F
Faith Ann Heinsch
Researcher at University of Montana
Publications - 30
Citations - 6670
Faith Ann Heinsch is an academic researcher from University of Montana. The author has contributed to research in topics: Primary production & Moderate-resolution imaging spectroradiometer. The author has an hindex of 17, co-authored 29 publications receiving 5917 citations. Previous affiliations of Faith Ann Heinsch include Texas A&M University & United States Forest Service.
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Journal ArticleDOI
A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production
Steven W. Running,Ramakrishna R. Nemani,Faith Ann Heinsch,Maosheng Zhao,Matthew C. Reeves,Hirofumi Hashimoto +5 more
TL;DR: A new satellite-driven monitor of the global biosphere that regularly computes daily gross primary production and annual net primary production at 1-kilometer (km) resolution over 109,782,756 km2 of vegetated land surface is introduced.
Journal ArticleDOI
Improvements of the MODIS terrestrial gross and net primary production global data set
TL;DR: In this article, a reprocessing key inputs to MODIS primary vegetation productivity algorithm, resulting in improved Collection5-MOD17 (here denoted as C5 MOD17) estimates.
Journal ArticleDOI
Development of a global evapotranspiration algorithm based on MODIS and global meteorology data
TL;DR: In this article, the authors developed a global remote sensing evapotranspiration (ET) algorithm based on Cleugh et al.'s [Cleugh, H.A., R. Leuning, Q. Mu, S.W. Running (2007) Regional evaporation estimates from flux tower and MODIS satellite data.
Journal ArticleDOI
Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations
Faith Ann Heinsch,Maosheng Zhao,Steven W. Running,John S. Kimball,Ramakrishna R. Nemani,Kenneth J. Davis,Paul V. Bolstad,Bruce D. Cook,Ankur R. Desai,Daniel M. Ricciuto,Beverly E. Law,Walter C. Oechel,Hyojung Kwon,Hongyan Luo,Steven C. Wofsy,Allison L. Dunn,J. W. Munger,Dennis D. Baldocchi,Liukang Xu,David Y. Hollinger,Andrew D. Richardson,Paul C. Stoy,Mario B. S. Siqueira,Russell K. Monson,Sean P. Burns,Lawrence B. Flanagan +25 more
TL;DR: The results of this study indicate that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes.