Cropland was treated as consisting of four subclasses and classified using the local adaptive random forest models, Global Spatial Temporal Spectral Library (GSPECLib), and time series of Landsat imagery.
This type of land has clear traits of intensive human activity. It varies a lot from bare field, seeding, and crop growing to harvesting. It can be easily identified if edges or textures are visible and the land parcels are sufficiently large. Fruit trees are classified as forests. Pasture can include the transition from cropland to natural grassland. Dataset link: http://data.ess.tsinghua.edu.cn/fromglc2015_v1.html
Cropland was treated as an independent layer and classified using 91,433 training samples and multitemporal Landsat imagery.
Land used for planting crops including paddy fields, irrigated dry land, and rainfed dry land; land used for growing vegetables, herbage, greenhouses, or fruit trees and other economically valuable trees; also land used for planting shrub cash crops such as tea and coffee Dataset link: http://www.globallandcover.com/GLC30Download/index.aspx
Developed based on both crop phenology and the regular distribution patterns of cultivated land; object-based segmentation was then overlaid onto potential images of cultivated land. Using virtual interpretation, only objects displaying regular man-made patterns such as circles or rectangles were identified as cultivated land.
The definition of cropland in this study is consistent with FAO’s definition of “arable lands and permanent crops”; “permanent pastures” is not included. Dataset link: http://data.ess.tsinghua.edu.cn/data
Composited from four existing cropland maps, including FROM_GLC and FROM_GLC_agg, and two 250 m masked cropland layers
There are several rules for defining cropland including the following: (1) the minimum mapping unit of a particular crop is an area of Landsat pixels (0.81 hectares); (2) all cultivated plants harvested for food, feed, and fiber, including plantations (e.g., orchards, vineyards, coffee and tea, and rubber plantations), are included; (3) >50% of the pixel is cropped; and (4) irrigation is defined as the artificial application of any amount of water to overcome crop water stress. Dataset link: not available
An ensemble of methods was employed, including spectral matching techniques, the Automated Cropland Classification Algorithm (ACCA), and the hierarchical segmentation (HSeg) algorithm based on the Landsat 30 m Global Land Survey 2010 (GLS2010) dataset and a suite of secondary data (e.g., long-term precipitation and temperature data and a DEM).
Lands cultivated with plants harvested for food, feed, and fiber, including both seasonal crops (e.g., wheat, rice, corn, soybeans, and cotton) and continuous plantations (e.g., coffee, tea, rubber, cocoa, and oil palm). Cropland fallows are lands uncultivated during a season or a year but are farmlands and are equipped for cultivation, including plantations. Dataset link: https://lpdaac.usgs.gov/news/release-of-gfsad-30 meter-cropland-extent-products/
Integration of pixel-based classifiers (random forest and support vector machines) and an object-based classifier (Recursive Hierarchical Image Segmentation) to obtain the cropland map for each ecological zone