International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-4/W16
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 433–440, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-433-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 433–440, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-433-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Oct 2019

01 Oct 2019

LAND USE/LAND COVER ASSESSMENT IN A SEISMICALLY ACTIVE REGION IN KUNDASANG, SABAH

N. A. Mohd Kamal1, K. A. Razak2, and S. Rambat1 N. A. Mohd Kamal et al.
  • 1Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia Kuala Lumpur, 54100 Kuala Lumpur, Malaysia
  • 2Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia Kuala Lumpur, 54100 Kuala Lumpur, Malaysia

Keywords: Land Use Land Cover, Geohazards, Change Detection, Remote Sensing

Abstract. Land use development in the mountainous environment must be risk-informed especially in the area highly vulnerable to disaster and extreme climate. Kundasang, Sabah, Malaysia is one of the tourist-demanding areas characterized by mountainous landscape and agriculture activity. The increasing number of tourists and agriculture activity affects the land use exploration. This area is vulnerable to geohazards such as earthquakes and landslides due to its location under seismically active region and complex geological environment. In this study, geospatial technique was used to assess the land use activity in Kundasang, Sabah pertaining to geological risk in this area. The assessment started with the identification of geohazard activities and its associated tectonic features using field investigation and mapping for coherent visualization. Subsequently, multiple high-resolution satellite imageries were used to detect land use changes before and after the disaster. In order to detect the land use change, object-based change detection was applied based on segmentation and object-based classification compared to the classical pixel-based method. The output of this study shows a number of field evidences associated with geohazard features that affecting the land use activities especially build-up area and agriculture land. In conclusion, the combined results provide an important benefit for better understanding the interaction between geohazard activity and landscape patterns in order to support the planning and decision making through spatial analysis and appropriate object-based processing method.