Mangrove mapping using cloud computing and a specific spectral index to support management activities: a semi-arid Colombian Caribbean case study

Abstract

Mangrove mapping is the foundation for sustainable management-driven zoning at sub-national scales. However, many environmental authorities do no have access to updated mangrove cartography and budget for field validation is usually limited. The objective of this article was to assess the performance of the Mangrove Vegetation Index (MVI) to update mangrove extent in a semi-arid area in the Southern Caribbean. The Sucre State (Colombia) was used as a sample area for a multi-temporal reconstruction (2017-2021) based on MVI, Sentinel 2 imagery, and Google Earth Engine computing. Field validation was assisted with above-ground observation using a commercial-grade un-tripulated aerial vehicle (DJI Phantom 3 Advanced) to explore difficult access internal areas in large patches. Mangrove area varied significantly between rainy and dry seasons due to a change in greenness. A total of 8924 ha (Kappa coefficient: 0.78) were estimated using a multi-temporal mosaic, covering all management categories. Comparison with previous estimates by global and national efforts showed a great degree of consistency. We concluded that this simple method offers a rapid alternative for updating mangrove zoning in semi-arid regions in Colombia. Advantages and limitations of the method are discussed.