A non-linear regression form for vegetation index-crop yield relation incorporating acquisition date normalization

$59.35 plus tax (Refund Policy)

Buy Article:

Abstract:

A non-linear form relating vegetation indices (VI) to crop grain yields which normalizes for differences in acquisition date is suggested. It is based on the assumption that deviations in VI near the peak VI follow a quadratic behaviour. This form gave a higher R2 value than a simple VI-yield linear model on a multi-year, multi-location data set of IRS (Indian Remote Sensing Satellite-1A) LISS-I(Linear Imaging Self Scanner-I) derived near-infrared (NIR)/red radiance ratios and wheat grain yields in a study site in Madhya Pradesh (India). As the suggested model includes time of peak as a variable, it allows integration of results from other sources, such as, weather-based crop phenology model or high repetivity spectral data into the VI-yield relation.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/014311697218520

Publication date: April 10, 1997

More about this publication?
Related content

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more