Geological Terrain Mapping using Geographic Information System (GIS) and Drone Photogrammetry

Abstract

The research area was conducted within the Bukit Persekutuan, Kuala Lumpur, and it was located at the latitude 3° 8'32.93"N and longitude 101°40'32.80"E. The researcher carried out geological terrain mapping to evaluate the research area in accordance with the geological terrain classification attributes of each thematic map produced, namely, Terrain map, slope gradient map, erosion, and instability map, as well as construction suitability map. The occurrence of landslide events within the research area becomes a major contributing factor to thoroughly conducting an investigation by field mapping and analysing using the Geographic Information System (GIS) technology. The application of Geographic Information System (GIS) and drone photogrammetry images play an essential role to analyze and process the data, thus, generate the thematic maps. The research area indicates that about 79.11% of the overall area was not appreciable with erosion, 8.58% contribute to the erosion, 11.00% of recent general instability, and 2.97% represent a landslide event. The suitability for development mapping illustrated Class I (23.40), Class II (36.37%), Class III (26.39%), and Class IV (15.50%) where it can be referred to the construction suitability classification system, the suitability for development was high in class I, moderate in class II, low in class III and not suitable in class IV.

Face Mapping in Open Pit Mines—A New Approach

“…The technological evolution in this field comes with remote sensing techniques, for example, ground-based, closerange hyperspectral sensors measure remote reflectance properties of mineral and rock masses, resulting in unsupervised classification waste from ore [2]. Many other researchers have recently published articles, which present numerous cases of UAV-photogrammetry applications, such as the identification of faults, fractures, bedding surfaces [3], rock mass discontinuities and kinematic stability of pit slopes [4], the data collection for geological survey and generation of thematic maps with potential landslides and steep rock faces [5,6], the classification of the lithology of mining face, and using photogrammetry point cloud data and machine learning algorithms [7]. The drone-photogrammetry technique has contributed to geological mapping and monitoring for many years, also providing feedback on slope stability, mineral exploration, blasting processes, and model improvements [8][9][10][11][12].…”