The dataset of main grain land changes in China over 1985–2020

Continuous, Accurate, and detailed information on main grain land (MGL) areas is crucial for provisioning food security and making policies affecting sustainable agricultural production. Here, we developed the change map of MGL with resolution 30m in China for the period 1985–2020 using the Landsat image-based random forest algorithm on the GEE platform. Finally, the planting intensity, gain time and loss time of MGL was calculated. Results indicate that our mapping results are highly consistent with the annual planting area of various grain crops according to national statistics. The proportion of different MGL types in 2020 is presented as follows: single maize (38.55%) > single rice (23.23%) > single wheat (15.42%) > wheat & maize (12.60%) > double rice (7.65%) > wheat & rice (2.48%). Due to over half of MGL expansion occurring after 2000, the average planting intensity of MGL in China is 19.74 years in the past 36 years. The consistent, high-resolution data of MGL change can support progress toward sustainable agricultural management and food production.For the convenience of users, the detailed classification data of MGL year by year has been made public on the GEE platform. Users with needs can view and download detailed MGL data for any year, including 7 MGL subtypes, according to the following link. Data viewing and download links: https://code.earthengine.google.com/d371ab6f6c1bd274c85af270e4ad09c5 Directly call ID of dataset in GEE: var MGL = ee.ImageCollection(“projects/ee-linshi-428901/assets/MrainlandType”) Data usage code： var year = 2020 // Any year between 1985 and 2020 var mglyear = MGL.filterMetadata('time', "equals", year).max() var visParams = { min: 1, max: 7, palette: ['cyan', 'blue','green', 'yellow', 'red','purple','white'] }; Map.addLayer(mglyear.selfMask(),visParams,"MGL"+year)