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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Assessing the pasturelands and livestock dynamics in Brazil, from 1985 to 2017: A novel approach based on high spatial resolution imagery and Google Earth Engine cloud computing
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Assessing the pasturelands and livestock dynamics in Brazil, from 1985 to 2017: A novel approach based on high spatial resolution imagery and Google Earth Engine cloud computing

机译:从1985年到2017年评估巴西的牧场和牲畜动态:一种基于高空间分辨率图像和谷歌地球发动机云计算的新型方法

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摘要

The livestock activity accounts for a large part of the transformations in land cover in the world, with pasture areas being the main land use in Brazil and the main livelihood of the largest commercial herd in the world. In this sense, a better understanding of the spatial-temporal dynamics of pasture areas is of fundamental importance for a better occupation and territorial governance. Moreover, because they provide different ecosystem services, pastures play a key role in mitigating climate change and in meeting GHG emission reduction targets. Within this context, and based on Landsat image processing via machine learning methods in a cloud computing platform (Google Earth Engine), this work has mapped, annually and in an unprecedented way, the totality of the Brazilian pastures, from 1985 to 2017. With an overall accuracy of about 90%, the 33 maps produced indicated the pasture area varying from similar to 118 Mha +/- 3.41% (1985) to similar to 178 Mha +/- 2.53% (2017), with this expansion occurring mostly in the northern region of the country and to a lesser extent in the midwest. Temporarily, most of this expansion occurred in the first half of the period evaluated (i.e. between 1985 and 2002), with an increase in Brazilian pasture areas of similar to 57 mha in just 17 years. After 2002, this area remained relatively stable, varying between similar to 175 mha +/- 2.48% and similar to 178 mha +/- 2.53% by 2017. In 33 years, about 87% of the mapped areas experienced zero, one, two, or three land-cover / land-use transitions; overall, of the similar to 178 mha 2.53% of existing pastures in 2017, similar to 52 mha are at least 33 years old, similar to 66 mha were formed after 1985, and similar to 33 mha may have undergone some reform action in the period under consideration. The dynamics revealed in this study reinforce the thesis of pasture utilization as a land reserve, and demonstrate the importance of these areas in the economic, social, and environmental aspe
机译:畜牧业活动占世界土地覆盖中的大部分变换,牧场地区是巴西的主要土地利用以及世界上最大的商业群体的主要生计。从这个意义上讲,对牧场地区的空间动态更好地了解更好的职业和领土治理的重要意义。此外,由于它们提供了不同的生态系统服务,牧场在缓解气候变化和符合GHG减排目标方面发挥着关键作用。在这种情况下,基于通过机器学习方法在云计算平台(Google地球发动机)中的Landsat图像处理,这项工作每年和以前所未有的方式映射,巴西牧场的总体,从1985年到2017年。随着整体准确性约为90%,产生的33层映射指示从类似于118 MHA +/- 3.41%(1985)的牧场地区,以类似于178 MHA +/- 2.53%(2017),主要发生这种扩展该国北部地区和中西部的程度较小。暂时,大多数这种扩张发生在评估的期末(即1985年至2002年之间),巴西牧场地区的增加与公约仅17岁类似于57 MHA。在2002年之后,该地区仍然相对稳定,与2017年相比相似,与175 MHA +/- 2.48%相同,与178 MHA +/- 2.53%相似。33年来,约87%的映射区域经历了零,一,两个或三个陆地覆盖/土地使用过渡;总体而言,2017年的现有牧场的相似,类似于52名MHA,至少33岁,类似于1985年后形成的66米,类似于33 MHA可能在该期间发生了一些改革行动在考虑中。本研究中透露的动态加强了牧场利用作为土地储备的论点,并证明了这些地区在经济,社会和环境中的重要性

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