spatial enhancement of modis-based images of leaf area index application to the boreal forest region of northern alberta, canada叶面积指数的空间增强modis-based图像应用于北方森林的阿尔伯塔省北部地区,加拿大.pdf

Remote Sens. 2010, 2, 278-289; doi:10.3390/rs2010278 OPEN ACCESS Remote Sensing ISSN 2072-4292 /journal/remotesensing Article Spatial Enhancement of MODIS-based Images of Leaf Area Index: Application to the Boreal Forest Region of Northern Alberta, Canada Quazi K. Hassan 1, *and Charles P.-A. Bourque 2 1 Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr. NW Calgary, Alberta, T2N 1N4, Canada 2 Faculty of Forestry and Environmental Management, University of New Brunswick, P.O. Box 44555, Fredericton, New Brunswick, E3B 6C2, Canada; E-Mail: cbourque@unb.ca * Author to whom correspondence should be addressed; E-Mail: qhassan@ucalgary.ca; Tel.: +1-403-210-9494; Fax: +1-403-284-1980. Received: 24 November 2009; in revised form: 4 January 2010 / Accepted: 5 January 2010 / Published: 8 January 2010 Abstract: Leaf area index (LAI) is one of the most commonly used ecological variables in describing forests. Since 2000, 1-km resolution Moderate Resolution Imaging Spectroradiometer (MODIS)-based 8-day composites of LAI have been operationally available from the National Aeronautics and Space Administration (NASA), USA, at no cost to the user. In this paper, we present a simple protocol to enhance the spatial resolution of NASA-produced LAI composites to 250-m resolution. This is done by fusing MODIS-based estimates of enhanced vegetation index (EVI), consisting of 16-day 250-m