SYNTHETIC IMAGERY FOR VISUALIZATION OF CROP CANOPY STATUS

Authors: ALARCON, VLADIMIR - MISS ST; Sassenrath, Gretchen

Submitted to: American Society for Photogrammetry and Remote Sensing Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 1/14/2005
Publication Date: 3/7/2005
Citation: Alarcon, V.J., Sassenrath, G.F. 2005. Synthetic imagery for visualization of crop canopy status. American Society for Photogrammetry and Remote Sensing Proceedings. CD-ROM.

Interpretive Summary: Systems have been developed for continuous crop monitoring for irrigation scheduling. These systems, based on thermal or visual remote imagery of the crop canopy, have been successfully deployed in arid growing environments for detection of crop water stress and scheduling of irrigation. However, their use in humid environments has been hampered by the high humidity levels and frequent cloud cover. We are interested in developing a sensing system that can be used to monitor cotton crop water status, and predict the need for irrigation prior to any yield-limiting stress. A first step in the development of this system has been the examination of cotton canopy reflectance functions, and factors contributing to changes in the reflectance from the canopy. To facilitate this study, we have developed a method of examining the entire reflectance spectra from the canopy, and examining individual components of the spectra that contribute to changes with crop stress. Previous research described the Fourier transformation of the spectra, development into synthetic imagery, and visualized in the JAVA interface. In this paper, we extend the use of the JAVA interface, and demonstrate its utility in presenting reflectance data for cotton canopies.

Technical Abstract: We are interested in adapting remote sensing technologies for continuous monitoring of crop status to determine water use and plant water stress. Previous research on crop water stress has demonstrated the utility of remote sensing as a production tool in arid regions. The commonly high humidity levels and frequent cloud cover in the lower Mississippi River Valley complicate the adaptation of these systems for crop monitoring in our area. Four factors contribute to the potential changes observed in a remote image: a) leaf physiological status, b) leaf angle, c) vegetative development (canopy structure, leaf area index, etc), and d) soil reflectance. We have adapted Fourier transformed signals from each of the components into synthetic imagery to explore the factors impacting canopy reflectance. In this paper, a web-based simulation environment for generating hyper-spectral synthetic imagery of cotton plots is presented. The system was developed using Java and is based on the synthetic imagery program developed previously. The mathematical and numerical formulation of the model is described. The core computing components of the simulation environment were written in C for their computational efficiency. The emerging Java Native Interface (JNI) technique and standard Java techniques were used to design a user-friendly simulator. The simulation system provides interactive user control and real time visualization of the resulting hyper-spectral image through standard web browsers. By generating a range of synthetic images of mixed individual components, we are able to separately examine each of the factors potentially impacting canopy reflectance. We are interested in adapting remote sensing technologies for continuous monitoring of crop status to determine water use and plant water stress. Previous research on crop water stress has demonstrated the utility of remote sensing as a production tool in arid regions. The commonly high humidity levels and frequent cloud cover in the lower Mississippi River Valley complicate the adaptation of these systems for crop monitoring in our area. Four factors contribute to the potential changes observed in a remote image: a) leaf physiological status, b) leaf angle, c) vegetative development (canopy structure, leaf area index, etc), and d) soil reflectance. We have adapted Fourier transformed signals from each of the components into synthetic imagery to explore the factors impacting canopy reflectance. In this paper, a web-based simulation environment for generating hyper-spectral synthetic imagery of cotton plots is presented. The system was developed using Java and is based on the synthetic imagery program developed previously. The mathematical and numerical formulation of the model is described. The core computing components of the simulation environment were written in C for their computational efficiency. The emerging Java Native Interface (JNI) technique and standard Java techniques were used to design a user-friendly simulator. The simulation system provides interactive user control and real time visualization of the resulting hyper-spectral image through standard web browsers. By generating a range of synthetic images of mixed individual components, we are able to separately examine each of the factors potentially impacting canopy reflectance.