NDLI: Research on PAR and FPAR of crop canopies based on RGM

Content Provider	IEEE Xplore Digital Library
Author	Donghui Xie Peijuan Wang Rongyuan Liu Qijiang Zhu
Copyright Year	2010
Description	Author affiliation: Chinese Academy of Meteorological Sciences, 100081, China (Peijuan Wang) \|\| State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications, CAS, China (Donghui Xie; Rongyuan Liu; Qijiang Zhu)
Abstract	PAR and FPAR are two important variables in agricultural field. Some researches show that many factors, such as LAI(leaf area index), LAD(leaf ange distribution) and the heterogeneity of vegetation will affect the distribution of PAR and FPAR. In order to understanding the exchange process of material and energy, Radiosity-Graphics combined Model (RGM) (Qin et al., 2000) is used to simulate the distribution of PAR and FPAR in canopy and some effect factors, such as the structure of canopy and sun zenith angle, can be analyze carefully. PAR and FPAR of a typical winter wheat canopy is simulated and the results are validated with the measured data. They agreed well. Next work is to simulate and analyze several factors of the distribution of PAR and FPAR, including sun incident angle, LAD, LAI, special for the heterogeneous canopies such as that crop with width and narrow ridges which can direct cropping patterns and remote sensing inversion.
Starting Page	1493
Ending Page	1496
File Size	243735
Page Count	4
File Format	PDF
ISBN	9781424495658
ISSN	21537003
e-ISBN	9781424495665
e-ISBN	9781424495641
DOI	10.1109/IGARSS.2010.5652908
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Computational modeling Analytical models Reflectivity Agriculture Mathematical model Data models LAI PAR FPAR Radiosity LAD
Content Type	Text
Resource Type	Article

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Analyzing the characteristics of FPAR from maize canopies measured in Northwest China

Estimation of maize LAI by assimilating remote sensing data into crop model

Extending RGM to simulate the directional reflectance for complex mountainous regions

Regional yield estimation of summer maize based on assimilation of remotely sensed LAI into EPIC model

Integration of multi-resolution data for crop LAI estimation based on continuous wavelet

Retrieval of time series LAI by coupling an empirical crop growth model with a radiative transfer model

Research on FPAR vertical distribution in different variety maize canopy

A data-based mechanistic assimilation method to estimate time series LAI

Integrating remotely sensed lai with epic model based on global optimization algorithm for regional crop yield assessment

Research on PAR and FPAR of crop canopies based on RGM

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