{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T12:51:56Z","timestamp":1768740716719,"version":"3.49.0"},"reference-count":60,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,14]],"date-time":"2018-04-14T00:00:00Z","timestamp":1523664000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000936","name":"Gordon and Betty Moore Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000936","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014596","name":"The Nature Conservancy","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014596","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005285","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Goi\u00e1s","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005285","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The pasturelands areas of Brazil constitute an important asset for the country, as the main food source for the world\u2019s largest commercial herd, representing the largest stock of open land in the country, occupying ~21% of the national territory. Understanding the spatio-temporal dynamics of these areas is of fundamental importance for the goal of promoting improved territorial governance, emission mitigation and productivity gains. To this effect, this study mapped, through objective criteria and automatic classification methods (Random Forest) applied to MODIS (Moderate Resolution Imaging Spectroradiometer) images, the totality of the Brazilian pastures between 2000 and 2016. Based on 90 spectro-temporal metrics derived from the Red, NIR and SWIR1 bands and distinct vegetation indices, distributed between dry and wet seasons, a total of 17 pasture maps with an approximate overall accuracy of 80% were produced with cloud-computing (Google Earth Engine). During this period, the pasture area varied from ~152 (2000) to ~179 (2016) million hectares. This expansion pattern was consistent with the bovine herd variation and mostly occurred in the Amazon, which increased its total pasture area by ~15 million hectares between 2000 and 2005, while the Cerrado, Caatinga and Pantanal biomes showed an increase of ~8 million hectares in this same period. The Atlantic Forest was the only biome in which there was a retraction of pasture areas throughout this series. In general, the results of this study suggest the existence of two relevant moments for the Brazilian pasture land uses. The first, strongly supported by the opening of new grazing areas, prevailed between 2000 and 2005 and mostly occurred in the Deforestation Arc and in the Matopiba regions. From 2006 on, the total pasture area in Brazil showed a trend towards stabilization, indicating a slight intensification of livestock activity in recent years.<\/jats:p>","DOI":"10.3390\/rs10040606","type":"journal-article","created":{"date-parts":[[2018,4,16]],"date-time":"2018-04-16T03:12:09Z","timestamp":1523848329000},"page":"606","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["Assessing the Spatial and Occupation Dynamics of the Brazilian Pasturelands Based on the Automated Classification of MODIS Images from 2000 to 2016"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1589-0467","authenticated-orcid":false,"given":"Leandro","family":"Parente","sequence":"first","affiliation":[{"name":"Image Processing and GIS Laboratory (LAPIG), Federal University of Goi\u00e1s (UFG), Goi\u00e2nia GO 74001-970, Brazil"}]},{"given":"Laerte","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Image Processing and GIS Laboratory (LAPIG), Federal University of Goi\u00e1s (UFG), Goi\u00e2nia GO 74001-970, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1126\/science.1185383","article-title":"Food security: The challenge of feeding 9 billion people","volume":"327","author":"Godfray","year":"2010","journal-title":"Science"},{"key":"ref_2","unstructured":"(2018, January 15). CNA Brasil Pode Se Tornar o Maior Produtor de Carne Bovina do Mundo. Available online: http:\/\/www.cnabrasil.org.br\/noticias\/brasil-pode-se-tornar-o-maior-produtor-de-carne-bovina-do-mundo."},{"key":"ref_3","unstructured":"Westcott, P., and Contact, E. (2016). USDA Agricultural Projections to 2025 Interagency Agricultural Projections Committee, USDA Long-term Projections."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e1601047","DOI":"10.1126\/sciadv.1601047","article-title":"Types and rates of forest disturbance in Brazilian Legal Amazon, 2000\u20132013","volume":"3","author":"Tyukavina","year":"2017","journal-title":"Sci. Adv."},{"key":"ref_5","first-page":"341","article-title":"Detec\u00e7\u00e3o de desmatamentos no bioma cerrado entre 2002 e 2009: Padr\u00f5es, tend\u00eancias e impactos","volume":"63","author":"Rocha","year":"2011","journal-title":"Rev. Bras. Cartogr."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1073\/pnas.1111374109","article-title":"Decoupling of deforestation and soy production in the southern Amazon during the late 2000s","volume":"109","author":"Macedo","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1804","DOI":"10.1111\/gcb.12174","article-title":"Agricultural intensification in Brazil and its effects on land-use patterns: An analysis of the 1975\u20132006 period","volume":"19","author":"Barretto","year":"2013","journal-title":"Glob. Chang. Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2887","DOI":"10.1111\/gcb.13314","article-title":"Patterns of land use, extensification, and intensification of Brazilian agriculture","volume":"22","author":"Dias","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1080\/15481603.2014.909108","article-title":"Analysis of agricultural intensification in a basin with remote sensing data","volume":"51","author":"Trabaquini","year":"2014","journal-title":"GIScience Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1007\/s10584-012-0443-3","article-title":"Estimating greenhouse gas emissions from cattle raising in Brazil","volume":"115","author":"Bustamante","year":"2012","journal-title":"Clim. Chang."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.jclepro.2013.05.026","article-title":"Greenhouse gas assessment of soybean production: Implications of land use change and different cultivation systems","volume":"54","author":"Castanheira","year":"2013","journal-title":"J. Clean. Prod."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1038\/nclimate2925","article-title":"Greenhouse gas mitigation potentials in the livestock sector","volume":"6","author":"Herrero","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Parente, L., Ferreira, L., Faria, A., Nogueira, S., Ara\u00fajo, F., Teixeira, L., and Hagen, S. (2017). Monitoring the brazilian pasturelands: A new mapping approach based on the landsat 8 spectral and temporal domains. Int. J. Appl. Earth Obs. Geoinform.","DOI":"10.1016\/j.jag.2017.06.003"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1016\/j.gloenvcha.2013.05.005","article-title":"Estimating the world\u2019s potentially available cropland using a bottom-up approach","volume":"23","author":"Lambin","year":"2013","journal-title":"Glob. Environ. Chang."},{"key":"ref_15","unstructured":"(2018, February 10). IBGE Pesquisa Pecu\u00e1ria Municipal, Available online: https:\/\/sidra.ibge.gov.br\/pesquisa\/ppm\/quadros\/brasil\/2016."},{"key":"ref_16","unstructured":"MMA (2002). Projeto de Conserva\u00e7\u00e3o e Utiliza\u00e7\u00e3o Sustent\u00e1vel da Diversidade Biol\u00f3gica Brasileira: Relat\u00f3rio de Atividades."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1038\/nclimate2056","article-title":"Pervasive transition of the Brazilian land-use system","volume":"4","author":"Lapola","year":"2014","journal-title":"Nat. Clim. Chang."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1126\/science.aad0055","article-title":"CONSERVATION ECOLOGY. How can higher-yield farming help to spare nature?","volume":"351","author":"Phalan","year":"2016","journal-title":"Science"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1109\/36.701075","article-title":"The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research","volume":"36","author":"Justice","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/S0034-4257(02)00078-0","article-title":"Global land cover mapping from MODIS: Algorithms and early results","volume":"83","author":"Friedl","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_21","first-page":"1","article-title":"A Time-Weighted Dynamic Time Warping method for land use and land cover mapping","volume":"20","author":"Maus","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/S0034-4257(02)00082-2","article-title":"Towards operational monitoring of terrestrial systems by moderate-resolution remote sensing","volume":"83","author":"Townshend","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.isprsjprs.2017.09.002","article-title":"Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States","volume":"132","author":"Peng","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","unstructured":"Didan, K., Munoz, A.B., Solano, R., and Huete, A. (2015). MODIS Vegetation Index User\u2019s Guide (MOD13 Series), Vegetation Index and Phenology Lab, The University of Arizona."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3833","DOI":"10.1016\/j.rse.2008.06.006","article-title":"Development of a two-band enhanced vegetation index without a blue band","volume":"112","author":"Jiang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/S0034-4257(01)00190-0","article-title":"AFRI\u2014Aerosol free vegetation index","volume":"77","author":"Karnieli","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1080\/01431161.2012.712223","article-title":"Biophysical characteristics and fire occurrence of cultivated pastures in the Brazilian savanna observed by moderate resolution satellite data","volume":"34","author":"Ferreira","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"307","DOI":"10.3390\/rs5010307","article-title":"Biophysical Properties of Cultivated Pastures in the Brazilian Savanna Biome: An Analysis in the Spatial-Temporal Domains Based on Ground and Satellite Data","volume":"5","author":"Ferreira","year":"2013","journal-title":"Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Aguiar, D., Mello, M., Nogueira, S., Gon\u00e7alves, F., Adami, M., and Rudorff, B. (2017). MODIS Time Series to Detect Anthropogenic Interventions and Degradation Processes in Tropical Pasture. Remote Sens., 9.","DOI":"10.3390\/rs9010073"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_34","unstructured":"IBGE (2016). Base Cartogr\u00e1fica Cont\u00ednua do Brasil, ao Milion\u00e9simo\u2014BCIM."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Jiang, Y., Sun, M., and Yang, C. (2016). A Generic Framework for Using Multi-Dimensional Earth Observation Data in GIS. Remote Sens., 8.","DOI":"10.3390\/rs8050382"},{"key":"ref_37","unstructured":"Lohr, S. (2000). Sampling: Design and Analysis. J. Chem. Inf. Model., 596."},{"key":"ref_38","unstructured":"Nogueira, S., Parente, L., and Ferreira, L. (2017). Temporal Visual Inspection: Uma ferramenta destinada \u00e0 inspe\u00e7\u00e3o visual de pontos em s\u00e9ries hist\u00f3ricas de imagens de sensoriamento remoto, XXVII Congresso Brasileiro de Cartografia."},{"key":"ref_39","unstructured":"IBGE (2006). Censo Agropecu\u00e1rio."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"25004","DOI":"10.1088\/1748-9326\/aa5986","article-title":"Forest carbon emissions from cropland expansion in the Brazilian Cerrado biome","volume":"12","author":"Noojipady","year":"2017","journal-title":"Environ. Res. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1093\/aepp\/ppr011","article-title":"Agricultural Land Elasticities in the United States and Brazil","volume":"33","author":"Barr","year":"2011","journal-title":"Appl. Econ. Perspect. Policy"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.apgeog.2015.04.008","article-title":"Converting Brazil\u2019s pastures to cropland: An alternative way to meet sugarcane demand and to spare forestlands","volume":"62","author":"Alkimim","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2941","DOI":"10.1098\/rstb.2010.0127","article-title":"Competition for land","volume":"365","author":"Smith","year":"2010","journal-title":"Philos. Trans. R. Soc. Lond. B Biol. Sci."},{"key":"ref_44","unstructured":"(2018, February 17). DNIT Atlas e Mapas, Available online: http:\/\/www.dnit.gov.br\/mapas-multimodais\/shapefiles."},{"key":"ref_45","unstructured":"(2018, March 11). LAPIG Matadouros e Frigor\u00edficos do Brasil. Available online: http:\/\/maps.lapig.iesa.ufg.br\/?layers=pa_br_matadouros_e_frigorificos_na_2017_lapig."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1016\/j.landusepol.2011.09.009","article-title":"Persistence of cattle ranching in the Brazilian Amazon: A spatial analysis of the rationale for beef production","volume":"29","author":"Bowman","year":"2012","journal-title":"Land Use Policy"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1590\/S0103-20032013000300010","article-title":"De Determinantes dos pre\u00e7os de terras no Brasil: Uma an\u00e1lise de regi\u00e3o de fronteira agr\u00edcola e \u00e1reas tradicionais","volume":"51","author":"Ferro","year":"2013","journal-title":"Rev. Econ. Sociol. Rural"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1007\/s00267-006-0149-2","article-title":"Brazil\u2019s Cuiab\u00e1-Santar\u00e9m (BR-163) Highway: The Environmental Cost of Paving a Soybean Corridor through the Amazon","volume":"39","author":"Fearnside","year":"2007","journal-title":"Environ. Manag."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.forpol.2013.02.009","article-title":"From large to small: Reorienting rural development policies in response to climate change, food security and poverty","volume":"36","author":"Pokorny","year":"2013","journal-title":"For. Policy Econ."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Mullan, K., Sills, E., Pattanayak, S.K., and Caviglia-Harris, J. (2017). Converting Forests to Farms: The Economic Benefits of Clearing Forests in Agricultural Settlements in the Amazon. Environ. Resour. Econ., 1\u201329.","DOI":"10.1007\/s10640-017-0164-1"},{"key":"ref_51","unstructured":"UNDP (2016). Human Development Report 2016: Human Development for Everyone, United Nations Development Programme."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1007\/s12665-015-4865-x","article-title":"Use of spatial regression models in the analysis of burnings and deforestation occurrences in forest region, Amazon, Brazil","volume":"75","author":"Salame","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.biocon.2016.03.005","article-title":"Biodiversity consequences of land-use change and forest disturbance in the Amazon: A multi-scale assessment using ant communities","volume":"197","author":"Barlow","year":"2016","journal-title":"Biol. Conserv."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.3390\/rs2041057","article-title":"Studies on the Rapid Expansion of Sugarcane for Ethanol Production in S\u00e3o Paulo State (Brazil) Using Landsat Data","volume":"2","author":"Rudorff","year":"2010","journal-title":"Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"399","DOI":"10.5216\/pat.v41i3.11054","article-title":"Avan\u00e7o do Setor Sucroalcooleiro e Expans\u00e3o da Fronteira Agr\u00edcola em Goi\u00e1s","volume":"41","author":"Silva","year":"2011","journal-title":"Pesqui. Agropecu. Trop."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"55","DOI":"10.5418\/RA2013.0912.0004","article-title":"Din\u00e2mica Geogr\u00e1fica da Mobilidade do Capital na Produ\u00e7\u00e3o de Celulose e Papel em Tr\u00eas Lagoas (MS)","volume":"9","author":"Perpetua","year":"2013","journal-title":"Rev. Anpege"},{"key":"ref_57","first-page":"149","article-title":"Feasibility Assessment of Sugarcane Expansion in Southwest Goi\u00e1s, Brazil Based on the GIS Technology","volume":"8","author":"Pedrosa","year":"2016","journal-title":"J. Geogr. Inf. Syst."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Richards, P., Pellegrina, H., Van Wey, L., and Spera, S. (2015). Soybean Development: The Impact of a Decade of Agricultural Change on Urban and Economic Growth in Mato Grosso, Brazil. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0122510"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.1017\/S1751731114001566","article-title":"Intensification of cattle ranching production systems: Socioeconomic and environmental synergies and risks in Brazil","volume":"8","author":"Latawiec","year":"2014","journal-title":"Animal"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.agee.2014.10.008","article-title":"Adoption and development of integrated crop\u2013livestock\u2013forestry systems in Mato Grosso, Brazil","volume":"199","author":"Gil","year":"2015","journal-title":"Agric. Ecosyst. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/606\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:00:41Z","timestamp":1760194841000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/606"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,14]]},"references-count":60,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["rs10040606"],"URL":"https:\/\/doi.org\/10.3390\/rs10040606","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,4,14]]}}}