Mapping sugarcane globally at 10 m resolution using GEDI and Sentinel-2

Dataset Abstract:
Sugarcane is an important source of food, biofuel, and farmer income in many countries. At the same time, sugarcane is implicated in many social and environmental challenges, including water scarcity and nutrient pollution. Currently, few of the top sugar-producing countries generate reliable maps of where sugarcane is cultivated. To fill this gap, we introduce a dataset of detailed sugarcane maps for the top 13 producing countries in the world, comprising nearly 90% of global production. Maps were generated for the 2019-2022 period by combining data from the Global Ecosystem Dynamics Investigation (GEDI) and Sentinel-2 (S2). GEDI data were used to provide training data on where tall and short crops were growing each month, while S2 features were used to map tall crops for all cropland pixels each month. Sugarcane was then identified by leveraging the fact that sugar is typically the only tall crop growing for a substantial fraction of time during the study period. Comparisons with field data, pre-existing maps, and official government statistics all indicated high precision and recall of our maps. Agreement with field data at the pixel level exceeded 80% in most countries, and sub-national sugarcane areas from our maps were consistent with government statistics. Exceptions appeared mainly due to problems in underlying cropland masks, or to under-reporting of sugarcane area by governments. 
The final maps should be useful in studying the various impacts of sugarcane cultivation and producing maps of related outcomes such as sugarcane yields.

Dataset: 
5 bands
b1: Number of tall months
b2: Sugarcane Map: 0 = non-sugarcane, 1 = sugarcane
b3: ESA crop mask: 0 = non-cropland, 1 = cropland
b4: ESRI crop mask: 0 = non-cropland, 1 = cropland
b5: GLAD crop mask: 0 = non-cropland, 1 = cropland

The dataset can be accessed on Google Earth Engine (GEE) at 
https://code.earthengine.google.com/?asset=projects/lobell-lab/gedi_sugarcane/maps/imgColl_10m_ESAESRIGLAD

Example GEE script for visualizing and masking the sugarcane maps by country available at:
https://code.earthengine.google.com/d4d43daf0b059a553f2ed75f2cb1cf1c?asset=projects%2Flobell-lab%2Fgedi_sugarcane%2Fmaps%2FimgColl_10m_ESAESRIGLAD