Preprints
https://doi.org/10.5194/essd-2022-131
https://doi.org/10.5194/essd-2022-131
 
02 Aug 2022
02 Aug 2022
Status: a revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

Global land surface 250-m 8-day Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product from 2000 to 2020

Han Ma1, Shunlin Liang2, Changhao Xiong1, Qian Wang3, and Aolin Jia2 Han Ma et al.
  • 1School of Remote Sensing and Information Engineering, Wuhan University, Hubei, 430010, China
  • 2Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA
  • 3Faculty of Geography, Beijing Normal University, Beijing, 100875, China

Abstract. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a critical land surface variable for carbon cycle modeling and ecological monitoring. Several global FAPAR products have been released and have become widely used; however, spatiotemporal inconsistency remains a large issue for the current products, and their spatial resolutions and accuracies can hardly meet the user requirements. An effective solution to improve the spatiotemporal continuity and accuracy of FAPAR products is to take better advantage of the temporal information in the satellite data using deep learning approaches. In this study, the latest version (V6) of the FAPAR product with a 250-m resolution was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data and other information, as part of the Global Land Surface Satellite (GLASS) products suite. In addition, it was aggregated to multiple coarser resolutions (up to 0.25° and monthly). Three existing global FAPAR products (MODIS Collection 6, GLASS V5, and PROBA-V V1) were used to generate the time series training samples, which were used to develop a Bidirectional Long Short-Term Memory (Bi-LSTM) model. Direct validation using high-resolution FAPAR maps from the Validation of Land European Remote sensing Instrument (VALERI) and ImagineS networks revealed that the GLASS V6 FAPAR product has a higher accuracy than PROBA-V, MODIS, and GLASS V5, with an R2 value of 0.80 and Root Mean Square Errors (RMSEs) of 0.10–0.11 at the 250-m, 500-m, and 3-km scales, and a higher percentage (72 %) of retrievals for meeting the accuracy requirement of 0.1. Global spatial evaluation and temporal comparison at the Ameriflux and National Ecological Observatory Network (NEON) sites revealed that the GLASS V6 FAPAR has a greater spatiotemporal continuity and reflects the variations in the vegetation better than the GLASS V5 FAPAR. The higher quality of the GLASS V6 FAPAR is attributed to the ability of the Bi-LSTM model, which involved high-quality training samples and combines the strengths of the existing FAPAR products, as well as the temporal and spectral information from the MODIS surface reflectance data and other information.

Han Ma et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-131', Anonymous Referee #1, 04 Sep 2022
  • RC2: 'Comment on essd-2022-131', Anonymous Referee #2, 23 Sep 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-131', Anonymous Referee #1, 04 Sep 2022
  • RC2: 'Comment on essd-2022-131', Anonymous Referee #2, 23 Sep 2022

Han Ma et al.

Data sets

A global land surface 250-m 8-day Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product (2022-part2) Han Ma https://doi.org/10.5281/zenodo.6430925

A global land surface 250-m 8-day Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product (2022-part1) Han Ma https://doi.org/10.5281/zenodo.6405564

Han Ma et al.

Viewed

Total article views: 471 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
352 102 17 471 9 10
  • HTML: 352
  • PDF: 102
  • XML: 17
  • Total: 471
  • BibTeX: 9
  • EndNote: 10
Views and downloads (calculated since 02 Aug 2022)
Cumulative views and downloads (calculated since 02 Aug 2022)

Viewed (geographical distribution)

Total article views: 451 (including HTML, PDF, and XML) Thereof 451 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Dec 2022
Download
Short summary
Fraction of Absorbed Photosynthetically Active Radiation is one of the essential climate variables, this study generated a global land surface FAPAR product with a 250-m resolution based on a deep learning model that takes advantage of the existing FAPAR products and MODIS time-series observation information. Direct validation and intercomparisons revealed that our product has higher percentage for meeting user requirement and a greater spatiotemporal continuity than other existing products.