A Comparison between the MODIS product (MOD17A2) and a tide-robust empirical GPP model evaluated in a Georgia Wetland

Jianbin Tao, Deepak R. Mishra, David L. Cotten, Jessica O'Connell, Monique Leclerc, Hafsah Binti Nahrawi, Gengsheng Zhang, Roshani Pahari

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Despite the importance of tidal ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these wetlands remain poorly understood. This limited understanding results from the challenges associated with in situ flux studies and their correlation with satellite imagery which can be affected by periodic tidal flooding. Carbon dioxide eddy covariance (EC) towers are installed in only a few wetlands worldwide, and the longest eddy-covariance record from Georgia (GA) wetlands contains only two continuous years of observations. The goals of the present study were to evaluate the performance of existing MODIS Gross Primary Production (GPP) products (MOD17A2) against EC derived GPP and develop a tide-robust Normalized Difference Moisture Index (NDMI) based model to predict GPP within a Spartina alterniflora salt marsh on Sapelo Island, GA. These EC tower-based observations represent a basis to associate CO2 fluxes with canopy reflectance and thus provide the means to use satellite-based reflectance data for broader scale investigations. We demonstrate that Light Use Efficiency (LUE)-based MOD17A2 does not accurately reflect tidal wetland GPP compared to a simple empirical vegetation index-based model where tidal influence was accounted for. The NDMI-based GPP model was capable of predicting changes in wetland CO2 fluxes and explained 46% of the variation in flux-estimated GPP within the training data, and a root mean square error of 6.96 g C m-2 in the validation data. Our investigation is the first to create a MODIS-based wetland GPP estimation procedure that demonstrates the importance of filtering tidal observations from satellite surface reflectance data.

Original languageEnglish
Article number1831
JournalRemote Sensing
Volume10
Issue number11
DOIs
StatePublished - Nov 1 2018
Externally publishedYes

Funding

We would thank GCE LTER project for providing the flux data. Moreover, the authors would also like to thank the anonymous reviewers for their comments and suggestions on this paper. This is contribution number 1073 of GCE-LTER. This work was partially supported by Natural Science Foundation of Hubei Province (The Spatial-temporal variations of vegetation dynamics of Jianghan Plain during 2001 and 2016). This project was also funded by D. Mishra's NASA grant#NNX14AR30G and the Georgia Coastal Ecosystems LTER, which is supported by the National Science Foundation (OCE12-37140). Funding: This work was partially supported by Natural Science Foundation of Hubei Province (The Spatial-temporal variations of vegetation dynamics of Jianghan Plain during 2001 and 2016). This project was also funded by D. Mishra’s NASA grant#NNX14AR30G and the Georgia Coastal Ecosystems LTER, which is supported by the National Science Foundation (OCE12-37140).

FundersFunder number
National Science FoundationOCE12-37140
National Aeronautics and Space Administration14AR30G, #NNX14AR30G
Natural Science Foundation of Hubei Province
National Science Foundation

    Keywords

    • Flux GPP
    • MOD17A2
    • MODIS GPP calibration
    • Normalized distribution moisture index
    • Salt marsh
    • Tidal wetlands
    • Tide adjusted wetland index

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