High resolution cropland agreement map (30 m) circa 2020

Accurate and precise measurements of global cropland extent are needed for monitoring the sustainability of agriculture at all scales. Recent advancement in remote sensing and land cover mapping methods have greatly increased the ability to estimate cropland area distribution and trends. Here the FAO presents a map of cropland agreement produced by consolidating information at pixel level from six high-resolutions maps for <em>circa </em>2020. The following six high resolution layers were used: ESRI 10 meter LU/LC, FROM-GLC, GLAD, GLC-FCS30, Globeland30 and Worldcover. Two bands are included in the dataset: Simple agreement (values between 1 and 6) Detailed agreement (values between 1 and 63) The map, developed in the Google Earth Engine platform, combines the 6 land cover/cropland layers to show their cropland agreement on pixel level at a spatial resolution of 30 meters. The simple agreement has pixel values that range from 1 (only 1 dataset classifies as cropland) to 6 (all datasets agree on presence of cropland). Pixels with a value of 0 indicate pixels where all datasets agree on absence of cropland. The second band includes a detailed agreement, showing which combination of the 6 datasets classify a pixel as cropland. The overview table (<em>DetailedAgreement_LookupTable.xlsx</em>) shows what the pixel values of this detailed agreement (from 1 to 63) correspond to. The dataset has been uploaded in 16 tiles, in the preview below and in the file "A<em>CroplandAgreement_30m_Tiles.png</em>" the extent of each tile can be found. For more information on FAO statistics on land cover and land use: FAO. 2022. <em>Land use statistics and indicators. Global, regional and country trends, 2000–2020</em>. FAOSTAT Analytical Brief, no. 48. Rome. https://doi.org/10.4060/cc0963en FAO. 2021. <em>Land cover statistics. Global, regional and country trends, 2000–2019</em>. FAOSTAT Analytical Brief Series No. 37. Rome.精准细致的全球农田覆盖范围实测数据，是全尺度监测农业可持续性的必要基础。近年来，遥感技术与土地覆盖制图方法的长足进步，极大提升了农田面积分布与变化趋势的估算能力。本数据集由联合国粮食及农业组织（Food and Agriculture Organization, FAO）发布，为约2020年的六幅高分辨率农田分布图整合像素级信息后生成的农田一致性制图产品。本次制图采用的六组高分辨率图层如下：ESRI 10米土地利用/覆盖（LU/LC）、FROM-GLC、GLAD、GLC-FCS30、Globeland30及Worldcover。本数据集包含两个波段：其一为简单一致性波段（像素值范围为1至6），其二为详细一致性波段（像素值范围为1至63）。该制图基于谷歌地球引擎（Google Earth Engine）平台开发，通过整合上述六组土地覆盖/农田图层，以30米空间分辨率实现像素级的农田一致性展示。简单一致性波段的像素值介于1至6之间：值为1代表仅1组数据集将该像素归类为农田，值为6则代表全部6组数据集均判定该像素为农田；像素值为0时，表示所有数据集均一致判定该像素非农田。详细一致性波段则展示了六组数据集将某像素判定为农田的具体组合方式，配套的查阅表《DetailedAgreement_LookupTable.xlsx》明确了该波段1至63区间内各像素值对应的数据集组合情况。本数据集以16个瓦片形式发布，预览图及《ACroplandAgreement_30m_Tiles.png》文件中可查看各瓦片的覆盖范围。如需获取更多土地覆盖与土地利用相关的FAO统计数据信息，请参考以下文献：1. 联合国粮食及农业组织. 2022. 《土地利用统计与指标：2000-2020年全球、区域及国家趋势》. FAOSTAT分析简报，第48号. 罗马. https://doi.org/10.4060/cc0963en 2. 联合国粮食及农业组织. 2021. 《土地覆盖统计：2000-2019年全球、区域及国家趋势》. FAOSTAT分析简报系列第37号. 罗马。