Conference Paper

Methods and techniques for the correction of natural shades on aerial-photo or satellite maps

Conference: 20th International Cartographic Conference, At Beijing

ABSTRACT This study examines possible ways first to restrain or even eliminate the "false" shades of the relief, created mainly by the direction of the natural sunlight presented on aerial-photo or satellite images, and then to replace them with the "correct" artificial hill-shading shades according to the cartographic principles of legibility and perceptibility, which allow the map user to easily and clearly interpret the relief's shapes and formations. The natural shades are eliminated from the aerial-photo or satellite images by applying special radiometric and statistical processing in order to create images free of shades. An analytical description of the earth's surface -stored as a digital elevation model-combined with computing tools of a variety of hill-shading methods are used to produce a cartographic "correct" image of shades of the study area. Finally, image-processing techniques are applied to create new images composed by the "correct" shades and the shaded free aerial-photo or satellite images. The outcomes indicate the potential of the incorporated methods and applied techniques in order to construct aerial-photo or satellite maps clearly and legibly perceived. KEY-WORDS: Aerial-photo/satellite maps, relief visualization, hill-shading, illumination models, correction of topographic effect.

0 Bookmarks
 · 
134 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The natural relief shades present in earth’s surface images are affected by physical lighting procedures that take place along the trace of sunlight from the initial radiation to the final capturing by sensors. An analysis of all these combined factors is given in the present paper in order to define their qualitative meaning and evaluate their influence on the variation of tones that forms the relief effect. These efforts are tested both on computational and conceptual level with examples of different lighting conditions on simulated solids. In addition, the qualitative and quantitative approaches of light components are discussed in the context of suggesting a systematic, practical strategy for the selection of the necessary parameters of relief shading for several cartographic products.
    21st International Cartographic Conference, Durban; 08/2003
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Three dimensional (3D) mapping has been used widely in the spatial industry as a powerful technique for rendering artificial objects and their surrounding topography. However, an accurate and effective 3D modelling of complex features e.g. feature rich buildings and trees, is still challenging. The aim of this study is to develop an efficient framework to obtain a high-accuracy 3D model of urban buildings using Airborne Laser Scanning (ALS) data and aerial ortho-imagery. First, building outlines and a digital surface model are extracted from ALS data. Aerial ortho-imagery is then integrated to improve the accuracy of building outlines. Digital photos of building facades are patched to the 3D model for texture mapping. The accuracy analysis is conducted by assessing the heights and outlines of extracted features. As far as the authors know, this is the first accuracy evaluation of constructed 3D models. The digital surface model (DSM) shows vertical errors of less than 12 cm. Building heights are less accurate than the DSM, with errors of less than 22 cm. This difference is explained in the paper. In order to examine the building model more closely, the buildings are classified into three categories: simple rectangular objects, complex polygons, and curved outlines. The horizontal accuracy of the three categories ranges from 42 to 64 cm in Easting (1σ) and 16 to 48 cm in Northing (1σ). The results show that the horizontal coordinates of simple rectangular buildings are more accurate than those of complex polygons or circular-shape buildings. Mean errors and root mean square errors for each category are presented in the paper.
    Survey Review 05/2011; 43(320):109-122. · 0.29 Impact Factor

Full-text (2 Sources)

Download
199 Downloads
Available from
Jun 1, 2014