Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link
 

 

 

Zarate-Valdez, JL; Whiting, ML; Lampinen, BD; Metcalf, S; Ustin, SL; Brown, PH (2012). Prediction of leaf area index in almonds by vegetation indexes. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 85, 24-32.

Abstract
Three levels of scale for determining leaf area index (LAI) were explored within an almond orchard of alternating rows of Nonpareil and Monterey varieties using hemispherical photography and mule lightbar (MLB) at ground level up to airborne and satellite imagery. We compared LAI estimates of 56 fisheye photos strategically placed in the orchard to validate 500,000 MLB point scans of a small portion of the aisles between tree rows to water and vegetation indexes of MASTER (MODIS/ASTER simulator) and Landsat 5 imagery. The high correlation of fisheye photo LAI to MLB LAI estimates establishes this new method against the measurement standard within the plant community while significantly increasing sample size. MLB LAI and MASTER vegetation indexes, such as NDWI (normalized difference water index), GMI (Gitelson-Merzlyak index) and NDVI (normalized difference vegetation index), were highly correlated (r(2) = 0.90). In addition, a high correlation ( r(2) = 0.80) between the MLB measured LAI and selected Landsat derived vegetation indexes (VI) was found. This scaling and validation of LAI estimate expands the spatial area and frequency of determination for time series analysis of crop phenology studies. (C) 2012 Elsevier B.V. All rights reserved.

DOI:
0168-1699

ISSN:
10.1016/j.compag.2012.03.009

NASA Home Page Goddard Space Flight Center Home Page