FAPAR Monthly Time-Series (250 M): Long-term Trend (2000-2021)

Julia Hackländer,Leandro Parente, Yu-Feng Ho, Davide Consoli,Tomislav Hengl

Zenodo (CERN European Organization for Nuclear Research)(2023)

引用 0|浏览0
暂无评分
摘要
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 images inside the months and one image before and after, about 5 to 6 images for a single month depending on the number of images inside the 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. Cloudy pixels were removed and only positive values of water vapor were considered to compute the statistics. The time-series gap-filling and time-series analysis were computed using the Scikit-map Python package. Statistical methods used: for the long-term, trend analysis 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 use some of the following channels: Technical issues and questions about the code: GitLab Issues General questions and comments: LandGIS Forum 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)
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要