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ABoVE: Light-Curve Modelling of Gridded GPP Using MODIS MAIAC and Flux Tower Data

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Global Change Master Directory (GCMD)2022-09-14 更新2026-04-25 收录
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https://cmr.earthdata.nasa.gov/search/concepts/C2445456434-ORNL_CLOUD.html
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This dataset contains gridded estimations of daily ecosystem Gross Primary Production (GPP) in grams of carbon per day at a 1 km2 spatial resolution over Alaska and Canada from 2000-01-01 to 2018-01-01. Daily estimates of GPP were derived from a light-curve model that was fitted and validated over a network of ABoVE domain Ameriflux flux towers then upscaled using MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) data to span the extended ABoVE domain. In general, the methods involved three steps; the first step involved collecting and processing mainly carbon-flux site-level data, the second step involved the analysis and correction of site-level MAIAC data, and the final step developed a framework to produce large-scale estimates of GPP. The light-curve parameter model was generated by upscaling from flux tower sub-daily temporal resolution by deconvolving the GPP variable into 3 components: the absorbed photosynthetically active radiation (aPAR), the maximum GPP or maximum photosynthetic capacity (GPPmax), and the photosynthetic limitation or amount of light needed to reach maximum capacity (PPFDmax). GPPmax and PPFDmax were related to satellite reflectance measurements sampled at the daily scale. GPP over the extended ABoVE domain was estimated at a daily resolution from the light-curve parameter model using MODIS MAIAC daily reflectance as input. This framework allows large-scale estimates of phenology and evaluation of ecosystem sensitivity to climate change.
提供机构:
ORNL_CLOUD
创建时间:
2022-09-14
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