{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T13:59:24Z","timestamp":1762955964417,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,8,21]],"date-time":"2018-08-21T00:00:00Z","timestamp":1534809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2014\/26928\u20132"],"award-info":[{"award-number":["2014\/26928\u20132"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Integrated crop-livestock (ICL) systems combine livestock and crop production in the same area, increasing the efficiency of land use and machinery, while mitigating greenhouse gas emissions, and reducing production risks, plant diseases and pests. ICL systems are primarily divided into annual (ICLa) and multi-annual (ICLm) systems. Projects such as the \u201cIntegrated crop-livestock-forest Network\u201d and the \u201cLivestock Rally\u201d have estimated the ICL areas for Brazil on a state or regional basis. However, it remains necessary to create methods for spatial identification of ICL areas. Thus, we developed a framework for mapping ICL areas in Mato Grosso, Brazil using the Enhanced Vegetation Index time-series of Moderate Resolution Imaging Spectroradiometer and a Time-Weighted Dynamic Time Warping (TWDTW) classification method. The classification of ICL areas occurred in three phases. Phase 1 corresponded to the classification of land use from 2008 to 2016. In Phase 2, the ICLa areas were identified. Finally, Phase 3 corresponded to the ICLm identification. The framework showed overall accuracies of 86% and 92% for ICL areas. ICLm accounted for 87% of the ICL areas. Considering only agricultural areas or only pasture areas, ICL systems represented 5% and 15%, respectively.<\/jats:p>","DOI":"10.3390\/rs10091322","type":"journal-article","created":{"date-parts":[[2018,8,21]],"date-time":"2018-08-21T11:12:42Z","timestamp":1534849962000},"page":"1322","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0881-5741","authenticated-orcid":false,"given":"V\u00edctor Danilo","family":"Manabe","sequence":"first","affiliation":[{"name":"School of Agricultural Engineering, University of Campinas, Campinas, SP 13083-875, Brazil"}]},{"given":"Marcio R. S.","family":"Melo","sequence":"additional","affiliation":[{"name":"Campus of Paragominas, Federal Rural University of Amazonia, Paragominas, PA 68625-970, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3337-4394","authenticated-orcid":false,"given":"Jansle Vieira","family":"Rocha","sequence":"additional","affiliation":[{"name":"School of Agricultural Engineering, University of Campinas, Campinas, SP 13083-875, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,21]]},"reference":[{"key":"ref_1","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":"2013","journal-title":"Nat. Clim. 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