Benchmark maps of 33 years of secondary forest age for Brazil

Benchmark maps of 33 years of secondary forest age for Brazil
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巴西次生林年龄 33 年的基准图

DOI:
10.1038/s41597-020-00600-4
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发表时间:
2020
期刊:
影响因子:
9.8
通讯作者:
Silva, Carlos A.
Silva, Carlos A.
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Silva Junior, Celso H.;Heinrich, Viola H.;Freire, Ana T.;Broggio, Igor S.;Rosan, Thais M.;Doblas, Juan;Anderson, Liana O.;Rousseau, Guillaume X.;Shimabukuro, Yosio E.;Silva, Carlos A.

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到2030年恢复和重新造林1200万公顷的森林,是在《巴黎协定》规定的巴西国家自主贡献目标范围内减少碳排放的主要减缓战略之一。1985年至2018年期间,整个巴西的森林覆盖率急剧下降,了解森林覆盖率的动态对于估计全球碳平衡和量化生态系统服务的提供至关重要。了解次生林的长期增量、范围和年龄是至关重要的;然而,这些变量的量化还很差。在这里,我们开发了一个30米空间分辨率的数据集,记录了1986-2018年期间巴西次生林的年增量、范围和年龄。MapBiomas项目(集合4.1)的土地利用和土地覆盖图被用作我们的算法的输入数据,在谷歌地球引擎平台上实现。该数据集为支持碳减排、生物多样性和恢复政策、促进环境科学应用、领土规划和补贴环境执法提供了关键的空间明确信息。
The restoration and reforestation of 12 million hectares of forests by 2030 are amongst the leading mitigation strategies for reducing carbon emissions within the Brazilian Nationally Determined Contribution targets assumed under the Paris Agreement. Understanding the dynamics of forest cover, which steeply decreased between 1985 and 2018 throughout Brazil, is essential for estimating the global carbon balance and quantifying the provision of ecosystem services. To know the long-term increment, extent, and age of secondary forests is crucial; however, these variables are yet poorly quantified. Here we developed a 30-m spatial resolution dataset of the annual increment, extent, and age of secondary forests for Brazil over the 1986–2018 period. Land-use and land-cover maps from MapBiomas Project (Collection 4.1) were used as input data for our algorithm, implemented in the Google Earth Engine platform. This dataset provides critical spatially explicit information for supporting carbon emissions reduction, biodiversity, and restoration policies, enabling environmental science applications, territorial planning, and subsidizing environmental law enforcement.
DOI: --
发表时间: 2020
影响因子: 6.7
作者:
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影响因子: 16.6
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作者更正:巴西次生林年龄 33 年的基准图
DOI: --
发表时间: 2020
期刊: Scientific Data
影响因子: 9.8
作者:
C. H. L. Silva Junior;Viola H. A. Heinrich;A. Freire;Igor S. Broggio;T. Rosan;J. Doblas;L. Anderson;G. Rousseau;Y. Shimabukuro;C. Silva;J. House;L. Aragão
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