A Integrated Inversion Method for Estimating Global Leaf Area Index from Chinese FY-3A Mersi Data

Global leaf area index (LAI) generally produced based on the satellite sensors with 1 km spatial resolution, such as the advanced very high resolution radiometer (AVHRR), moderate resolution imaging spectroradiometer (MODIS) and VEGETATION. At present, there isn't a LAI product estimated from the Chinese Feng Yun No.3 (FY-3) images. This study aims to generate a 10-day composite LAI product from FY-3A with a medium resolution spectral imaging (MERSI) at global scale in 2011. Making use of the land cover type as priori knowledge, the LAI for pure vegetation types was inversed from a lookup-table (LUT) based on an stochastic three-dimensional radiative transfer model (3D RTM). For the mixed water and vegetation types, LAI was inversed based on an improved linear decomposition method. The accuracy of LAI inversion from FY-3A MERSI was assessed by LAI field measurements from the Chinese ecosystem research network (CERN) in 2011.

[1]  J. Moreno,et al.  Seasonal variations of leaf area index of agricultural fields retrieved from Landsat data , 2008 .

[2]  Aixia Yang,et al.  Cross-calibration of reflective bands of major moderate resolution remotely sensed data , 2018 .

[3]  J. Chen,et al.  Defining leaf area index for non‐flat leaves , 1992 .

[4]  Jindi Wang,et al.  Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Jan G. P. W. Clevers,et al.  Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review , 2015 .

[6]  Ranga B. Myneni,et al.  Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements , 2008 .

[7]  Frédéric Baret,et al.  Development and assessment of leaf area index algorithms for the Sentinel-2 multispectral imager , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[8]  Yonglan Qian,et al.  Winter wheat acreage estimation and assessment in China based on FY-3A/MERSI Vegetation Index time series data , 2012, 2012 First International Conference on Agro- Geoinformatics (Agro-Geoinformatics).

[9]  Martha C. Anderson,et al.  A comparison of empirical and neural network approaches for estimating corn and soybean leaf area index from Landsat ETM+ imagery ☆ , 2004 .

[10]  Hideki Kobayashi,et al.  Reflectance seasonality and its relation to the canopy leaf area index in an eastern Siberian larch forest : Multi-satellite data and radiative transfer analyses , 2007 .

[11]  Jan Pisek,et al.  Algorithm for global leaf area index retrieval using satellite imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Qinhuo Liu,et al.  An Iterative BRDF/NDVI Inversion Algorithm Based on A Posteriori Variance Estimation of Observation Errors , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[13]  F. Baret,et al.  Retrieving wheat Green Area Index during the growing season from optical time series measurements based on neural network radiative transfer inversion , 2011 .

[14]  Ni Guo,et al.  The application of FY-3A/MERSI in drought and vegetation monitoring in Gansu , 2014, 2014 The Third International Conference on Agro-Geoinformatics.

[15]  O. Hagolle,et al.  LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm , 2007 .

[16]  S. Running,et al.  MODIS Leaf Area Index (LAI) And Fraction Of Photosynthetically Active Radiation Absorbed By Vegetation (FPAR) Product , 1999 .

[17]  J. Zhao,et al.  Comparative Analysis of the Difference of the Vegetation Indexes between FY-3A/VIRR, FY-3A/MERSI and Terra/MODIS data , 2016 .

[18]  N. Goel Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data , 1988 .

[19]  Frédéric Baret,et al.  GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production , 2013 .