Spectral and agronomical indicators of crop yield

Rumiana Kancheva; Georgi Georgiev

doi:10.1117/12.898294

7 October 2011 Spectral and agronomical indicators of crop yield

Rumiana Kancheva, Georgi Georgiev

Proceedings Volume 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII; 817413 (2011) https://doi.org/10.1117/12.898294
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

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.

Citation Download Citation

Rumiana Kancheva and Georgi Georgiev "Spectral and agronomical indicators of crop yield", Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 817413 (7 October 2011); https://doi.org/10.1117/12.898294

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KEYWORDS

Data modeling

Vegetation

Remote sensing

Reflectivity

Biological research

Data acquisition

Statistical analysis

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