Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

Sensors

Atiqur Rahman¹  Leonid Roytman¹  Nir Y. Krakauer¹  Mohammad Nizamuddin¹ 

[1] NOAA-CREST, CCNY,138^th Street and Convent Ave, New York, NY 10031,USA; E-Mails:

关键词: Remote sensing;    Vegetation health indices;    Correlation;    Principal Component Regression;   

DOI  :  10.3390/s90402968

来源: mdpi

【 摘 要 】

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

【 授权许可】

CC BY   
© 2009 by the authors; licensee MDPI, Basel, Switzerland