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Proceedings Paper

Improved cross-sensor resolution enhancement for landcover products
Author(s): Todd A. Jamison; Ernest A. Carroll
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Paper Abstract

The overall accuracy of digital landcover products can often be improved through the use of fused imagery products generated by good cross-sensor resolution enhancement algorithms. This paper describes a process for fusing medium resolution multi-spectral data, such as Landsat and SPOT, with National Aerial Photographic Program (NAPP) photographs. The NAPP has a goal of providing coverage of the 48 contiguous United States every 10 years at high spatial resolution [i.e., 2 meter ground resolving distance (GRD)]. NAPP and National High Altitude Photography (NHAP) provide a wealth of current and historic high resolution data for environmental and natural resource studies. Despite their comprehensive coverage and high spatial resolution, these images are often overlooked for use in large-scale computerized classification problems, because: (1) they are photographic 'analog' data stored on film, not digital data on magnetic media; (2) comprehensive support data (e.g., aircraft x, y, z, roll, pitch, and yaw) is lacking; (3) they are not geocoded or orthorectified and random aircraft motion combined with sensor projection make it difficult to georegister; and (4) their radiometric quality varies both within and between images. This paper describes a technique for merging NAPP/NHAP data with lower resolution satellite data such as Landsat and SPOT which results in a fused image product that has the high spatial resolution of the NAPP/NHAP data and the spectral quality of the satellite data. The technique permits the user to utilize this higher resolution data to improve the quality and accuracy of their landcover, change detection, stress analysis, or other remote sensing products. Specific published results show an improvement in the overall accuracy from 79.4% correct classification using Landsat TM (25 meter GSD) alone to over 94.2% correct classification using higher resolution (5 meter GSD) data. We also discuss our future plans related to these techniques and their applications.

Paper Details

Date Published: 17 June 1996
PDF: 13 pages
Proc. SPIE 2758, Algorithms for Multispectral and Hyperspectral Imagery II, (17 June 1996); doi: 10.1117/12.243213
Show Author Affiliations
Todd A. Jamison, Observera, Inc. (United States)
Ernest A. Carroll, Observera, Inc. (United States)

Published in SPIE Proceedings Vol. 2758:
Algorithms for Multispectral and Hyperspectral Imagery II
A. Evan Iverson, Editor(s)

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