://doi.org/10.17605/OSF.IO/9JVAK