Estimating global land use change over the past 300 years: the HYDE database
Open accessAbstract
Testing against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate system, these models should aim the simulation of the land use dynamics for long periods, i.e., spanning decades up to a century. Developing such models requires understanding of past and current trends and is therefore strongly data dependent. For this purpose, a history database of the global environment has been developed: HYDE. This paper describes and analyzes parts of HYDE version 2.0, presenting historical population and land use patterns for the past 300 years. Results suggest, among other things, a global increase of cropland area from 265 million ha in 1700 to 1471 million ha in 1990, while the area of pasture has increased more than six fold from 524 to 3451 million ha. In general, the increase of man‐made agricultural land took place at the expense of natural grasslands and to a lesser extent of forests. There are differences between the several regions in the temporal pace of these land use conversions. The temperate/developed regions of Canada, United States, USSR, and Oceania appear to have had their strongest increase during the 19th century, while most of the tropical/developing regions witnessed the largest land use conversions at the end of the last century. Results of this analysis can be used to test integrated models of global change and are available at http://www.rivm.nl/env/int/hyde/.
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The History Database of Global Environment 3.0 (HYDE) has also been used to assess the area of abandoned cropland.
“A second database produced using satellite and census data, the History Database of Global Environment 3.0 (HYDE), has also been used to assess the area of abandoned cropland (Goldewijk, 2001;Goldewijk, Bouwman, & Drecht, 2007).”
From Mapping the world's degraded lands (2015) · cites this paper as Goldewijk, 2001
Recent satellite advances have enabled new global scale datasets of agricultural land cover, which have been developed by merging satellite derived land cover maps with ground level agricultural inventory data sets.
“Recent satellite advances have enabled new global scale datasets of agricultural land cover, which have been developed by merging satellite derived land cover maps with ground level agricultural inventory data sets (Cardille, Foley, & Costa, 2002;Goldewijk, 2001;Ramankutty & Foley, 1999).”
From Mapping the world's degraded lands (2015) · cites this paper as Goldewijk, 2001
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“Steppes, savannas, and grasslands also experienced a rapid decline, from around 3200 million ha in 1700 to 1800–2700 million ha in 1990 (Ramankutty and Foley 1999; Goldewijk et al. 2001).”
Background
- Authors
- Goldewijk, K. K.
- Affiliations
- National Institute for Public Health and the Environment (NL)
- Corresponding author
- Goldewijk, Kees Klein
- Venue
- Global Biogeochemical Cycles
- Publisher
- American Geophysical Union (AGU)
- Published
- 2001-06
- Volume
- 15
- Issue
- 2
- Pages
- 417-433
- ISSN
- 0886-6236 (ISSN-L)
- 1944-9224
- OpenAlex
- W2014634808
- Cited by
- 984
- References
- 35
- Citations by year
- 2026: 10 · 2025: 26 · 2024: 33 · 2023: 34 · 2022: 38 · 2021: 66 · 2020: 44 · 2019: 31 · 2018: 43 · 2017: 52 · 2016: 60 · 2015: 59 · 2014: 47 · 2013: 56 · 2012: 42
- FWCI
- 17.28
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Global Biogeochemical Cycles (publishedVersion)
- Funders
- Rijksinstituut voor Volksgezondheid en Milieu
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
- Physical Sciences › Environmental Science › Global and Planetary Change › Environmental Changes in China
- Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Agriculture, Land Use, Rural Development
- Keywords
- land use history, cropland expansion, pasture expansion, land use conversion, demographic history, natural grassland, forest loss, agricultural land, model validation, historical data
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