Identifying the relationship between changes in vegetation indices and the anthropogenic activities in the tropical Semarang City of Indonesia using space imagery

Abstract

The existence of vegetation in the watershed area as a function of maintaining the continuity of the process of soil infiltration, erosion resistance, and landslide resistance is essential. Studies that measure the existence of vegetation through vegetation index parameters by utilizing optical-based satellite imagery maps, as well as radiometric waves or Radio Detection and Ranging (RADAR), have been widely carried out. However, attempts to test it to formulate it into vegetation resilience indices on the scale of functional areas such as watersheds are still a challenge in itself. In this study, the vegetation resilience index was measured by looking for spatial change patterns from Normalized Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI) in 2015-2021. This spatial pattern change is associated with anthropogenic factors represented by the dynamics of changes in vegetation to housing and population distribution. The use of residential land is obtained from the interpretation of optical-based satellite imagery maps from Google Earth sources mitigated by the administrative boundaries of villages. The population change was obtained from statistical data on the village’s population in the same year. The change in vegetation index, residential, and inhabitants were examined by the Spatial Autocorrelation (SA) using the Global Moran’s Index (GMI). Finally, the changes in the spatial patterns in vegetation indices, residentials index, and inhabitant index were conducted with correlation analysis to determine the relationship between these parameters. The results of GMI indicate a tendency towards dispersion in NDVI and SAVI, which showed a linear index decline in the dry season but weak linear indices incline in the wet season. The trend of dispersion patterns also occurs in residential and inhabitants, showing a linear index decline with a high confidence level (R2=0.9171 in residentials and R2=0.5872 in inhabitants). The relationship between pattern changes in NDVI and SAVI and Residential and Inhabitant found by the following formula; NDVI = 0.214173 -3.12952 * Residential + 6.457788 * Inhabitant; SAVI = 0.101544 + 0.120294 * Residential + 1.963223 * Inhabitant.