Paper
22 October 2010 A high-resolution index for vegetation extraction in IKONOS images
M. Chikr El-Mezouar, N. Taleb, K. Kpalma, J. Ronsin
Author Affiliations +
Abstract
In monitoring vegetation change and urban planning, the measure and the mapping of the green vegetation over the Earth play an important role. The normalized difference vegetation index (NDVI) is the most popular approach to generate vegetation maps for remote sensing imagery. Unfortunately, the NDVI generates low resolution vegetation maps. Highresolution imagery, such as IKONOS imagery, can be used to overcome this weakness leading to better classification accuracy. Hence, it is important to derive a vegetation index providing the high-resolution data. Various scientific researchers have proposed methods based on high-resolution vegetation indices. These methods use image fusion to generate high-resolution vegetation maps. IKONOS produces high-resolution panchromatic (Pan) images and low-resolution multispectral (MS) images. Generally, for the image fusion purpose, the conventional linear interpolation bicubic scheme is used to resize the low-resolution images. This scheme fails around edges and consequently produces blurred edges and annoying artefacts in interpolated images. This study presents a new index that provides high-resolution vegetation maps for IKONOS imagery. This vegetation index (HRNDVI: High Resolution NDVI) is based on a new derived formula including the high-resolution information. We use an artefact free image interpolation method to upsample the MS images so that they have the same size as that of the Pan images. The HRNDVI is then computed by using the resampled MS and the Pan images. The proposed vegetation index takes the advantage of the high spatial resolution information of Pan images to generate artefact free vegetation maps. Visual analysis demonstrates that this index is promising and performs well in vegetation extraction and visualisation.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Chikr El-Mezouar, N. Taleb, K. Kpalma, and J. Ronsin "A high-resolution index for vegetation extraction in IKONOS images", Proc. SPIE 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 78242A (22 October 2010); https://doi.org/10.1117/12.866187
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Cited by 1 scholarly publication.
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KEYWORDS
Vegetation

High resolution satellite images

Earth observing sensors

Image fusion

Near infrared

Remote sensing

Spatial resolution

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