By Topic

Spectral inputs to crop identification and condition assessment

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Bauer, M.E. ; University of Minnesota, St. Paul, MN, USA

This review discusses, from an agronomic perspective, contemporary remote sensing research on crop identification and condition assessment. The paper begins with a review of the basic relationships of reflectance and biophysical properties of crop canopies. Leaf area index is shown to be a key parameter linking multispectral reflectance and crop physiology. Major advancements in capability, particularly the development of spectral-temporal profile models, for crop identification have been made in the past decade. The same model form has been used for estimating crop development stage, leaf area index, and canopy light interception as inputs to crop growth and yield models. The paper concludes with a discussion of potential advancements in capability with respect to new sensors.

Published in:

Proceedings of the IEEE  (Volume:73 ,  Issue: 6 )