Here you can find the maps used as a reference by MapBiomas Trinacional Atlantic Forest to train the classification algorithms and to validate the quality of the project's automatic classifications. These references come from various organizations and have varied geographical and temporal scales.
Some of these maps still do not have public access because they are in the process of being published. When they are available, their corresponding link will be incorporated to allow the data to be downloaded directly from the original source.
| Name of the map | Source/Author | Description | Link |
| Copernicus Global Land Service: Land Cover 100m: collection 3 | Buchhorn, M. ; Smets, B. ; Bertels, L. ; De Roo, B. ; Lesiv, M. ; Tsendbazar, N. - E. ; Herold, M. ; Fritz, S. Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2019: Globe 2020. | Land cover maps present spatial information on different types of land cover, such as forests, grasslands, croplands, lakes or wetlands. | Access |
| Global Forest Change 2000–2015 | University of Maryland | Results of time series analysis of Landsat imagery to characterise global forest extent and change between 2000 and 2015. | Access |
| ESRI 10m Annual Land Use Land Cover (2017-2022) | Karra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. | Time series of annual global land use and land cover (LULC) maps. It currently has data from 2017-2022. The maps are derived from ESA Sentinel-2 imagery at 10 m resolution. | Access |
| ETH Global Canopy Height 2020 | Lang, N., Jetz, W., Schindler, K. et al. A high-resolution canopy height model of the Earth. Nat Ecol Evol (2023). https://doi.org/10.1038/s41559-023-02206-6 | Global canopy map for the year 2020. The product is based on Sentinel-2 imagery. | Access |
| Coverage map of the Republic of Paraguay | FCA/CIF/FFPRI, 2013 | The elaboration of the map was carried out from the analysis and interpretation of Landsat 5 satellite images (TM) (E 1:250.000) | Access |
| Land use change in Paraguay | INFONA 2018, 2023 | Land use change map between 2016 and 2017, obtained by classifying Landsat 8 images | Access |
| Annual Agriculture in the Paraguayan Chaco 2000/2001 | Agrosatélite Geotecnología Aplicada | Map of soy crop areas in 2000/2001 in the Paraguayan Chaco, elaborated based on the interpretation of Landsat images of 30 m spatial resolution. | |
| Annual Agriculture in the Paraguayan Chaco 2006/2007 | Agrosatélite Geotecnología Aplicada | Map of soy crop areas in 2006/2007 in the Paraguayan Chaco, elaborated based on the interpretation of Landsat images of 30 m spatial resolution. | |
| Annual Agriculture in the Paraguayan Chaco 2016/2017 | Agrosatélite Geotecnología Aplicada | Map of soy crop areas in 2016/2017 in the Paraguayan Chaco, elaborated based on the interpretation of Landsat images of 30 m spatial resolution. | Acceder |
| Soy Crops in the Eastern Region of Paraguay 2014 | INFONA/SIRT 2014 | ||
| Land Use and Land Cover Map of the Paraguayan Chaco 2018 | DLR/INFONA/WWF 2019 | Land Use and Land Cover Map of the Paraguayan Chaco obtained through classification of Landsat 8 OLI images for 2017 and 2018 | |
| MapBiomas Chaco-
Land Use and Land cover from 1985 to 2022 of the Gran Chaco Americano. Collection 4.0 | MapBiomas Chaco Project – Collection 4 of the Annual Series of Land Use and Land Cover Maps of Chaco | Collection 4 of MapBiomas Chaco includes annual data of land use and land cover for the period 1985 to 2022 | Acceder |