Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil
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...
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doaj-2be5237159874e45b523627a7fc5c8e82020-11-25T00:13:17ZengMDPI AGRemote Sensing2072-42922018-08-01109132210.3390/rs10091322rs10091322Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, BrazilVíctor Danilo Manabe0Marcio R. S. Melo1Jansle Vieira Rocha2School of Agricultural Engineering, University of Campinas, Campinas, SP 13083-875, BrazilCampus of Paragominas, Federal Rural University of Amazonia, Paragominas, PA 68625-970, BrazilSchool of Agricultural Engineering, University of Campinas, Campinas, SP 13083-875, BrazilIntegrated 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 “Integrated crop-livestock-forest Network” and the “Livestock Rally” 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.http://www.mdpi.com/2072-4292/10/9/1322time seriesenhanced vegetation indexland-use intensificationTime-Weighted Dynamic Time Warping (TWDTW)temporal pattern |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Víctor Danilo Manabe Marcio R. S. Melo Jansle Vieira Rocha |
spellingShingle |
Víctor Danilo Manabe Marcio R. S. Melo Jansle Vieira Rocha Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil Remote Sensing time series enhanced vegetation index land-use intensification Time-Weighted Dynamic Time Warping (TWDTW) temporal pattern |
author_facet |
Víctor Danilo Manabe Marcio R. S. Melo Jansle Vieira Rocha |
author_sort |
Víctor Danilo Manabe |
title |
Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil |
title_short |
Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil |
title_full |
Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil |
title_fullStr |
Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil |
title_full_unstemmed |
Framework for Mapping Integrated Crop-Livestock Systems in Mato Grosso, Brazil |
title_sort |
framework for mapping integrated crop-livestock systems in mato grosso, brazil |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-08-01 |
description |
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 “Integrated crop-livestock-forest Network” and the “Livestock Rally” 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. |
topic |
time series enhanced vegetation index land-use intensification Time-Weighted Dynamic Time Warping (TWDTW) temporal pattern |
url |
http://www.mdpi.com/2072-4292/10/9/1322 |
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