Google Earth Engine（GEE）——巴西33年次生林年龄基准图v3（1986-2019）

巴西33年次生林年龄基准图v3（1986-2019） 到2030年恢复和重新造林1200万公顷的森林，是《巴黎协定》规定的巴西国家确定贡献目标中减少碳排放的主要缓解战略之一。了解森林覆盖率的动态（1985年至2018年期间巴西全国森林覆盖率急剧下降）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、范围和年龄至关重要；然而，这些变量的量化程度还很低。前言 – 床长人工智能教程

在此，我们开发了巴西1986-2018年期间30米空间分辨率的次生林年度增量、范围和年龄的数据集。来自MapBiomas项目的土地利用和土地覆盖地图被用作我们算法的输入数据，在谷歌地球引擎平台上实施。这个数据集为支持碳减排、生物多样性和恢复政策、实现环境科学应用、领土规划和补贴环境执法提供了关键的空间明确信息。在这里阅读数据集的论文和细节Benchmark maps of 33 years of secondary forest age for Brazil | Zenodo

引用：

Silva Junior, C.H.L., Heinrich, V.H.A., Freire, A.T.G., Broggio, I.S., Rosan, T.M., Doblas, J.,
Anderson, L.O., Rousseau, G.X., Shimabukuro, Y.E., Silva, C.A., House, J.I., Aragão, L.E.O.C.
Benchmark maps of 33 years of secondary forest age for Brazil. Scientific Data (2020).
https://doi.org/10.1038/s41597-020-00600-4

You can access the dataset here: Benchmark maps of 33 years of secondary forest age for Brazil | Zenodo

The updated v3 of the dataset is available directly as GEE collections

Dataset Citation¶

Celso H. L. Silva Junior, Viola H. A. Heinrich, Ana T. G. Freire, Igor S. Broggio, Thais M. Rosan, Juan Doblas,
Luiz E. O. C. Aragão. (2020). Benchmark maps of 33 years of secondary forest age for Brazil (Version v2.0.0)
[Data set]. Scientific Data. Zenodo. http://doi.org/10.5281/zenodo.3928660

Earth Engine Snippet¶

var forest_age = ee.Image('users/celsohlsj/public/secondary_forest_age_collection5_v3');
var forest_extent = ee.Image('users/celsohlsj/public/secondary_forest_extent_collection5_v3');
var forest_increment = ee.Image('users/celsohlsj/public/secondary_forest_increment_collection5_v3');
var forest_loss = ee.Image('users/celsohlsj/public/secondary_forest_loss_collection5_v3');

Sample Code: https://code.earthengine.google.com/?scriptPath=users/sat-io/awesome-gee-catalog-examples:agriculture-vegetation-forestry/BRAZIL-SECONDARY-FOREST-AGE

技术验证 本数据集基于MapBiomas项目的4.1集（巴西年度土地利用和土地覆盖图）1；因此，本文介绍的次生林增量、延伸和树龄图的准确性是以MapBiomas土地利用和土地覆盖数据集的准确性为基础。MapBiomas的精度分析是用Pontius Jr和Millones（2011）的方法进行的23。对于整个巴西24，MapBiomas数据集在1985年至2018年期间，考虑到从图例层面上最详细的土地利用和土地覆盖类别（第3级），其总体精度平均为86.40±0.46%，分配差异为11.06±0.67%，面积差异为2.5±0.29%。巴西生物群落的精度评估可以在MapBiomas精度统计网页（https://mapbiomas.org/en/accuracy-analysis）上找到。

License & Usage¶

This work is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy and redistribute the material in any medium or format, and to transform and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made.

Github Page: https://github.com/celsohlsj/gee_brazil_sv

Export Page for App: https://code.earthengine.google.com/13bfcedb77ac7bac9ea1fb962b587a54?hideCode=true

Zenodo Data download page: https://zenodo.org/record/3928660

Created and Curated by: Celso H. L. Silva Junior

Keywords: Deforestation, MapBiomas, Climate Change, Forest Restoration, Carbon Sequestration

Last updated: 2021-03-05