{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:30:28Z","timestamp":1772253028648,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,20]],"date-time":"2022-02-20T00:00:00Z","timestamp":1645315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Brazilian livestock is predominantly extensive, with approximately 90% of the production being sustained on pasture, which occupies around 20% of the territory. It is estimated that more than half of Brazilian pastures have some level of degradation. In this study, we mapped and evaluated the spatiotemporal dynamics of pasture quality in Brazil, between 2010 and 2018, considering three classes of degradation: Absent (D0), Intermediate (D1), and Severe (D2). There was no variation in the total area occupied by pastures in the evaluated period, in spite of the accentuated spatial dynamics. The percentage of non-degraded pastures increased by ~12%, due to the recovery of degraded areas and the emergence of new pasture areas. However, about 44 Mha of the pasture area is currently severely degraded. The dynamics in pasture quality were not homogeneous in property size classes. We observed that in the approximately 2.68 million properties with livestock activity, the proportion with quality gains was twice as low in small properties compared with large ones, and the proportion with losses was three times greater, showing an increase in inequality between properties with more and fewer resources (large and small properties, respectively). The areas occupied by pastures in Brazil present a unique opportunity to increase livestock production and make areas available for agriculture, without the need for new deforestation in the coming decades.<\/jats:p>","DOI":"10.3390\/rs14041024","type":"journal-article","created":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T08:23:29Z","timestamp":1645431809000},"page":"1024","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Assessing the Wall-to-Wall Spatial and Qualitative Dynamics of the Brazilian Pasturelands 2010\u20132018, Based on the Analysis of the Landsat Data Archive"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4181-1929","authenticated-orcid":false,"given":"Claudinei Oliveira dos","family":"Santos","sequence":"first","affiliation":[{"name":"Image Processing and GIS Laboratory (LAPIG), Federal University of Goi\u00e1s (UFG), Goiania 74001-970, GO, Brazil"}]},{"given":"Vin\u00edcius Vieira","family":"Mesquita","sequence":"additional","affiliation":[{"name":"Image Processing and GIS Laboratory (LAPIG), Federal University of Goi\u00e1s (UFG), Goiania 74001-970, GO, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1589-0467","authenticated-orcid":false,"given":"Leandro Leal","family":"Parente","sequence":"additional","affiliation":[{"name":"Image Processing and GIS Laboratory (LAPIG), Federal University of Goi\u00e1s (UFG), Goiania 74001-970, GO, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9380-5021","authenticated-orcid":false,"given":"Alexandre de Siqueira","family":"Pinto","sequence":"additional","affiliation":[{"name":"Ecology Department, Federal University of Sergipe, S\u00e3o Crist\u00f3v\u00e3o 49100-000, SE, Brazil"}]},{"suffix":"Jr.","given":"Laerte Guimaraes","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Image Processing and GIS Laboratory (LAPIG), Federal University of Goi\u00e1s (UFG), Goiania 74001-970, GO, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,20]]},"reference":[{"key":"ref_1","unstructured":"ABIEC (2020). 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