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.
For EE Code Editor:
https://code.earthengine.google.com/?accept_repo=users/embrslab/ModL2T_BA
Clone EE Git Repository in Terminal:
git clone https://earthengine.googlesource.com/users/embrslab/ModL2T_BA
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']});
We use the following datasets:
- MCD64A1 Burned Area, 500m
- MOD09A1 8-Day Composite Surface Reflectance, 500m
- MxD14A1 Active Fires, 1km
- Surface Reflectance, 30m
- 10-class global land cover for 2010, 30m
- March 10, 2018: MCD64A1 C6 added as a collection in GEE
- Earlier versions of the Landsat collections used in this study are now deprecated in the GEE catalog
- 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
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