The DOI matches its Crossref record; 66 of the 68 references it cites were found in a registry or an index.
Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000
Open accessAbstract
Agricultural activities have dramatically altered our planet's land surface. To understand the extent and spatial distribution of these changes, we have developed a new global data set of croplands and pastures circa 2000 by combining agricultural inventory data and satellite‐derived land cover data. The agricultural inventory data, with much greater spatial detail than previously available, is used to train a land cover classification data set obtained by merging two different satellite‐derived products (Boston University's MODIS‐derived land cover product and the GLC2000 data set). Our data are presented at 5 min (∼10 km) spatial resolution in longitude by longitude, have greater accuracy than previously available, and for the first time include statistical confidence intervals on the estimates. According to the data, there were 15.0 (90% confidence range of 12.2–17.1) million km 2 of cropland (12% of the Earth's ice‐free land surface) and 28.0 (90% confidence range of 23.6–30.0) million km 2 of pasture (22%) in the year 2000.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The extent of permanent pastures and meadows, the key category for which global statistical data are available (http://faostat.fao.org;any grazing land used for more than five consecutive years), spans 28 (33) to 34 Mkm², including extensively used natural grasslands (Section 2.2), intensively managed pastures and meadows established in natural grassland areas, as well as grassland that was estab”
From Restoring Degraded Lands (2021) · cites this paper as [33]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Global Consequences of Land Use
Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., Chapin, F. S., Coe, M. T., Daily, G. C., Gibbs, H. K., et al. (2005) · Science · doi:10.1126/science.1111772 · Cited by 13,272
Self-citationFreshwater biodiversity: importance, threats, status and conservation challenges
Dudgeon, D., Arthington, A. H., Gessner, M. O., Kawabata, Z., Knowler, D. J., Lévêque, C., Naiman, R. J., Prieur‐Richard, A., Soto, D., Stiassny, M. L. J., et al. (2006) · Biological Reviews · doi:10.1017/s1464793105006950 · Cited by 8,489
Forecasting Agriculturally Driven Global Environmental Change
Tilman, D., Fargione, J., Wolff, B., D'Antonio, C., Dobson, A., Howarth, R., Schindler, D., Schlesinger, W. H., Simberloff, D., & Swackhamer, D. (2001) · Science · doi:10.1126/science.1057544 · Cited by 3,992
Global land cover mapping from MODIS: algorithms and early results
Friedl, M. A., McIver, D. K., Hodges, J. C. F., Xiaoyang Zhang, A., Muchoney, D. M., Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A. B., et al. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00078-0 · Cited by 2,686
Ecosystems and human well-being: current state and trends
Hassan, R., Scholes, R. J., & Ash, N. (2005) · Cited by 2,582
Farming and the Fate of Wild Nature
Green, R. E., Cornell, S. J., Scharlemann, J. P. W., & Balmford, A. (2005) · Science · doi:10.1126/science.1106049 · Cited by 2,238
Estimating historical changes in global land cover: Croplands from 1700 to 1992
Ramankutty, N., & Foley, J. A. (1999) · Global Biogeochemical Cycles · doi:10.1029/1999gb900046 · Cited by 2,074
Self-citationMonfreda, C., Ramankutty, N., & Foley, J. A. (2008) · Global Biogeochemical Cycles · doi:10.1029/2007gb002947 · Cited by 1,895
Self-citationGLC2000: a new approach to global land cover mapping from Earth observation data
claude, B. E. M., & Belward, A. S. (2005) · International Journal of Remote Sensing · doi:10.1080/01431160412331291297 · Cited by 1,799
Modelling the role of agriculture for the 20th century global terrestrial carbon balance
Bondeau, A., Smith, P. L., Zaehle, S., Schaphoff, S., Lucht, W., Crämer, W., Gerten, D., Lotze‐Campen, H., Müller, C., Reichstein, M., et al. (2006) · Global Change Biology · doi:10.1111/j.1365-2486.2006.01305.x · Cited by 1,333
Flagged first, then by citations
2 of the 68 references couldn’t be matched to a known paper.
Research works printed but not linked: 9
- Central Bureau of Statistics, 2001, Statistical Year Book of Nepal 2001
- Crook F., 1993, China International Agriculture and Trade Report, 33
- Forestry Management, Evaluation and Coordinating Unit (FORMECU), 1995, An Assessment of Land Use and Vegetation Changes in Nigeria Between 1978–1993
- 10.1034/j.1600-0889.2003.01450.x · DOI
- Latham J., 2001, AFRICOVER eastern Africa, LUCC Newsl, 7, 15
- Lopez‐Meisel D., 1996, 1991 Census of Agriculture of the Philippines
- 10.1175/1520-0442-16.10.1511 · DOI
- National Statistical Office of Mongolia, 2004, Mongolia in a Market System Statistical Yearbook: 1989–2002
- State Committee of the Russian Federation on Statistics, 1995, Sel'skoe khoziaistvo Rossii: Statisticheskii sbornik
Cited by
Sorted by citations
Items 501–600 of 1,002
Multimodel assessment of water budget in Indian sub-continental river basins
Kushwaha, A., Tiwari, A., Dangar, S., Shah, H. L., Mahto, S., & Mishra, V. (2021) · Journal of Hydrology · doi:10.1016/j.jhydrol.2021.126977 · Cited by 65
Miller, S. M., Kort, E. A., Hirsch, A. I., Dlugokencky, E. J., Andrews, A. E., Xu, X., Tian, H., Nehrkorn, T., Eluszkiewicz, J., Michalak, A. M., et al. (2012) · Journal of Geophysical Research Atmospheres · doi:10.1029/2011jd016951 · Cited by 71
Data and monitoring needs for a more ecological agriculture
Zaks, D. P. M., & Kucharik, C. J. (2011) · Environmental Research Letters · doi:10.1088/1748-9326/6/1/014017 · Cited by 71
Zaks, D. P. M., Barford, C. C., Ramankutty, N., & Foley, J. A. (2009) · Environmental Research Letters · doi:10.1088/1748-9326/4/4/044010 · Cited by 71
Self-citationAmazonian forest-savanna bistability and human impact
Wuyts, B., CHAMPNEYS, A. R., & House, J. I. (2017) · Nature Communications · doi:10.1038/ncomms15519 · Cited by 78
Sun, Z., Scherer, L., Zhang, Q., & Behrens, P. (2022) · Nature Food · doi:10.1038/s43016-022-00634-4 · Cited by 70
Ecosystem services and land sparing potential of urban and peri-urban agriculture: A review
Wilhelm, J. A., & Smith, R. G. (2017) · Renewable Agriculture and Food Systems · doi:10.1017/s1742170517000205 · Cited by 73
“Agricultural systems, including crop and pastureland, currently cover approximately 40% of terrestrial land area (Ramankutty et al., 2008).”
BackgroundGlobal bioenergy capacity as constrained by observed biospheric productivity rates
Smith, W. K., Zhao, M., & Running, S. W. (2012) · BioScience · doi:10.1525/bio.2012.62.10.11 · Cited by 70
Capolupo, A., Monterisi, C., & Tarantino, E. (2020) · Remote Sensing · doi:10.3390/rs12071201 · Cited by 69
“Recent research activities have shown that, due to their coarse resolution, most of the listed datasets are not reliable over urban and agricultural areas since they show substantial disagreement with each other and with national statistics [1,10,11].”
BackgroundXie, H., Longuevergne, L., Ringler, C., & Scanlon, B. R. (2012) · Hydrology and earth system sciences · doi:10.5194/hess-16-3083-2012 · Cited by 69
Venkatramanan, V., & Shah, S. (2019) · Springer eBooks · doi:10.1007/978-981-13-2772-8_2 · Cited by 72
Tipping point dynamics in global land use
Taylor, C. A., & Rising, J. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/ac3c6d · Cited by 76
Effect of spatial heterogeneity on the validation of remote sensing based GPP estimations
Gelybó, G., Barcza, Z., Kern, A., & Kljun, N. (2013) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2013.02.003 · Cited by 70
Quantifying yield gaps in wheat production in Russia
Schierhorn, F., Faramarzi, M., Prishchepov, A. V., Koch, F. J., & Müller, D. (2014) · Environmental Research Letters · doi:10.1088/1748-9326/9/8/084017 · Cited by 71
Crop-specific seasonal estimates of irrigation water demand in South Asia
Biemans, H., Siderius, C., Mishra, A., & Ahmad, B. (2016) · Hydrology and earth system sciences · doi:10.5194/hess-20-1971-2016 · Cited by 63
Does global meat consumption follow an environmental Kuznets curve?
Cole, J. R., & McCoskey, S. K. (2013) · Sustainability Science Practice and Policy · doi:10.1080/15487733.2013.11908112 · Cited by 69
Goldman, E. D., Weisse, M., Harris, N. L., & Schneider, M. (2020) · doi:10.46830/writn.na.00001 · Cited by 67
“Pasture EarthStat (Ramankutty et al. 2008) 10 kilometer 2000 Global”
MethodInfluentialDefining healthy and sustainable diets for infants, children and adolescents
Hollis, J., Collins, C. E., DeClerck, F., Chai, L. K., McColl, K., & Demaio, S. (2020) · Global Food Security · doi:10.1016/j.gfs.2020.100401 · Cited by 81
Seasonal climate forecast can inform the European agricultural sector well in advance of harvesting
Ceglar, A., & Toreti, A. (2021) · npj Climate and Atmospheric Science · doi:10.1038/s41612-021-00198-3 · Cited by 72
How Reliable is the MODIS Land Cover Product for Crop Mapping Sub-Saharan Agricultural Landscapes?
Leroux, L., Jolivot, A., Bégué, A., Seen, D. L., & Zoungrana, B. (2014) · Remote Sensing · doi:10.3390/rs6098541 · Cited by 67
Environmental and Human Controls of Ecosystem Functional Diversity in Temperate South America
Alcaraz‐Segura, D., Paruelo, J. M., Epstein, H. E., & Cabello, J. (2013) · Remote Sensing · doi:10.3390/rs5010127 · Cited by 67
Rishmawi, K., Prince, S. D., & Xue, Y. (2016) · Remote Sensing · doi:10.3390/rs8110910 · Cited by 68
Global Hotspots of Conflict Risk between Food Security and Biodiversity Conservation
Molotoks, A., Kuhnert, M., Dawson, T. P., & Smith, P. (2017) · Land · doi:10.3390/land6040067 · Cited by 67
“This was overlaid with a global cropland database [22] to exclude areas which are already cultivated, and the resulting index was used as an indicator of potential threat of agricultural expansion in the future.”
MethodCalibration of a Land Cover Supply Function Using Transition Probabilities
Ahmed, S. A., Hertel, T. W., & Lubowski, R. N. (2009) · GTAP research memoranda series · doi:10.21642/gtap.rm14 · Cited by 67
Jaafar, H. H., & Ahmad, F. A. (2015) · International Journal of Remote Sensing · doi:10.1080/01431161.2015.1084434 · Cited by 75
Bowen, M. E., McAlpine, C., Seabrook, L., House, A. P. N., & Smith, G. C. (2009) · Biological Conservation · doi:10.1016/j.biocon.2009.08.005 · Cited by 65
Impacts of Climate Change and the End of Deforestation on Land Use in the Brazilian Legal Amazon
Lapola, D. M., Schaldach, R., Alcamo, J., Bondeau, A., Msangi, S., Priess, J. A., Silvestrini, R. A., & Soares-Filho, B. S. (2010) · Earth Interactions · doi:10.1175/2010ei333.1 · Cited by 67
White, E., & Roy, D. P. (2015) · Geo Geography and Environment · doi:10.1002/geo2.4 · Cited by 65
Yu, Q., Wu, W.-B., Yang, P., Li, Z.-G., Xiong, W., & Tang, H. (2012) · Agriculture Ecosystems & Environment · doi:10.1016/j.agee.2012.04.026 · Cited by 59
Green growth: From intention to implementation
Jouvet, P., & de Perthuis, C. (2013) · International Economics · doi:10.1016/j.inteco.2013.05.003 · Cited by 68
Historical trade-offs of livestock’s environmental impacts
Davis, K. F., Yu, K., Herrero, M., Havlík, P., Carr, J. A., & D’Odorico, P. (2015) · Environmental Research Letters · doi:10.1088/1748-9326/10/12/125013 · Cited by 65
Perspectives for environmental conservation and ecosystem services on coupled rural–urban systems
Silva, R., Rodrigues, M. D. A., Vieira, S. A., Batistella, M., & Farinaci, J. S. (2017) · Perspectives in Ecology and Conservation · doi:10.1016/j.pecon.2017.05.005 · Cited by 64
Modelled biophysical impacts of conservation agriculture on local climates
Hirsch, A. L., Prestele, R., Davin, É. L., Seneviratne, S. I., Thiery, W., & Verburg, P. H. (2018) · Global Change Biology · doi:10.1111/gcb.14362 · Cited by 66
Wang, Y., Fu, X., Wang, T., Ma, J., Gao, H. J., Wang, X., & Pu, W. (2023) · Environmental Science & Technology · doi:10.1021/acs.est.2c07793 · Cited by 65
Teluguntla, P., Thenkabail, P., Xiong, J., Gumma, M., Congalton, R., Oliphant, A., Poehnelt, J., Yadav, K., Rao, M., & Massey, R. (2017) · International Journal of Digital Earth · doi:10.1080/17538947.2016.1267269 · Cited by 67
Integrating cloud-based workflows in continental-scale cropland extent classification
Massey, R., Sankey, T. T., Yadav, K., Congalton, R. G., & Tilton, J. C. (2018) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.10.013 · Cited by 65
Development and evaluation of the aerosol dynamics and gas phase chemistry model ADCHEM
Roldin, P., Swietlicki, E., Schurgers, G., Arneth, A., Lehtinen, K. E. J., Boy, M. H., & Kulmala, M. (2011) · Atmospheric chemistry and physics · doi:10.5194/acp-11-5867-2011 · Cited by 63
Coefficient of variation for use in crop area classification across multiple climates
Whelen, T., & Siqueira, P. (2018) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2017.12.014 · Cited by 63
Paying the price for the meat we eat
Allen, A. M., & Hof, A. R. (2019) · Environmental Science & Policy · doi:10.1016/j.envsci.2019.04.010 · Cited by 69
“…we focus on the livestock industry given its contribution to climate change (Gerber et al., 2013) and domination of land-use practices of our planet (Ramankutty et al., 2008), both of which have severe consequences for https://doi.org/10.1016/j.envsci.2019.04.010 Received 19 February 2019;…”
BackgroundInfluentialDias, T. A. D. C., Lora, E. E. S., Maya, D. M. Y., & del Olmo, O. A. A. (2021) · Land Use Policy · doi:10.1016/j.landusepol.2021.105346 · Cited by 63
Priority areas for investment in more sustainable and climate-resilient livestock systems
Bonilla, C., Steward, P., Rosenstock, T. S., Thornton, P. K., Arango, J., Kropff, M. J., & Ramírez-Villegas, J. (2023) · Nature Sustainability · doi:10.1038/s41893-023-01161-1 · Cited by 76
“Exposure was represented by the total VOP 42 , total rural population 43 , pasture area 44 and TLUs.”
Mapping Irrigated Areas in China From Remote Sensing and Statistical Data
Zhu, X., Zhu, W., Zhang, J., & Pan, Y. (2014) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2013.2296899 · Cited by 63
Rosas, M. A., & Gutiérrez, R. R. (2019) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2019.135474 · Cited by 63
Ecosystem Services of Mangroves: An Overview
Mitra, A. (2019) · Springer eBooks · doi:10.1007/978-3-030-20595-9_1 · Cited by 62
Multivariate random forest prediction of poverty and malnutrition prevalence
Browne, C., Matteson, D. S., McBride, L., Hu, L., Liu, Y., Sun, Y., Wen, J., & Barrett, C. B. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255519 · Cited by 69
“• Pasture coverage data present at 5 minute (�10 km) spatial resolution drawn from Ramankutty et al’s [29] data series on agricultural lands in 2000;”
MethodChallenges of Pasture Feeding Systems—Opportunities and Constraints
Wróbel, B., Zielewicz, W., & Staniak, M. (2023) · Agriculture · doi:10.3390/agriculture13050974 · Cited by 77
Anthropogenic effects on global mean fire size
Hantson, S., Lasslop, G., Kloster, S., & Chuvieco, E. (2015) · International Journal of Wildland Fire · doi:10.1071/wf14208 · Cited by 62
Representation of Ecosystem Services by Terrestrial Protected Areas: Chile as a Case Study
Durán, A. P., Casalegno, S., Marquet, P. A., & Gaston, K. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0082643 · Cited by 61
Reimagining the potential of Earth observations for ecosystem service assessments
Ramirez‐Reyes, C., Brauman, K. A., Chaplin‐Kramer, R., Galford, G. L., Adamo, S. B., Anderson, C. B., Anderson, C. R., Allington, G. R. H., Bagstad, K. J., Coe, M. T., et al. (2019) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2019.02.150 · Cited by 64
Kugler, T. A., Grace, K. L., Wrathall, D. J., de Sherbinin, A., Riper, D. C. V., Aubrecht, C., Comer, D. C., Adamo, S. B., Cervone, G., Engstrom, R. N., et al. (2019) · Population and Environment · doi:10.1007/s11111-019-00326-5 · Cited by 64
Sigler, W. A., Ewing, S. A., Jones, C. A., Payn, R. A., Miller, P. R., & Maneta, M. (2020) · Agriculture Ecosystems & Environment · doi:10.1016/j.agee.2020.107158 · Cited by 61
“Fifteen million square kilometers of the earth ’ s surface is cultivated (Ramankutty et al., 2008).”
Loss of green landscapes due to urban expansion in China
He, Y., Liang, Y., Liu, L., Yin, Z., & Huang, J. (2023) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2023.107228 · Cited by 64
An analysis of methodological and spatial differences in global cropping systems models and maps
Anderson, W., You, L., Wood, S., Wood‐Sichra, U., & Wu, W. (2014) · Global Ecology and Biogeography · doi:10.1111/geb.12243 · Cited by 61
Sus, O., Williams, M., Bernhofer, C., Béziat, P., Buchmann, N., Ceschia, É., Doherty, R. M., Werner Eugster, A., Grünwald, T., Kutsch, W. L., et al. (2010) · Agriculture Ecosystems & Environment · doi:10.1016/j.agee.2010.06.012 · Cited by 61
Capital Obsolescence and Agricultural Productivity*
Caunedo, J., & Keller, E. (2020) · The Quarterly Journal of Economics · doi:10.1093/qje/qjaa028 · Cited by 60
“We use the EarthStat dataset constructed by Ramankutty et al. (2008), which consists of agricultural census and survey 12Detailed comparisons to Census data can be found in the online appendix. information on crop land areas and yields for 175 crops measured at the smallest political units…”
MethodPlant disease risk is modified by multiple global change drivers
Laine, A. (2023) · Current Biology · doi:10.1016/j.cub.2023.03.075 · Cited by 60
Net anthropogenic nitrogen inputs and nitrogen fluxes from Indian watersheds: An initial assessment
Swaney, D. P., Hong, B., Selvam, A. P., Howarth, R. W., Ramesh, R., & Purvaja, R. (2014) · Journal of Marine Systems · doi:10.1016/j.jmarsys.2014.09.004 · Cited by 60
Nimmo, D. G., Haslem, A., Radford, J. Q., Hall, M., & Bennett, A. F. (2015) · Journal of Applied Ecology · doi:10.1111/1365-2664.12535 · Cited by 60
Ecology and Conservation of Steppes and Semi-Natural Grasslands
Valkó, O., Żmihorski, M., Biurrun, I., Loos, J., Labadessa, R., & Venn, S. (2016) · Hacquetia · doi:10.1515/hacq-2016-0021 · Cited by 60
Hummel, M., Hoose, C., Gallagher, M., Healy, D. A., Huffman, J. A., O'Connor, D., Pöschl, U., Pöhlker, C., Robinson, N. H., Schnaiter, M., et al. (2015) · Atmospheric Chemistry and Physics · doi:10.5194/acp-15-6127-2015 · Cited by 59
Closing yield gap is crucial to avoid potential surge in global carbon emissions
Suh, S., Johnson, J. A., Tambjerg, L., Sim, S., Broeckx-Smith, S., Reyes, W., & Chaplin‐Kramer, R. (2020) · Global Environmental Change · doi:10.1016/j.gloenvcha.2020.102100 · Cited by 61
A review of global gridded cropping system data products
Kim, K., Doi, Y., Ramankutty, N., & Iizumi, T. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/ac20f4 · Cited by 62
Self-citationGlobal soil organic carbon changes and economic revenues with biochar application
Han, M., Zhao, Q. X., Li, W., Ciais, P., Wang, Y., Goll, D. S., Zhu, L., Zhao, Z. S., Wang, J., Wei, Y., et al. (2021) · GCB Bioenergy · doi:10.1111/gcbb.12915 · Cited by 58
“Cropland distribution at 1 km × 1 km was derived from global land cover map database (GLCM) (Ramankutty et al., 2008).”
Churkina, G., Zaehle, S., Hughes, J., Viovy, N., Chen, Y., Jung, M., Heumann, B. W., Ramankutty, N., Rödenbeck, C., Heimann, M., et al. (2010) · Biogeosciences · doi:10.5194/bg-7-2749-2010 · Cited by 62
Self-citationIdentifying representative crop rotation patterns and grassland loss in the US Western Corn Belt
Sahajpal, R., Zhang, X., Izaurralde, R. C., Gelfand, I., & HURTT, G. C. (2014) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2014.08.005 · Cited by 67
Progressive Midlatitude Afforestation: Impacts on Clouds, Global Energy Transport, and Precipitation
Laguë, M. M., & Swann, A. L. S. (2016) · Journal of Climate · doi:10.1175/jcli-d-15-0748.1 · Cited by 61
“5 is determined from a combination of MODIS land cover data (Friedl et al. 2002) and global crop area data from Unauthenticated | Downloaded 05/12/22 07:42 AM UTC the year 2000 (Ramankutty et al. 2008).”
BackgroundBradford, J. B., Schlaepfer, D. R., Lauenroth, W. K., Yackulic, C. B., Duniway, M. C., Hall, S. A., Jia, G., Jamiyansharav, K., Munson, S. M., Wilson, S. D., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-13165-x · Cited by 59
Distinct Influences of Land Cover and Land Management on Seasonal Climate
Singh, D., McDermid, S., Cook, B., Puma, M., Nazarenko, L., & Kelley, M. (2018) · Journal of Geophysical Research - Atmospheres · doi:10.1029/2018jd028874 · Cited by 34
“Agricultural activities including cropland expansion and intensification have considerably altered over 40% of the Earth’s ice-free surface and have been a major source of global environmental change in the twentieth century (Defries et al., 2004; Green et al., 2005; Matson et al., 1997; Ramankutty et al., 2008; Sacks…”
BackgroundPorwollik, V., Rolinski, S., Heinke, J., von Bloh, W., Schaphoff, S., & Müller, C. (2022) · Biogeosciences · doi:10.5194/bg-19-957-2022 · Cited by 58
Critical Role of Irrigation Efficiency for Cropland Expansion in Western China Arid Agroecosystems
Fu, J., Wang, W., Zaitchik, B. F., Nie, W., Fei, E. X., Miller, S. M., & Harman, C. J. (2022) · Earth s Future · doi:10.1029/2022ef002955 · Cited by 58
Parker, N. E., & Williams, J. W. (2011) · The Holocene · doi:10.1177/0959683611425550 · Cited by 58
Mueller, N. D., Rhines, A. N., Butler, E. E., Ray, D. K., Siebert, S., Holbrook, N. M., & Huybers, P. (2017) · Journal of Climate · doi:10.1175/jcli-d-17-0096.1 · Cited by 62
“…these boundaries are then classified as a “major cropping area” if they134 8 contain greater than 50% cropland according to a circa 2000 dataset (Ramankutty et al. 2008) and135 exhibit positive trends in our summer cropping intensity index, defined below.136 b. Cropland area…”
BackgroundProgress and perspectives on agricultural remote sensing research and applications in China
Chen, Z., Ren, J., Tang, H., Shi, Y., Leng, P., Liu, J., Wang, L., Wu, W., Yao, Y., & Hasiyuya (2016) · National Remote Sensing Bulletin · doi:10.11834/jrs.20166214 · Cited by 58
Water Scarcity and Challenges for Smallholder Agriculture
Giordano, M., Barron, J., & Unver, O. I. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-812134-4.00005-4 · Cited by 57
The empirical analysis of climate change impacts and adaptation in agriculture
Ortiz‐Bobea, A. (2021) · Handbook of agricultural economics · doi:10.1016/bs.hesagr.2021.10.002 · Cited by 68
“For global studies one can rely on global datasets describing the global distribution of agricultural lands (e.g. Ramankutty et al., 2008).”
BackgroundCrop domestication and the disruption of species interactions
Macfadyen, S., & Bohan, D. A. (2010) · Basic and Applied Ecology · doi:10.1016/j.baae.2009.11.008 · Cited by 58
Dotta, G., Phalan, B., da Silva, T. W., Green, R., & Balmford, A. P. (2015) · Conservation Biology · doi:10.1111/cobi.12635 · Cited by 57
The water footprint of staple crop trade under climate and policy scenarios
Konar, M., Reimer, J. J., Hussein, Z., & Hanasaki, N. (2016) · Environmental Research Letters · doi:10.1088/1748-9326/11/3/035006 · Cited by 59
Trade‐offs in water and carbon ecosystem services with land‐use changes in grasslands
Kim, J. H., Jobbagy, E. G., & Jackson, R. B. (2016) · Ecological Applications · doi:10.1890/15-0863.1 · Cited by 58
Rapid corn and soybean mapping in US Corn Belt and neighboring areas
Zhong, L., Yu, L., Li, X.-C., Hu, L.-N., & Gong, P.-Y. (2016) · Scientific Reports · doi:10.1038/srep36240 · Cited by 56
Montes, C. M., Demler, H. J., Li, S., Martin, D. G., & Ainsworth, E. A. (2021) · The Plant Journal · doi:10.1111/tpj.15501 · Cited by 56
Agricultural risk assessment of compound dry and hot events in China
Zhang, Y., Hao, Z., & Zhang, Y. (2022) · Agricultural Water Management · doi:10.1016/j.agwat.2022.108128 · Cited by 56
Effect of ozone stress on crop productivity: A threat to food security
Ramya, A., Dhevagi, P., Poornima, R., Avudainayagam, S., Watanabe, M., & Agathokleous, E. (2023) · Environmental Research · doi:10.1016/j.envres.2023.116816 · Cited by 61
Chen, T., van der Werf, G. R., Dolman, A. J., & Groenendijk, M. (2011) · Geophysical Research Letters · doi:10.1029/2011gl047533 · Cited by 56
Nesme, T., Senthilkumar, K., Mollier, A., & Pellerin, S. (2015) · European Journal of Agronomy · doi:10.1016/j.eja.2015.08.001 · Cited by 56
Alcamo, J., Schaldach, R., Koch, J., Kölking, C., Lapola, D. M., & Priess, J. A. (2011) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2011.03.002 · Cited by 57
Humans on Earth: Global extents of anthropogenic land cover from remote sensing
Small, C., & Sousa, D. (2016) · Anthropocene · doi:10.1016/j.ancene.2016.04.003 · Cited by 56
Heterogeneous returns to chemical fertilizer at the intensive margins: Insights from Nepal
Takeshima, H., Adhikari, R., Shivakoti, S., Kaphle, B. D., & Kumar, A. (2017) · Food Policy · doi:10.1016/j.foodpol.2017.03.007 · Cited by 56
Carbon Sequestration in Grassland Soils
Lorenz, K. E., & Lal, R. (2018) · Springer eBooks · doi:10.1007/978-3-319-92318-5_4 · Cited by 59
Sensitivity of Global Pasturelands to Climate Variation
Stanimirova, R., Arévalo, P., Kaufmann, R. K., MAUS, V. W., Lesiv, M., Havlík, P., & Friedl, M. A. (2019) · Earth s Future · doi:10.1029/2019ef001316 · Cited by 62
Ganjurjav, H., Zhang, Y., Gornish, E. S., Hu, G., Li, Y., Wan, Y., & Gao, Q. (2019) · Journal of Environmental Management · doi:10.1016/j.jenvman.2019.109579 · Cited by 56
A scoping review of research funding for small-scale farmers in water scarce regions
Ricciardi, V., Wane, A., Sidhu, B. S., Godde, C., Solomon, D. S., McCullough, E., Diekmann, F., Porciello, J., Jain, M., Randall, N., et al. (2020) · Nature Sustainability · doi:10.1038/s41893-020-00623-0 · Cited by 58
Understanding the distribution of cattle production systems in the South American Chaco
Fernández, P. D., Kuemmerle, T., Baumann, M., Grau, H. R., Nasca, J., Radrizzani, A., & Gasparri, I. (2020) · Journal of Land Use Science · doi:10.1080/1747423x.2020.1720843 · Cited by 55
Temperature variability and long-run economic development
Linsenmeier, M. (2023) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2023.102840 · Cited by 59
Global loss of climatically suitable areas for durum wheat growth in the future
Ceglar, A., Toreti, A., Zampieri, M., & Royo, C. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/ac2d68 · Cited by 59
Mapping and analysing cropland use intensity from a NPP perspective
Niedertscheider, M., Kästner, T., Fetzel, T., Haberl, H., Kroisleitner, C., Plutzar, C., & Erb, K. (2016) · Environmental Research Letters · doi:10.1088/1748-9326/11/1/014008 · Cited by 58
Premke, K., Attermeyer, K., Augustin, J., Cabezas, Á., Casper, P., Deumlich, D., Gelbrecht, J., Gerke, H. H., Geßler, A., Grossart, H., et al. (2016) · Wiley Interdisciplinary Reviews Water · doi:10.1002/wat2.1147 · Cited by 64
Peak growing season gross uptake of carbon in North America is largest in the Midwest USA
Hilton, T. W., Whelan, M., Zumkehr, A., Kulkarni, S., Berry, J. A., Baker, I., Montzka, S. A., Sweeney, C., Miller, B. R., & Campbell, J. E. (2017) · Nature Climate Change · doi:10.1038/nclimate3272 · Cited by 55
Grazing alters net ecosystem C fluxes and the global warming potential of a subtropical pasture
Gomez‐Casanovas, N., DeLucia, N. J., Bernacchi, C. J., Boughton, E. H., Sparks, J. P., Chamberlain, S. D., & DeLucia, E. H. (2017) · Ecological Applications · doi:10.1002/eap.1670 · Cited by 54
Toward Climate-Resilient Development in Nigeria
Cervigni, R., Valentini, R., & Santini, M. (2013) · World Bank, Washington, DC eBooks · doi:10.1596/978-0-8213-9923-1 · Cited by 54
Metadata
- Authors
- Ramankutty, N., Evan, A. T., Monfreda, C., & Foley, J. A.
- Affiliations
- McGill University (CA)
- University of Wisconsin–Madison (US)
- Venue
- Global Biogeochemical Cycles
- Publisher
- American Geophysical Union (AGU)
- Published
- 2008-01-17
- Volume
- 22
- Issue
- 1
- ISSN
- 0886-6236 (ISSN-L)
- 1944-9224
- OpenAlex
- W1838764073
- Cited by
- 1,942
- References
- 68
- Citations by year
- 2026: 55 · 2025: 79 · 2024: 142 · 2023: 123 · 2022: 119 · 2021: 173 · 2020: 149 · 2019: 141 · 2018: 142 · 2017: 119 · 2016: 145 · 2015: 86 · 2014: 104 · 2013: 87 · 2012: 88
- FWCI
- 55.51
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Global Biogeochemical Cycles (publishedVersion)
- Funders
- National Aeronautics and Space Administration
- Wageningen University and Research
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Social Sciences › Development › Agriculture, Land Use, Rural Development
- Keywords
- cropland extent, land cover classification, MODIS land cover, GLC2000, land surface change, confidence intervals
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
