Preprints
https://doi.org/10.5194/essd-2024-121
https://doi.org/10.5194/essd-2024-121
15 Apr 2024
 | 15 Apr 2024
Status: this preprint is currently under review for the journal ESSD.

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

Stefania Di Tommaso, Sherrie Wang, Rob Strey, and David B. Lobell

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.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Stefania Di Tommaso, Sherrie Wang, Rob Strey, and David B. Lobell

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2024-121', Anonymous Referee #1, 16 May 2024
  • RC2: 'Comment on essd-2024-121', Anonymous Referee #2, 17 May 2024
Stefania Di Tommaso, Sherrie Wang, Rob Strey, and David B. Lobell

Data sets

Mapping sugarcane globally at 10 m resolution using GEDI and Sentinel-2 Stefania Di Tommaso, Sherrie Wang, Rob Strey, and David B. Lobell https://zenodo.org/records/10871164

Stefania Di Tommaso, Sherrie Wang, Rob Strey, and David B. Lobell

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Short summary
Sugarcane plays a vital role in food, biofuel, and farmer income globally, yet its cultivation faces numerous social and environmental challenges. Despite its significance, accurate mapping remains limited. Our study addresses this gap by introducing a novel 10m global dataset of sugarcane maps spanning 2019–2022. Comparisons with field data, pre-existing maps, and official government statistics all indicate the high precision and recall of our maps.
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