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Effectiveness of using very high resolution imagery (IKONOS) for land use mapping
 Ghaleb Faour and Rania Bou Kheir National Council for Scientific Research Remote Sensing Center 11-8281, Beirut, Lebanon. Email: gfaour@cnrs.edu.lb, raniabk@cnrs.edu.lb Abstract The objective of this study was to identify the potential benefit and limitations of using very high resolution satellite images IKONOS in producing land cover/use maps at large scale (1:5,000). For that, a visual interpretation was performed on pan-sharpen IKONOS imageries with 1 m spatial resolution (October 2000) covering representative areas in Lebanon situated on the coast and at the mountains. A land cover/use legend was developed according to FAO classification including 72 classes divided into four hierarchical levels. Afterwards, spatial and statistical comparisons were conducted between the results obtained from the interpretation of IKONOS imageries and existing land use inventories. The later were produced from Indian satellite images (IRS-1C, 5.8 m) merged with multispectral Landsat TM images (30 m), both acquired in October 2000, using visual interpretation techniques. These comparisons indicate the enhancement identification capabilities offered by IKONOS images in most cases and the limitations that can be offset in some other cases. IKONOS images show an improvement of land use maps spatial accuracy in mountainous areas more than coastal areas. Moreover, they were particularly effective at delineating impervious surfaces prevalent in urban areas, which are problematic to map from other low resolution remotely sensed data. The visual interpretation of IKONOS imagery performed at 88.5 percent level of accuracy, whereas the processing of Landsat TM and IRS yielded 82 percent accuracy. The degree of spatial coincidence between land cover/use maps was equal to 87%. 1. Introduction Satellite remote sensing is widely accepted as a technique to study land use. The later is of extreme importance in protecting water quality and controlling erosion and associated sedimentation. Two main approaches to land use mapping have been reported. The first analysis involves spectral classification (textural, structural) of satellite imageries into land use categories while the second method, i.e. visual interpretation, depends on several image characteristics (e.g., tone or colour, texture, size, shadow, pattern, location and associations) in order to identify and deduce the significance of the components of the image. The majority of those characteristics are not used in conventional digital classifications. Although, digital classification techniques are considered much less subjective than visual interpretation; land use classes vary spectrally, especially when land covers present high spatial complexity. Moreover, significant advantages of visual interpretation of image products over classified images can be distinguished as follows: 1) less time required with photo interpretation methods to create a usable product; 2) little expense beyond the acquisition of the image; 3) image illumination problems such as shadows and brightly illuminated surfaces can be used as an interpretation aid; and 4) minimal expertise required to interpret the image. Several attempts using different approaches (spectral image classification, visual interpretation) have been made to test the accuracy of each method (Conese and Maselli, 1991; Janssen and Vanderwel, 1994; Mas and Ramirez, 1996; Palacio-Prieto and Luna-Gonzalez, 1996; Bethel et al., 2001). These studies have demonstrated the performance of visual interpretation methods over automated ones in getting a broad-picture view of an area to understand land cover types and patterns. Recent advances in technology have made a tremendous contribution to remote sensing through the launching of new digital sensors and improved algorithms to process imagery. Hence, the use of very high resolution satellites (IKONOS, Quickbird) had implemented new challenges to land use mapping and is becoming substitute for data derived from time consuming aerial photo interpretation. The objective of this study is to assess the capability and effectiveness of IKONOS data for such a purpose through comparing the existing land use inventories with the results that can be obtained via the interpretation of IKONOS imageries. This assessment can help researchers in identifying the best remote sensing data sources needed to create land use inventories.
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