The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1621–1627, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1621-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1621–1627, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1621-2020

  22 Aug 2020

22 Aug 2020

IDENTIFYING LAND USE AND LAND COVER (LULC) CHANGE FROM 2000 TO 2025 DRIVEN BY TOURISM GROWTH: A STUDY CASE IN BALI

A. B. Rimba1,3,4, T. Atmaja2, G. Mohan1,3, S. K. Chapagain1, A. Arumansawang5, C. Payus1,3,6, and K. Fukushi1,3 A. B. Rimba et al.
  • 1United Nations University-Institute for the Advanced Study of Sustainability (UNU-IAS), 5-53-70, Shibuya-Ku, Tokyo 150-8925, Japan
  • 2Department of Urban Engineering, University of Tokyo, 7-3-1, Bunkyo-ku, Tokyo 113-8654, Japan
  • 3Institute for Future Initiatives (IFI), University of Tokyo, 7-3-1 Bunkyo-ku, Tokyo 113-8654, Japan
  • 4Center for Remote Sensing and Ocean Sciences (CReSOS), Udayana University, PB Sudirman St., Denpasar, Bali 80232, Indonesia
  • 5Department of Mining Engineering, Hasanuddin University, Poros Malino Street km.6, Bontomarannu, Gowa, South Sulawesi 92171, Indonesia
  • 6Faculty of Science & Natural Resources, Universiti Malaysia Sabah, Kota Kinabalu 88400, Sabah, Malaysia

Keywords: Sarbagita, land change model (LCM), Landsat 8 OLI, land use and land cover (LULC), tourism, Multi-Layer Perceptron (MLP) neural network

Abstract. Bali has been open to tourism since the beginning of the 20th century and is known as the first tourist destination in Indonesia. The Denpasar, Badung, Gianyar, and Tabanan (Sarbagita) areas experience the most rapid growth of tourism activity in Bali. This rapid tourism growth has caused land use and land cover (LULC) to change drastically. This study mapped the land-use change in Bali from 2000 to 2025. The land change modeller (LCM) tool in ArcGIS was employed to conduct this analysis. The images were classified into agricultural land, open area, mangrove, vegetation/forest, and built-up area. Some Landsat images in 2000 and 2015 were exploited in predicting the land use and land cover (LULC) change in 2019 and 2025. To measure the accuracy of prediction, Landsat 8 OLI images for 2019 were classified and tested to verify the LULC model for 2019. The Multi-Layer Perceptron (MLP) neural network was trained with two influencing factors: elevation and road network. The result showed that the built-up growth direction expanded from the Denpasar area to the neighbouring areas, and land was converted from agriculture, open area and vegetation/forest to built-up for all observation years. The built-up was predicted growing up to 43 % from 2015 to 2025. This model could support decision-makers in issuing a policy for monitoring LULC since the Kappa coefficients were more than 80% for all models.