Geographia Technica, Vol 18, Issue 1, 2023, pp. 71-84
IDENTIFYING CLIMATE CHANGE VULNERABILITY BASED ON LAND COVER INDICATORS: A CASE STUDY IN SURABAYA, INDONESIA
Floriberta BINARTI 
, Albertus Joko SANTOSO
ABSTRACT: Surabaya is facing the threat of climate change indicated by the increase in air and surface temperature. The city has a risk of sinking by 2050 if the global warming cannot be resolved. Several related studies established that the change in land cover and land use is accompanied by the increase in surface temperature, which will be addressed in this present study. Therefore, this study aimed to examine the impact of land use/cover on the increase in air/surface temperature and investigate the contribution of land cover indicators to climate change in Surabaya as the basis of the identification of spatial climate change vulnerability. Data were collected from satellite images obtained over a long period and processed with GIS-based software to obtain an overview of changes. Mined long-term historical climate data and satellite imagery were processed into a land surface temperature map (LST), describing the tendency of climate change. The satellite imagery data from 2013 to 2021 was used to have an overview of land use and land cover changes based on indicators of built-up area (NDBI), surface imperviousness (NDISI), vegetation (NDVI), and water (NDWI). The contribution of each indicator to the surface temperature was analyzed using the multivariate regression method. The significant contribution of the land cover indicators to the surface temperature as the results means that NDBI, NDISI, NDVI, and NDWI can be used as indicators in climate change vulnerability assessment. The sequential contribution weights to the surface temperature are NDISI, NDWI, NDVI, and NDBI. Furthermore, the climate change vulnerability map of Surabaya City was developed based on the contribution weights, which the pattern of vulnerability levels corresponds to the pattern of water index values.
Keywords: Climate change vulnerability, Land cover indicator, Satellite imagery, Surface temperature
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