Share Email Print
cover

Proceedings Paper

Spectral and agronomical indicators of crop yield
Author(s): Rumiana Kancheva; Georgi Georgiev
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Being recognized as a powerful tool in many scientific and application fields, remote sensing enters recently still wider into its utilization stage when the goal is to bring the up-to-now investigation results to an operational use. Agricultural monitoring is among the priorities of remote sensing observations supplying early information on the development and growth conditions of crops. Various approaches have been used for crop behavior assessment in order to provide objective, timely and quantitative yield forecasts at regional and national scales. Among these approaches are phenology tracking, agro-meteorological modeling, remote sensing data implementation. On the other hand, continues the research to improve the reliability of the results by implying, for instance, different sampling strategies, different statistical data analysis and extrapolations, different data integration from various sources. In this paper we test an approach for yield forecasting and verification of the predictions with consideration of plant phenology. It comprises the development of simple yield prediction models based on key crop bioparameters; the development of crop spectral-biophysical relationships for crop variables retrieval and yield prediction from multispectral reflectance data; verification of the spectral predictions via crop yield agronomical indicators.

Paper Details

Date Published: 7 October 2011
PDF: 8 pages
Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 817413 (7 October 2011); doi: 10.1117/12.898294
Show Author Affiliations
Rumiana Kancheva, Space and Solar-Terrestrial Research Institute (Bulgaria)
Georgi Georgiev, Space and Solar-Terrestrial Research Institute (Bulgaria)


Published in SPIE Proceedings Vol. 8174:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

© SPIE. Terms of Use
Back to Top