Quantitative Land-Use and Landslide Assessment: A Case Study in Rize, Türkiye

Kasahara N., Gonda Y., Huvaj N.

WATER (SWITZERLAND), vol.14, no.11, pp.1-15, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 11
  • Publication Date: 2022
  • Doi Number: 10.3390/w14111811
  • Journal Name: WATER (SWITZERLAND)
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Compendex, Environment Index, Food Science & Technology Abstracts, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Page Numbers: pp.1-15
  • Keywords: land use, quantitative landslide assessment, Rize, satellite images, tea garden, RISK-ASSESSMENT, TEA PLANTATION, SUSCEPTIBILITY, INVENTORY, ARDESEN, TURKEY, GIS
  • Middle East Technical University Affiliated: Yes


Currently, many studies have reported that many landslides occur in tea or rubber plantation areas. In these areas, it is important to make a landslide susceptibility map and to take necessary measures to mitigate landslide damage. However, since historical landslide distribution data and land use data are not available, quantitative landslide assessment measurements have not been made in many countries. Therefore, in this study, landslide distribution maps and land use maps are created with worldwide available satellite imagery and Google Earth imagery, and the relationship between landslides and land use is analyzed in Rize, Türkiye. The results show that landslides are 1.75 to 5 times more likely to occur in tea gardens than in forests. It was also found that land use has the highest contribution to landslides among the landslide conditioning factors. The landslide assessment, using a simple landslide detection method and land use classification method with worldwide available data, enabled us to quantitatively reveal the characteristics of landslides. The results of this study reveal that quantitative landslide assessments can be applied in any location, where relatively high resolution satellite imagery and Google Earth imagery, or its alternatives, are available.