Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup
By J. Morisette, Frédéric Baret, J. Privette, Ranga B. Myneni, J. Nickeson, S. Garrigues, N. Shabanov, Marie Weiss, Richard A. Fernandes, Sylvain G. Leblanc and 20 more. IEEE Transactions on Geoscience and Remote Sensing, 2006
420 citations recorded by the source corpus.
Subfields: Atmospheric Science, Ecology, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/5e2b5195665c1ded23e2107d69f290cf1098beb1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
In Ecology
- Qinhuo Liu
- Frédéric Baret
- Zhiqiang Xiao
- Jindi Wang
- Marie Weiss
- Jinling Song
- Shilong Piao
- Yuri Knyazikhin
In Environmental Engineering
- Qinhuo Liu
- Zhiqiang Xiao
- Jindi Wang
- Jinling Song
- Frédéric Baret
- Denis Allard
- Yuri Knyazikhin
- Arindam Samanta
Citations in the corpus
- Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data (2006, background): “Improving and assessing the accuracy of LAI estimates is therefore required (Morisette et al., 2002, 2006; Baret et al., in press).”
- Long-Time-Series Global Land Surface Satellite Leaf Area Index Product Derived From MODIS and AVHRR Surface Reflectance (2016, methodology): “According to guidelines defined by the CEOS/WGCV LPV subgroup, a comparison can be performed by upscaling the LAI ground measurements to the moderate-resolution products using high-resolution remotely sensed imagery [36].”
- Global Data Sets of Vegetation Leaf Area Index (LAI)3g and Fraction of Photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011 (2013, background): “In the process, the community has also developed common protocols for sampling the field sites and scaling methodologies that translate point-based field measurements of LAI and FPAR to the spatial scale of remotely-sensed products to facilitate accurate validation [35,64].”
- Analysis of Global LAI/FPAR Products from VIIRS and MODIS Sensors for Spatio-Temporal Consistency and Uncertainty from 2012–2016 (2018, methodology): “The generated LAI/FPAR maps can be aggregated to match the product pixel grid and are used as the benchmark to validate products [46].”