HIStory of LAND transformation by humans in South America (HISLAND-SA): annual and 1 km gridded data for soybean, maize, wheat, and rice (1950–2020)
Abstract. South America is a global hotspot for land use and land cover (LULC) change, marked by dramatic agricultural land expansion and deforestation. While previous studies have documented land use and land cover changes in South America over recent decades, there is still a lack of spatially explicit and time-series maps of crop types that capture shifts in crop distribution. Therefore, developing high-resolution, long-term, and crop-specific datasets is crucial for advancing our understanding of human–environment interactions and for assessing the impacts of agricultural activities on carbon and biogeochemical cycles, biodiversity, and climate. In this study, we integrated multi-source data, including high-resolution remote sensing data, model-based data, and historical agricultural census data, to reconstruct the historical dynamics of four major commodity crops (i.e., soybean, maize, wheat, and rice) in South America at an annual timescale and 1 km × 1 km spatial resolution from 1950 to 2020. The results showed that soybean and maize cultivation expanded rapidly in South America by encroaching on other vegetation (i.e., forest, pasture/rangeland, and unmanaged grass/shrubland) over the past 70 years, whereas wheat and rice areas remained relatively stable. Specifically, soybean is one of the most dramatically expanded crops, increasing from essentially zero in 1950 to 48.8 Mha in 2020, resulting in a total loss of 23.92 Mha of other vegetation. In addition, the area of maize increased by a factor of 2.1 from 12.7 Mha in 1950 to 26.9 Mha in 2020. The newly developed crop type dataset provides important insights for assessing the impacts of cropland expansion on crop production, biodiversity, greenhouse gas emissions, and carbon and nitrogen cycles in South America. Moreover, these data are instrumental for developing national policies, sustainable trade, investment, and development strategies aimed at securing food supply and other human and environmental objectives in South America. The datasets are available at https://doi.org/10.5281/zenodo.14002960 (Xu et al., 2024).
Authors
- Óscar Melo (ORCID: https://orcid.org/0000-0002-9136-5413)
- Edson Severnini (ORCID: https://orcid.org/0000-0002-0166-4250)
- Feng Zhao (ORCID: https://orcid.org/0000-0003-4534-933X)
- Katharine Young (ORCID: https://orcid.org/0000-0002-3614-4722)
- Shufen Pan (ORCID: https://orcid.org/0000-0001-7920-1427)
- Marco Picone (ORCID: https://orcid.org/0000-0003-0126-7914)
- Xiao‐Peng Song (ORCID: https://orcid.org/0000-0002-5514-0321)
- A. McDonald
- Ran Meng (ORCID: https://orcid.org/0000-0003-4756-9934)
- Hanqin Tian (ORCID: https://orcid.org/0000-0002-1806-4091)
- Xiaoyong Li (ORCID: https://orcid.org/0000-0003-3107-3483)
- Binyuan Xu
Institutions
- Boston College (US)
- Shandong University of Technology (CN)
- Pontificia Universidad Católica de Chile (CL)
- Huazhong Agricultural University (CN)
- Harbin Institute of Technology (CN)
- Education Department of Heilongjiang Province (CN)
- Sophia University (JP)
- Northeast Forestry University (CN)
- University of Maryland, College Park (US)
Publication Details
- Journal
- Earth system science data
- Published
- 2025-11-24
- DOI
- https://doi.org/10.5194/essd-17-6353-2025
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00