Rice yield estimation using remote sensing and simulation model

Remote sensing techniques have the potential to provide information on agricultural crops quantitatively, instantaneously and above all nondestructively over large areas. Crop simulation models describe the relationship between physiological processes in plants and environmental growing conditions. The integration between remote sensing data and crop growth simulation model is an important trend for yield estimation and prediction, since remote sensing can provide information on the actual status of the agricultural crop. In this study, a new model (Rice-SRS) was developed based mainly on ORYZA1 model and modified to accept remote sensing data as input from different sources. The model can accept three kinds of NDVI data: NOAA AVHRR(LAC)-NDVI, NOAA AVHRR(GAC)-NDVI and radiometric measurements-NDVI. The integration between NOAA AVHRR (LAC) data and simulation model as applied to Rice-SRS resulted in accurate estimates for rice yield in the Shaoxing area, reduced the estimating error to 1.027%, 0.794% and (−0.787%) for early, single, and late season respectively. Utilizing NDVI data derived from NOAA AVHRR (GAC) as input in Rice-SRS can yield good estimation for rice yield with the average error (−7.43%). Testing the new model for radiometric measurements showed that the average estimation error for 10 varieties under early rice conditions was less than 1%. Project supported by the National Defense Scientific and Technological Committee of China(No. Y97#14-6-2)     

A Practical Application of Ocean Color Methodology to an Undergraduate Curriculum

Recently there have been newly launched ocean color satellites which target the coastlines at unprecedented scales. Science education curricula can benefit from the provision of small low-cost spectroradiometers and curriculum supplemental materials that can be incorporated in a “hands on” teaching approach to explain and demonstrate remote sensing reflectance principles. A lesson in which a progressive set of spectral measurements of familiar and unfamiliar objects and natural waters acquired by students using a small fiberoptic probe and spectroradiometer is presented. This lesson has a dual purpose. The first is to serve as a teaching supplement to high school science curricula while paralleling the National Science Education Standards (NSES) for NASA ocean color products, as well as other satellite ocean products such as GLI and MERIS. The second is to focus on the scientific goals of the graduate-school bound undergraduate student by providing a fundamental understanding of the principles of passive ocean color remote sensing that will perhaps nurture the interest of some students toward research involving utilization of NASA’s Earth science data products. We intend to have these spectroradiometers readily available for use by teachers in the Earth sciences through a publicly available technology library.