Gridded 5-arcmin, simultaneously farm-size- and crop-specific harvested area for 56 countries

There are over 608 million farms around the world but they are not the same. We developed high spatial resolution maps telling where small and large farms were located and which crops were planted for 56 countries. We checked the reliability and have the confidence to use them for the country-level and global studies. Our maps will help more studies to easily measure how agriculture policies, water availabilities, and climate change affect small and large farms respectively.

The code, source data, and the simultaneously farm size- and crop-specific harvested area, including the GAEZ based downscaled map and SPAM based downscaled map, are open-access, free, and available, which could be found below. The downscaled maps are available in *.csv files for each crop and farming system. Each *.csv file provides the grid cell index, administrative unit index, crop name, farm size, harvested area, and x and y coordinates in the projection of WGS84.

File name of maps *.csv: [spam/gaez]_[crop name]_[farming system]
[spam/gaez]: SPAM-based or GAEZ based map
[crop name]:crop name
[farming system]: 'i':irrigation; 'r' rainfed; 'l' low-input rainfed; 'h' high-input rainfed; 's' rainfed in subsistence conditions

Example: gaez_maize_i.csv, the farm-size specific harvested area of irrigated maize based on the crop map of GAEZv4.

Variables included in maps *.csv:
grid: the grid index
shpid: the polygon id in Ricciardi's dataset
spam_crop/gaez_crop: crop name defined in SPAM2010 or GAEZv4 classification system
fs_class_min: lower bound of each farm size class, -1 means no farm size information is available in Ricciardi's dataset
ha: harvested area (ha)
x, y: the lat-lon coordinate in the projection WGS84

Note: please cite the original publications/sources if any data source based on which this dataset was developed is reused for your own study.

SPAM2010: 

Yu, Q., You, L., Wood-Sichra, U., Ru, Y., Joglekar, A. K. B., Fritz, S., Xiong, W., Lu, M., Wu, W., and Yang, P.: A cultivated planet in 2010 – Part 2: The global gridded agricultural-production maps, Earth System Science Data, 12, 3545-3572, 10.5194/essd-12-3545-2020, 2020.

GAEZ v4:

FAO and IIASA: Global Agro Ecological Zones version 4 (GAEZ v4), FAO UN, Rome, Italy, 2021

Ricciardi's dataset:

Ricciardi, V., Ramankutty, N., Mehrabi, Z., Jarvis, L., and Chookolingo, B.: How much of the world's food do smallholders produce?, Global Food Security, 17, 64-72, 2018.

The global dominant field size dataset:

Lesiv, M., Laso Bayas, J. C., See, L., Duerauer, M., Dahlia, D., Durando, N., Hazarika, R., Kumar Sahariah, P., Vakolyuk, M., Blyshchyk, V., Bilous, A., Perez-Hoyos, A., Gengler, S., Prestele, R., Bilous, S., Akhtar, I. U. H., Singha, K., Choudhury, S. B., Chetri, T., Malek, Z., Bungnamei, K., Saikia, A., Sahariah, D., Narzary, W., Danylo, O., Sturn, T., Karner, M., McCallum, I., Schepaschenko, D., Moltchanova, E., Fraisl, D., Moorthy, I., and Fritz, S.: Estimating the global distribution of field size using crowdsourcing, Glob Chang Biol, 25, 174-186, 10.1111/gcb.14492, 2019.

GLC-Share:

Latham, J., Cumani, R., Rosati, I., and Bloise, M.: Global land cover share (GLC-SHARE) database beta-release version 1.0-2014, FAO, Rome, Italy, 2014.

CAAS-IFPRI cropland extent map:

Lu, M., Wu, W., You, L., See, L., Fritz, S., Yu, Q., Wei, Y., Chen, D., Yang, P., and Xue, B.: A cultivated planet in 2010 – Part 1: The global synergy cropland map, Earth System Science Data, 12, 1913-1928, 10.5194/essd-12-1913-2020, 2020.