Integration GIS-MCDA and remote sensing imagery for ecological vulnerability assessment

Ecological vulnerability (EV) is a condition that describes the comparison of ecological resilience and ecological sensitivity in the face of pressures and disturbances or after being influenced by natural factors. Resilience indicators and sensitivity indicators are composed of set components that have different criteria depending on spatial heterogeneity conditions. These criteria affect the spatial distribution of ecological vulnerability levels in each region. Integration of Geographic information system and Multicriteria decision analysis (GIS-MCDA) with remote sensing imagery is considered to be capable of measuring the influence of each criterion on EV. The combination of GIS-MCDA supports more comprehensive spatial analysis because the effect of each criterion is determined by systematic weighting. Remote sensing imagery helps identify spatial heterogeneity through image pixel values that have different spectral signatures for each object in every single season. Remote sensing imagery as the primary data source on spatial analysis has advantages such as real-time data recording, rapid detection, and large area coverage that help understand region characteristics for EV factors identification. Therefore, this study aims to determine the indicators of ecological vulnerability from the ecological resilience and sensitivity aspect; and to measure the ecological vulnerability by integrating GIS-MCDA with remote sensing image processing. The indicators and criteria for each parameter are determined based on the literature study and the biophysical heterogeneity of the area. The final results are five classes of ecological vulnerability: low (14.19), low (54.33), moderate (14.86), high (15.41), and very high vulnerability (1.19). The distribution of EVI values forms a "bullseye"pattern because the topography of the WROB of Purwokerto affects the spatial heterogeneity of the environment. © 2023 Author(s).