Assessment of TerraClass and MapBiomas data on legend and map agreement for the Brazilian Amazon biome

ABSTRACT Reliable environmental monitoring and evaluation require high-quality maps of land use and land cover. For the Amazon biome, the TerraClass and MapBiomas projects apply different methodologies to create these maps. We evaluated the agreement between land cover and land use maps generated by TerraClass and MapBiomas (Collections 2 and 3) for the Brazilian Amazon biome, from 2004 to 2014. Specifically, we: (1) described both project legends based on the LCCS (Land Cover Classification System); (2) analyzed the differences between their classes; and (3) compared the mapping differences among the Brazilian states that are totally or partially covered by the Amazon biome. We compared the classifications with a per-pixel approach and performed an evaluation based on agreement matrices. The overall agreement between the projects was 87.4% (TerraClass x MapBiomas 2) and 92.0% (TerraClass x MapBiomas 3). We analyzed methodological differences to explain the disagreements in class identification. We conclude that using these maps together without a properly adapted legend is not recommended for the analysis of land use and land cover change. Depending on the application, one mapping system may be more suitable than the other.

摘要
可靠的环境监测与评估需要高质量的土地利用与土地覆盖地图。针对亚马逊生物群区，TerraClass与MapBiomas项目采用不同方法学生成此类地图。我们针对2004至2014年巴西亚马逊生物群区内由TerraClass和MapBiomas（第2版与第3版集合）生成的土地覆盖与土地利用地图，评估了二者的一致性。具体而言，我们完成了以下工作：(1) 基于土地覆盖分类系统（Land Cover Classification System，LCCS），对两个项目的分类图例进行说明；(2) 分析了二者分类体系间的差异；(3) 对比了亚马逊生物群区全部或部分覆盖的巴西各州的制图差异。我们采用逐像素方法对分类结果进行对比，并基于一致性矩阵开展评估。两个项目的总体一致性分别为87.4%（TerraClass × MapBiomas 第2版集合）与92.0%（TerraClass × MapBiomas 第3版集合）。我们通过分析方法学差异，对分类识别中的不一致性进行了解释。我们得出结论：若未对图例进行适配调整，不建议将这两类地图直接结合用于土地利用与土地覆盖变化分析。根据具体应用场景，二者之一的制图体系可能更具适配性。