文献类型： 外文期刊

作者： Casa, R. ¹ ; Silvestro, P. C. ¹ ; Yang, H. ² ; Pignatti, S. ³ ; Pascucci, S. ³ ; Yang, G. ² ;

作者机构： 1.Univ Tuscia, DAFNE, Via San Camillo de Lellis, Viterbo, Italy

2.Beijing Acad Agr & Forestry Sci, Natl Engn Res Ctr Informat Technol Agr, Beijing, Peoples R China

3.CNR, IMAA, Potenza, Italy

4.Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing, Peoples R China

关键词： Crop model;Aquacrop;SAFY;sensitivity analysis;Ensemble Kalman Filter (EnKF)

期刊名称：2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)

ISSN： 2153-6996

年卷期： 2015 年

页码：

收录情况： SCI

摘要： The aim of this work is the development of methods for the assimilation of biophysical variables, estimated from multi-source remote sensing data, into crop growth models, in order to estimate the yield losses due to drought both at the farm and at the regional scale. A methodology to obtain maps of leaf area index (LAI), and fractional canopy cover (CC), from HJ1A and HJ1B Chinese satellite optical data was established, using an algorithm based on the training of artificial neural networks (ANN) on PROSAIL model simulations. Retrieved values of biophysical variables, such as LAI or CC, will be assimilated into crop growth models in order to estimate wheat yield. The present work focused on testing two different approaches using a common dataset gathered in Xiaotangshan (China) with two crop models of different complexity, in order to compare the procedures and analyse the responses of the models, before the subsequent application at a regional scale in Yangling, Shaanxi, Central China.