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Monthly aggregated GLASS FAPAR V6 (250 m): 95th percentile monthly time-series (2011)

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Zenodo2023-11-30 更新2026-05-26 收录
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List of Subdatasets: Long-term data: 2000-2021 5th percentile (p05) monthly time-series: 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 50th percentile (p50) monthly time-series: 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 95th percentile (p95) monthly time-series: 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 General Description The monthly aggregated Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) dataset is derived from 250m 8d GLASS V6 FAPAR. The data set is derived from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and LAI data using several other FAPAR products (MODIS Collection 6, GLASS FAPAR V5, and PROBA-V1 FAPAR) to generate a bidirectional long-short-term memory (Bi-LSTM) model to estimate FAPAR. The dataset time spans from March 2000 to December 2021 and provides data that covers the entire globe. The dataset can be used in many applications like land degradation modeling, land productivity mapping, and land potential mapping. The dataset includes: Long-term: Derived from monthly time-series. This dataset provides linear trend model for the p95 variable: (1) slope beta mean (p95.beta_m), p-value for beta (p95.beta_pv), intercept alpha mean (p95.alpha_m), p-value for alpha (p95.alpha_pv), and coefficient of determination R2 (p95.r2_m). Monthly time-series: Monthly aggregation with three standard statistics: (1) 5th percentile (p05), median (p50), and 95th percentile (p95). For each month, we aggregate all composites within that month plus one composite each before and after, ending up with 5 to 6 composites for a single month depending on the number of images within that month. Data Details Time period: March 2000 – December 2021 Type of data: Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) How the data was collected or derived: Derived from 250m 8 d GLASS V6 FAPAR using Python running in a local HPC. The time-series analysis were computed using the Scikit-map Python package. Statistical methods used: for the long-term, Ordinary Least Square (OLS) of p95 monthly variable; for the monthly time-series, percentiles 05, 50, and 95. Limitations or exclusions in the data: The dataset does not include data for Antarctica. Coordinate reference system: EPSG:4326 Bounding box (Xmin, Ymin, Xmax, Ymax): (-180.00000, -62.0008094, 179.9999424, 87.37000) Spatial resolution: 1/480 d.d. = 0.00208333 (250m) Image size: 172,800 x 71,698 File format: Cloud Optimized Geotiff (COG) format. Support If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues Reference Hackländer, J., Parente, L., Ho, Y.-F., Hengl, T., Simoes, R., Consoli, D., Şahin, M., Tian, X., Herold, M., Jung, M., Duveiller, G., Weynants, M., Wheeler, I., (2023?) "Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution", submitted to PeerJ, preprint available at: https://doi.org/10.21203/rs.3.rs-3415685/v1 Name convention To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: generic variable name: fapar = Fraction of Absorbed Photosynthetically Active Radiation variable procedure combination: essd.lstm = Earth System Science Data with bidirectional long short-term memory (Bi–LSTM) Position in the probability distribution / variable type: p05/p50/p95 = 5th/50th/95th percentile Spatial support: 250m Depth reference: s = surface Time reference begin time: 20000301 = 2000-03-01 Time reference end time: 20211231 = 2022-12-31 Bounding box: go = global (without Antarctica) EPSG code: epsg.4326 = EPSG:4326 Version code: v20230628 = 2023-06-28 (creation date)

子数据集列表: 长期数据集:2000-2021年 第5百分位数(5th percentile, p05)月度时间序列:2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 第50百分位数(50th percentile, p50)月度时间序列:2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 第95百分位数(95th percentile, p95)月度时间序列:2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 总体说明 月度聚合光合有效辐射吸收比(Fraction of Absorbed Photosynthetically Active Radiation, FAPAR)数据集源自250米8天合成的GLASS V6 FAPAR产品。本数据集基于中分辨率成像光谱仪(Moderate Resolution Imaging Spectroradiometer, MODIS)反射率与叶面积指数(Leaf Area Index, LAI)数据,并结合多款FAPAR产品(MODIS Collection 6、GLASS FAPAR V5及PROBA-V1 FAPAR),通过双向长短期记忆网络(bidirectional long-short-term memory, Bi-LSTM)模型估算得到FAPAR数据。数据集时间跨度为2000年3月至2021年12月,覆盖全球全域。该数据集可应用于土地退化建模、土地生产力制图及土地潜力制图等诸多场景。数据集包含以下内容: 长期数据集: 基于月度时间序列衍生。本数据集为p95变量提供线性趋势模型:(1) 斜率β均值(p95.beta_m)、β的p值(p95.beta_pv)、截距α均值(p95.alpha_m)、α的p值(p95.alpha_pv)以及决定系数R²(p95.r2_m)。 月度时间序列: 对月度数据进行聚合,采用三类标准统计量:(1) 第5百分位数(p05)、中位数(p50)及第95百分位数(p95)。对于每个月份,我们会聚合该月内的所有合成影像,以及该月份前后各1景合成影像,最终单个月份可获得5至6景合成影像,具体数量取决于当月有效影像的数量。 数据详情 时间范围:2000年3月—2021年12月 数据类型:光合有效辐射吸收比(Fraction of Absorbed Photosynthetically Active Radiation, FAPAR) 数据获取或衍生方式:基于本地高性能计算集群(HPC)运行Python脚本,从250米8天合成的GLASS V6 FAPAR产品衍生得到。时间序列分析通过Scikit-map Python包完成。 所用统计方法:针对长期数据集,采用p95月度变量的普通最小二乘法(Ordinary Least Square, OLS);针对月度时间序列,采用第5、50、95百分位数统计。 数据局限性或排除范围:本数据集未包含南极洲区域的数据。 坐标参考系统:EPSG:4326 边界框(Xmin, Ymin, Xmax, Ymax):(-180.00000, -62.0008094, 179.9999424, 87.37000) 空间分辨率:1/480 d.d. = 0.00208333(约250米) 影像尺寸:172,800 × 71,698 文件格式:云优化地理标签图像文件格式(Cloud Optimized Geotiff, COG)。 技术支持 若您发现数据存在错误、异常或不一致问题,或有相关疑问,请提交GitHub议题:https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues 参考文献 Hackländer, J., Parente, L., Ho, Y.-F., Hengl, T., Simoes, R., Consoli, D., Şahin, M., Tian, X., Herold, M., Jung, M., Duveiller, G., Weynants, M., Wheeler, I., (2023?) "Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution", 已投稿至PeerJ,预印本可在:https://doi.org/10.21203/rs.3.rs-3415685/v1 获取。 命名规范 为确保项目内及跨项目的数据一致性与易用性,本数据集遵循Open-Earth-Monitor标准文件命名约定。该命名规则包含10个字段,用于描述数据的关键属性,用户可无需打开文件即可实现文件检索、数据分析准备等操作。各字段说明如下: 1. 通用变量名:fapar = 光合有效辐射吸收比(Fraction of Absorbed Photosynthetically Active Radiation) 2. 变量-处理流程组合:essd.lstm = 采用双向长短期记忆网络(Bi-LSTM)的地球系统科学数据(Earth System Science Data) 3. 概率分布位置/变量类型:p05/p50/p95 = 第5/50/95百分位数 4. 空间分辨率:250m 5. 深度参考:s = 地表(surface) 6. 时间参考起始时间:20000301 = 2000-03-01 7. 时间参考结束时间:20211231 = 2022-12-31 8. 空间覆盖范围:go = 全球(不含南极洲) 9. EPSG代码:epsg.4326 = EPSG:4326 10. 版本代码:v20230628 = 2023-06-28(数据集创建日期)

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2023-10-10
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