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 # Land cover mapping the Orinoquía region 
 
-In this project, we worked with the Wildlife Conservation Society Colombia ([WCS Colombia](https://colombia.wcs.org/en-us)) to create up-to-date land cover maps of the [Orinoquía](https://colombia.wcs.org/en-us/Wild-Places/Orinoquia.aspx) region in Colombia. This natural region encompasses a high diversity of ecosystems, from seasonally flooded savanna to rainforest. In recent years, agricultural production has expanded, causing changes in these ecosystems. It is therefore critically important to present information on land use to policy makers so that they may balance the need for agricultural development and conserving the biodiversity and ecological functions of the region.
+In this [AI for Earth](https://www.microsoft.com/en-us/ai/ai-for-earth) project, we worked with the Wildlife Conservation Society Colombia ([WCS Colombia](https://colombia.wcs.org/en-us)) to create up-to-date land cover maps of the [Orinoquía](https://colombia.wcs.org/en-us/Wild-Places/Orinoquia.aspx) region in Colombia. This natural region encompasses a high diversity of ecosystems, from seasonally flooded savanna to rainforest. In recent years, agricultural production has expanded, causing changes in these ecosystems. It is therefore critically important to present information on land use to policy makers so that they may balance the need for agricultural development and conserving the biodiversity and ecological functions of the region.
 
 Specifically, we used a land use and land cover (LULC) map that was manually produced using satellite imagery and field data from 2010-2012 to train a semantic segmentation model for 12 land cover classes. The model can be applied to composites of Landsat 8 imagery collected in subsequent years to enable ecological analysis.