Application of geomatic technology for geological map updating

Abstract

This study focuses on applying integrated remote sensing and GIS technologies to geological, rock formation units studies in the northern part of Thailand and eastern part of Myanmar (Burma) area, covering around 60 square kilometer. The major techniques have been investigated and employed include image processing, data fusion, DEM processing and 3D visualization, which incorporated from topographic map (1:50,000 scale), image classification, image registration, GIS overlying techniques. This paper presents geological study results applied to two sets of satellites imageries for rock types. The study areas covered deciduous forest in mountainous region. The satellite data include Landsat TM taken on 10 February, 1989 and ASTER taken on February, 2003. The spatial resolution of TM is 28.5 m and ASTER is either 15m or 30m. Remote sensing data has been used for lineament_analyses to suggest subsurface structure, and in the mapping of geologic structure, lithology, and drainage features. The two main sources of satellite image data are Landsat TM and ASTER data. Additional datasets are used in conjunction with data derived from Thai Mineral Resource Department, geological feature of Burma and rock unit classification. ASTER SWIR bands has been analysized for lithological mapping in this paper and compared with the two band ratio,true colour and false colour techniques have been used. The spatial association between rocks occurrences and geological features are characterised quantitatively. Remotely-sensed data are used to extract additional geological information. Geoinformation derived from quantitative characterisation of spatial between rocks and geological features are used in GIS-based predictive geological mapping. Supervised classification method based on 2D scatter plot. Image classification results were poor for rock unit identification because study area is covered bydense forest. The drainage patterns and geological structure linearments have been recognised in satellite image and DEM derived image.