Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama

Abstract

Mangrove stands of differing species composition are hard to distinguish in conventional, coarse resolution satellite images. The new generation of meter-level satellite imagery provides a unique opportunity to achieve this goal. In this study, an IKONOS Geo bundle image and a QuickBird Standard bundle image were acquired for a study area located at Punta Galeta on the Caribbean coast of Panama. The two images cover the same area and were acquired under equivalent conditions. Three comparison tests were designed and implemented, each with separate objectives. First, a comparison was conducted band by band by examining their spectral statistics and species by species by inspecting their textural roughness. The IKONOS image had a higher variance and entropy value in all the compared bands, whereas the QuickBird image displayed a finer textural roughness in the forest canopy. Second, maximum likelihood classification (MLC) was executed with two different band selections. When examining only multispectral bands, the IKONOS image had better spectral discrimination than QuickBird while the inclusion of panchromatic bands had no effect on the classification accuracy of either the IKONOS or QuickBird image. Third, first- and second-order texture features were extracted from the panchromatic images at different window sizes and with different grey level (GL) quantization levels and were compared through MLC classification. Results indicate that the consideration of image texture enhances classifications based on the IKONOS panchromatic band more than it does classifications based on comparable QuickBird imagery. An object-based classification was also utilized to compare underlying texture in both panchromatic and multispectral bands. On the whole, both IKONOS and QuickBird images produced promising results in classifying mangrove species.