期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2000
卷号：XXXIII Part B7(/1-4)
页码：272-279
出版社：Copernicus Publications
摘要：Monitoring the growth of agricultural crops during the whole growing season is important for observing anomalies in growth and development in order to be able (1) to adjust the growth of the crops, and (2) to obtain yield predictions well before harvest time. More and more use is being made of crop growth simulation models for this purpose. Remote sensing data can be used for calibrating dynamic crop growth models for actual field conditions, thus rendering the combination of growth models and remote sensing data a valuable tool for growth monitoring. This paper describes the use of SPOT satellite data for deriving crop biophysical parameters at various dates during the growing season. In particular, the leaf area index is estimated by using the semi-empirical CLAIR model. Subsequently, these leaf area index estimates are used for calibrating the mechanistic crop growth model ROTASK. This study is based on measurements obtained during the ReSeDA experiment at the Alpilles test site in Southern France from October 1996 to November 1997. The methodology is applied to a number of wheat fields in the area. A total of four SPOT images during the growing season were used. Results show that crop variables such as leaf area index can be monitored well using SPOT data. Also the calibration of a wheat growth model yields good results. Correspondence with field measurements was satisfactory
